Alex’s venture wishlist

🤖 AI-Native Vertical Integration: Re-building conventional businesses from scratch with AI at the core (e.g., insurance brokerages) to capture both margin expansion and faster growth.

🛍️ Agentic E-Commerce Rails: Infrastructure that lets LLM agents query live stock & dynamic prices, then transact on behalf of users, effectively “rebundling” online retail.

🏠 Full-Stack Home-Buying Concierge: A vertically-integrated service that combines buyer’s agent, mortgage broking, conveyancing, surveys, moving logistics and utility switch-over in one flow.

💸 Autonomous Personal Finance: Hands-off AI that optimises day-to-day money (cards, cash-management, savings, investments) and executes money moves automatically.

🔓 Agent-to-Bank Open Finance: Interfaces that welcome browser-automation agents (think MCP/A2A endpoints or AI-friendly front-ends) so institutions stay discoverable and transactable without waiting for new Open Finance regulation.

🍛 Fast-Casual Indian Chain (fun one): A UK-wide grab-and-go curry brand, Leon-style, aimed at office workers who want reliable chicken tikka for £8.50 at lunch.

Other insights

🎯 Lead at Seed Still Differentiates: Many micro-funds can only “participate”; writing the term sheet at seed wins allocation and goodwill.

📍 UK Remains Fintech’s Best Launchpad: Despite some recent grumbles, the FCA sandbox, unified regulation and deep talent pool keep London the go-to jurisdiction.

🪄 Deep, “Boring” Fintech Pays Off: Wonky infra plays like treasury management looked dull…until rising rates & SVB’s collapse turned TreasurySpring into a hot commodity.

🦾 Quiet AI > Loud AI: Sometimes the non-consensus move is using AI without pitching it; let enterprise value, not buzzwords, do the talking.

🚧 Sceptical on Top-Down Open Finance: A decade on, mandated APIs still drag; permissionless agent automation may leapfrog regulatory efforts and reach true “open finance” faster.

Full Interview

So we usually start with an overview of the fund and the strategy.

Anthemis Group was founded in 2010 by Amy Nauiokas and Sean Park, originally investing the founders' own money from balance sheet capital into companies that would later be known as fintech companies, but that term didn’t exist yet.

Some of the early investments include Carta, The Climate Corporation, eToro, and Currency Cloud - early examples of familiar fintech products. We also invested in Betterment, which was the first robo-advisor, and Simple Bank, the first mobile banking app.

As of today, we're on our third early-stage fund. In 2016, we launched as a venture capital firm, investing third party capital, guided by a thesis closely aligned with our original focus: transforming financial services. Like most fintech investors, that space has expanded into many verticals through embedding, APIs, and so on.

Nowadays, we take a generalist approach, but make investments where we can be informed by our experience in regulated markets, with a focus around reshaping our global economy.

Geographically and stage-wise, we’re about 50/50 US and Europe. Within Europe, there's more of a focus on the UK, but we do invest outside the UK as well. Our third fund is seed-focused – very much investing at the seed stage. We like to lead and sit on boards. So we’re lead investors, which I think a lot of people are happy to hear when they pick up the phone. And yeah, we get good reviews from our founders on that.

So why do you think being a lead is important at that stage?

When you're a lead investor and you're talking with a company about how their round is going, a common refrain is, "Well, we have all the capital circled from participants, but we're just waiting for a lead."

We know that when we step into a room as a lead, you're automatically wanted – unless it's a very competitive deal. It's surprising, at the seed stage, when there are a tremendous number of emerging managers and smaller AUM funds who, through no fault of their own – it's just a function of fund size – can only participate and not lead.

To step in and be able to say, "Okay, we can lead this round and give you a term sheet," it's a nice position to be in. And it's oddly differentiating.

What's the last investment that you made that you can talk about?

We invested in a company called Cariqa. It's a German company involved in electric car charging payments.

Despite it being a relatively novel industry – charging for electric cars sounds modern and up to date – it has all the characteristics of an old-school industry. There are middlemen that need cutting out, older processes, and things that aren’t running as digitally as you'd imagine. Everything digital feels previous-generation – slow and outdated.

What Cariqa is doing is selling a payments experience to consumers. When they roll up to an EV charging terminal, if it's Cariqa-managed, they can use Cariqa to make the payment directly to the charging provider.

On the charge provider end, Carica enables dynamic pricing – adjusting charges based on energy cost, demand, and other factors. On the consumer end, it can surface the best price pumps in their area.

That’s an example of the applied fintech we're doing out of that fund – payments meets another vertical, in this case, electric cars.

Any non-consensus beliefs that you think drive your investing?

As a fund, there are a number of places where, because we know a lot about financial services, we can get involved in really nerdy, boring, and intricate things that I think aren't as flashy to other VCs.

For example, in our second fund, we invested in a company called TreasurySpring that does very interesting things with treasury management. We made that investment prior to the rise in interest rates and prior to the Silicon Valley Bank crisis.

So when all of that happened in that time window, the importance of good treasury management – specifically, treasury management not directly exposed to banks – became super important. We had made that investment as a very wonkish fintech play, and then suddenly:

A) the product became totally in demand, and

B) a lot of other VCs woke up to the idea of that being an interesting, investable area.

It did very well and raised a strong late Series A-type round from Balderton, a leading investor here in Europe.

They do treasury, but not with banks?

Yeah, they have a bunch of different money market products. We encourage our portfolio companies to use it immediately. They let you ladder tenors in a way that releases capital over time. So you put a chunk in, and then it comes out as you need it.

Oh, you put your startups on an allowance.

Sure. And in return, they get market-beating rates and a great product that’s robust against wacky things going on.

I think what you’re saying is that if you understand how things work and go deep, you can uncover opportunities.

Opportunity areas that might otherwise not be served or recognized by generalists.

Well, here’s a wonky question. I don’t know if you study this, but where do you think is the best jurisdiction for fintech, since you invest across a lot of different jurisdictions?

Firstly, it depends on what type of thing you're doing. There's a lot of interesting insurance stuff where the jurisdiction is Bermuda.

But I would say – and this is self-tooting or possibly patriotic, borderline nationalist – but if you look at Nikolai from Revolut, he had his pick of jurisdictions, and when Revolut was founded, he chose London. A lot of that was due to the FCA, which is our equivalent of the SEC – or maybe the other one, but you know what I mean.

Well, that's actually why it's better – fewer regulators, I think.

Sure. Or they’re unified into one. We also have the PRA – the Prudential Regulation Authority, though.

But still fewer.

Sure. But it’s not just the number – it’s also that, at the time, they had what they called the innovation sandbox.

It was a very collaborative place where small companies could play around with the limits of financial regulation before becoming too large for a misstep to be incredibly damaging. Then, once the regulator was comfortable, they could scale.

At the time, the FCA had a world-leading quality. It has slipped recently, and some people have concerns about its performance now. Everyone has concerns about their own regulator. But one thing that gets pointed out is that it used to be fantastic and now it's slightly less fantastic.

Still, I think the UK is – at least in Europe – the best place to set up a fintech company. Not least because of the talent and the concentration.

We have offices in New York, and I’d say if you’re picking East Coast vs. West Coast for fintech, it’s still consensus – but correct – to choose the place with the giant finance hub. Usually, that’s the right way to go.

There are people who’ll tell you there are interesting things happening in Dubai, and it’s great there’s a burgeoning community there. I know a lot of Sub-Saharan African deals have a Dubai topco.

But if you have your pick of the globe, base case: I’d go for the UK. If you need a market as large as the US, go for the US. Elsewhere – if you're doing credit cards, go to Brazil or somewhere with the right opportunity. If you're doing insurance, do Bermuda.

But all else being equal, I'm still a UK supporter on this.

Any themes you're excited about these days?

Our inbox is swamped with AI use cases, and that's going to come up in a lot of my wishlist. Enterprise use cases like AI compliance and AI workflows are very common and interesting.

The difficult part is picking the winner. It's easy for our LPs – many of whom are financial institutions – to come to us and say, "Hey, can you tell us about the AI onboarding companies out there at the moment?" And we're very happy to tell them all about those. But there's a difference between a client-vendor relationship and an investor-startup relationship. Trying to pick which one out of the ten doing that is going to win is much harder than onboarding one as a vendor.

Still, a very interesting theme, and it's going to create a lot of change in the financial industry. I’ve found it’s almost like the negative space of a theme. My wish list is filled with AI, but some of the most interesting conversations with founders right now are almost the anti-theme.

If you're starting a non-AI startup in 2025, you've probably got a fantastic reason for doing that. Or it's very binary – it either means you haven’t thought about it at all or you really, really have. Some of the best conversations we've had have been pretty non-AI focused because there's something very interesting going on elsewhere that not many people are paying attention to. I like the sort of inherent alpha to the non-AI stuff at the moment, even though there's a huge tidal wave of lucrative innovation happening in AI of course.

You're saying that you’re interested if people really have thought about a problem, understand a problem, and aren't just going where they think the current trend is or what everyone else is talking about?

Yeah, there's a selection effect to it. It almost means you can kind of switch your brain off. There are people who are very good at identifying well-thought-through innovation in a normal year – but in 2025, you can identify it with a pretty strong hit rate if all you have to do is go, are they doing something in AI or not? And if it's not in AI, then you can rely on that maxim.

That's interesting. To some extent, it feels like AI should be used in almost every startup, but that doesn't make it an AI startup.

Sure.

Sometimes there's this impulse – founders wanting to follow the money, seeing that AI is getting a lot of VC – thinking, "Oh, I have to position my thing as being AI," even if it's mostly not. Just throwing AI on top as a way of dressing it up.

Yeah, but don't you think it's such a baller move in the face of that trend to just say it's not even going to be on the deck? Yeah, we're going to use it – whatever, no big deal – we'll use it. It's just the next generation of software. We're a software company. But here's our problem, what we're going after, and here's the solution. Now, it's not to say there isn't actually a good opportunity in the whole next-generation thing – where you're using the technology. That’s kind of a different thing. But if you're just going after something that happens to use AI, then yeah, maybe it's non-consensus not to frame it with AI at all – not even to have the slide. But you've got to be able to pull it off.

So you said you have a wishlist – I want to hear about it.

Yeah. Okay. So I do have five – and then I have a fun one.

A fun one that’s kind of not in tech, and really not venture fundable, but I think it’s a massive market gap.

Okay, the first one touches on what we just said. I’ve completely bought the Slow Ventures Kool-Aid on AI-native versions of normal companies.

There was a lot of chatter about this last summer on the West Coast – like, is this the time to start conventional businesses from scratch, but in an AI-native way?

We’ve seen a couple of examples in the financial services ecosystem – some here in London, some in New York – and I do think there’s something to that.

In the face of insourcing, where people are developing their own software, and with software development in general being cheaper and faster to outsource, maybe the place to capture value is not in selling software to the people doing the thing, but in doing the thing better and faster because you’re using AI.

Can you give an example that you think is successful – or at least one you're excited about?

There's a company in the UK right now called Meshed, and they are trying to be the best insurance broker in the world.

One of the founders had previously started an insurance brokerage – which is great experience to apply here – and another was working at a company developing software in the insurance space.

I had a conversation with them, and they really evangelized this idea to me. I think I was already on the edge of buying into it, and then I totally did.

There’s a lot of interesting stuff to be done – without giving away too much of their secret sauce – but brokers have a lot of leads coming in. Being able to convert leads quickly, move on to the next one, and take the commission – there’s a lot of interesting opportunity there.

It’s all done by email as well, so there’s a lot of interesting software you could build and use – or build and sell – because there’s someone doing the selling too. There are both players in the space right now.

There’s a lot of advantage that can be driven directly to the top line – not just cost reduction – by being able to quickly respond to emails, scan large PDFs, respond with quotes, and generate relevant text.

So yeah, very interesting in the insurance space – that type of thing. Slow Ventures will also tell you that you should do it with parking lots.

They call it a Growth Buyout?

I think that’s where you write software and you buy the customer. And actually, this is a bit of the thesis I think applied when people were doing the Amazon e-commerce roll-up companies.

It was almost like – you couldn’t sell software to e-commerce vendors because they were too small, too disparate, or too hard to sell into. So, just buy them and force them to use the software by owning them.

That’s kind of the same. Really, it’s the philosophy of rollups in general. But I think maybe the power of software has reached such a point that there’s a tipping point where it becomes the natural thing to do.

I think a lot of rollups traditionally use cost savings, but mainly were about multiple expansion by scale. The difference now from what Slow and others are arguing is that not only are you increasing margins, but as you said, you can grow faster if you identify ways to serve customers better.

And it’s also not just the traditional approach of borrowing money and relying on financial leverage to make equity returns – if it all works out.

Yeah.

So what’s next on the list?

Thinking a lot about – this is very buzzword-y – but agentic e-commerce.

If I break this down, it’s like: I want to be able to buy something through ChatGPT, but I kind of don’t want OpenAI to become Amazon.

There needs to be infrastructure that allows purchases within LLM interactions once they can access the internet.

So you kind of want it to be yours. You’re saying, like, it’s your agent that goes shopping for you, right?

Well, there are two sides to it. You can have your agent go shopping for you, but I actually think OpenAI and the labs are probably going to provide the best personal agents.

I think a lot of the issue is actually on the vendor side. We've been looking at companies in this space, so some of this is straight from their playbook.

If you're an e-commerce store online, you need to have your website optimized for not rejecting crawler bots, and you also need to make sure your MCP is built – or whatever your interface is – for AIs to access up-to-date stock information and pricing.

This is a much harder problem than you might think. There are whole companies, like Farfetch, that have been built around aggregating stock information and sitting on top of e-commerce providers.

It's more than just a new generation of Shopify that makes you AI-compatible. Aggregating all this data – and if you're the infrastructure provider – puts you in a really interesting place. You can start doing rankings, and you become a semi-publisher.

If I go out and say, “I'm looking for blue shoes,” and the AI hits the platform that has everything aggregated, it says, “This guy wants blue shoes, what have you got?” That first set of results becomes almost like Google’s splash page. You’re in a powerful position.

I've been waiting for someone to rebundle e-commerce. First, there was the bundle – Amazon. Then came unbundling with Shopify. Who’s going to bring it all back together again?

I think you need a platform shift for that to happen. It’s probably going to come from some kind of infrastructure provider in the agentic e-commerce space. But it’s really, really hard, because it’s a lot of data to handle and get right.

The thing I’ve been looking for is someone to aggregate local inventory. If I want to buy something locally, how do I know what’s there without having to call around or go there physically?

One of my main hobbies is cocktails, and I have a hit list in my head. If I’m looking for a specific spirit, I’ll think: is it at my local corner store? No, because they’ve only got really basic stuff.

Okay, then is it at this independent provider? I’ll check there. If it’s not, I’ll go to the slightly larger specialist. And if they don’t have it, then I’ll buy online.

I’ve got this process, and you’re right – it would be nice to know. The corner store is probably never going to convert to that kind of system, but the slightly more advanced shops, the ones already using something like WooCommerce to manage their inventory – it would be nice to know what they have.

I thought that would be coming as more physical retail adopts Shopify. They’re making inroads there, so that might expose some of that inventory. So that's two, right? What's next?

So three: I’ve been looking for someone to do what I call an end run on housing.

In the US – you have buyer’s agents who represent you while you’re trying to purchase a home.

In the UK, you’re on your own. Only the wealthy have buyer’s agents. You're interfacing with the seller’s agent – called the estate agent, rather than real estate agent.

You’re dealing with the seller’s estate agent, going through a mortgage broker, who then connects you to a mortgage provider. Conveyancing lawyers are separate. There are all these different providers.

It’s clearly very hard to do, but I want to see somebody have the guts to say:

“We're going to do all of it. We’ll be your buyer’s agent. We’ll interact with the estate agent for you. We’ll find the right home, facilitate viewings, optimize the price negotiation. We’ll connect you with mortgage providers – or maybe we are the mortgage provider. We’ll know the lawyers – or be the lawyers – for conveyancing. And maybe we’ll own a logistics company for moving you in. We’ll automate your utility transfers to the new address.”

The only thing they probably won’t be able to do is change your address on all your subscriptions and cards – but now that I think about it, I’ve got an idea for that too.

It would be great if more of these services were the same company so I’m not getting referred from one to another, with each taking a slice of the pie.

It could be cheaper, smoother, and I wouldn’t have to deal with strangers over email that I have to implicitly trust to handle critical parts of the process.

I'm curious about that. I would think it’s easier to trust someone to be the mortgage broker than to say, “You're my buyer’s agent, and you're also going to be my lender.” I could see wanting to keep the lender separate.

You want to keep the lenders separate, so you're getting bids from multiple lenders?

Yeah, you’d want to see that.

I remember when I went through a mortgage broker, he said, “There’s only one, and it’s these guys.” You never know when mortgage brokers are or aren’t getting a kickback from the provider.

I thought that’s how they made money.

Well, the only alternative is captive agents who only have one provider to talk about anyway. So, yeah, that’s difficult.

I’m still annoyed that there are separate providers who do the survey of the house. That’s a whole other thing. The lawyer says, “Here’s the survey provider.” Why doesn’t the law firm have a surveyor? It’s insane.

More verticalization inside real estate. There are people who try this now and again, but there needs to be someone who’s a very seasoned entrepreneur – someone who can walk into the top firms and pull together £30 million just because of who they are and say, “Here’s what I’m going to do.”

Because I think it requires substantial capital to fund and start five companies at the same time and pull them all together in one go. Obviously, you can start in one place and build out from there – but they never do. They always get comfortable in their niche.

Is this from personal experience?

A little bit. But also from one of our portfolio companies that touches on e-commerce. They bought their fulfillment warehouse, and it added some percentage to their gross margin.

And I was like – you can just do that? You can just verticalize like that and get a better margin? It really set me thinking: what has a massively fragmented supply chain that could be verticalized?

What I landed on – from personal experience buying a house – was: wow, I’ve spoken to seven or eight different entities just to buy this house. Surely that’s one or two too many. Maybe I should only have to deal with one or two at all.

All right. So now we're up to number four.

Four. And I think this is an area where I can speak with some amount of certainty. Out of our fund, we really want to do a fully automated personal finance company this fund cycle, because we think the technology is there to do it.

We've spoken to a couple of firms in the space – really applying an AI brain to optimizing personal finances, to just do the right and smart thing for you.

And this is across the board? So it's not just cash flow – you’re talking about investing as well? What scope are you thinking?

Yeah, so there are certainly things you can do to make transactional products – like credit cards, debit cards, and maybe savings accounts – work properly for you. I think that’s a whole space to conquer on its own.

We know from talking to startups working in this area that a lot of people just get that wrong straight up.

And then there’s the broader personal finance world – actually, this touches on the next one – but there’s this whole open finance space, which includes every other financial product. That’s really hard and gnarly because they’re all so different. You've got contracts, different providers, and a lot of complexity to plug into.

Still, I think there’s a baseline of automated management that can be done. People have been trying to do this for a while – things like sweeping accounts, moving money into the right places, salary splitters.

We were invested in a company called Qapital that had a salary splitter product. We think the time is right for that kind of aggressive hands-off automation in this space.

The hard part is incentive alignment. You could sell this software into banks and have them automate everything, but if you sell the same software into another bank, the two might not cooperate. Banks don’t necessarily want to authorize capital outflows to another bank just because the software they’re paying for told them to – especially if they like keeping those deposits for yield.

So maybe it has to be B2C – which is very untrendy at the moment. Then you have to deal with marketing, outbound sales, and all of that.

And if it is B2C, then you run into the issue we talked about with mortgage brokers: how do you ensure the autonomous engine isn’t making biased decisions – like putting your money into a suboptimal savings account because of a hidden kickback?

That’s the issue to solve. But if there’s a way to do that, I think you can unlock this space without having to obsess over incentives.

Or maybe consumers just absorb the misalignment, because they’re already non-optimal. Like, maybe it’s not that bad to be 0.1% off on your savings yield if the system is doing everything else right. Maybe that’s a Pareto-optimal outcome – you eat the misalignment just to get to “good” and miss “perfect.”

You mentioned Betterment earlier – it was an earlier fund investment. That seems like it’s roughly in this neighborhood.

Yeah, it’s getting there. Definitely.

So what do you think you can learn from that case as you think about the next generation?

I think it’s about starting points. Wealth management companies – there’s a reason we haven’t done too many AUM businesses at Anthemis.

Our experience from Betterment is that they’re difficult to pull off because AUM revenues are tough – they’re backloaded.

If the AUM of a consumer increases over time, then you're making most of your revenue at the end of the customer’s lifetime value rather than the beginning. So the payback periods are super long.

That’s why I mentioned transactional products like cards. Wealth is tough because, first, not everyone uses wealth management services.

Yeah, I’m sure you do. I actually don’t at the moment – but I would if I were more on top of things.

Whereas credit and debit cards are relatively universal. Some people work entirely in the cash economy, and that’s a whole separate set of products.

But entry points matter. If you're going to build a vertically integrated personal finance company where you control everything, where you start is really important.

You can get stuck in a niche, or it can be hard to scale your customer count from a particular starting point. Some businesses are also just harder to operate than others.

That said, I’m not that close to the Betterment case, since it was done long before I joined Anthemis.

Fair enough. So you have two more.

Yes. Well, I have one more serious one, and then you can have my fun one.

I actually don’t believe in open finance. This is something I’ll be posting a longer-form blog about.

There was this whole wave of open banking, which meant API access to banks. First it was just read access, then write access – like initiating transactions. Now, at least in Europe, people are trying to do QR code-based bank-to-bank transactions in real life, similar to what Line Pay and WeChat Pay do.

That seems to be semi-functional via the EU’s Payment Services Directive 2, which mandated that banks provide API access to certain functions in their transactional accounts.

Now they're coming out with Payment Services Directive 3 – ten years after PSD2 was first initiated – because there were problems. Banks were being facetious and not providing the full functionality they were supposed to in those open APIs.

So it's already been a 10+ year battle to get open banking off the ground and get everyone bought in.

When people come along – well-meaning fintech speakers or consultants – and say, “The next thing is open finance and everything’s going to be open,” it’s like...

First of all, open banking has been incredibly difficult to build. Now imagine extending that to wealth managers, insurers, lenders – every other part of finance. Private placement agents, capital markets – you name it.

To expose all of that, and to mandate open functionality for each of those buckets, means multiplying the difficulty of open banking across all of them. So conservatively, it's five times harder than something that has already taken 10 to 15 years to even partly accomplish.

Now, I’m going somewhere with this.

Along comes agentic technology – web crawling, browser automation, and current AI use cases.

Suddenly, if I can automate a browser, I can theoretically navigate through the existing websites of banks and other financial institutions.

You don’t need them to put up an API – as long as they have a website.

You can hit the private APIs via their web UI. Of course, you need the right consents and passwords. But if you can handle password management at the LLM management layer, that becomes very interesting.

Then you’ve got people permissionlessly doing the open finance thing. What banks are going to have to get their heads around – and this is the same with the agentic e-commerce stuff – is that it's going to be very hard to resist this.

Either other people are going to get the business if you don’t buy into it and make it more frictionless, or you do buy into it and make it easier for these types of agents to interact with you.

What I’m interested in is – either via MCP or A2A – agent-to-bank front ends for banking services. So when these pseudo-open finance interactions happen, you can actually allow for the opening of accounts and other actions via an agent, rather than things breaking or defaulting to just a static product overview that requires the user to go to the website themselves.

There are various levels of autonomy here.

Level one is: when an agent hits your website, do you instantly flip – based on browser headers – into a more technical version that strips out images and difficult UI? A version that an AI can simply read and parse?

Because you can give a huge list – maybe not a thousand pages, but close – to an AI, and it can ingest it. For a human, scrolling forever through every product and option is difficult.

Level two is: you have proper structured services that AIs can hit via new protocols – MCP, A2A, or whatever else comes along – and actually build around that.

So, stuff in the agent-to-bank open finance space, outside of just transactional banking, would be super interesting.

It’s probably a very difficult enterprise sell, but I think there are inroads here.

And the benefit to the financial institution for buying this software is, that over time it’ll be demanded by current customers and potential ones.

It’s going to be happening anyway. If your competition does it, they’re more likely to be discovered by the AI, and those customers are more likely to convert via the AI.

The theory is that it’s the next interface. If you didn’t have a website, or didn’t have a mobile experience, now if you don’t have an agent experience, you’re going to miss out on customers.

Yeah. They just won’t be surfaced through the channel people are looking in. Or they will – but the experience will suck.

I can’t wait to hear what this fun one is.

I've been picking up on this a lot – there’s no fast casual Indian place. No private equity-backed, reliable, office-worker-slop food that’s Indian-themed in the UK.

You’ve got Coco di Mama, which is Italian – you go in, there's a screen, you tap your name in, someone calls “Alexander,” and you grab your pasta and go.

You've got Itsu, which is Pan Asian – Japanese. Leon, another good chain. These are all reliable lunch spots in the UK.

You’d think, with our cultural heritage and with who lives in London, there’d be a unified Indian brand where I can get a reliable chicken tikka masala for £8.50, ordered off a touchscreen, from a recognizable, private equity-backed brand – optimized specifically for office workers to get their food at lunchtime.

How does that not exist? I agree with you.

I'm completely out of my mind that this doesn’t exist. And it’s fine – I can go to independent Indian places – but usually they’re optimized for you to sit down.

This is a problem I have with a lot of so-called street food restaurants: they’re optimized for dine-in, but you're supposed to be street food. “Street food restaurant” is an oxymoron.

Or you’ve got to discover them – there’s a discoverability problem.

Whereas I can be anywhere, walk into Leon, and I know exactly what the food’s going to be like. It’s about having the overarching brand. There is no overarching Indian fast-casual brand in the UK.

I would have thought – because it’s London – it would exist. But it doesn’t, and it drives me crazy. So somebody, please, start the fast casual Indian.

Because everyone loves their local place that they already found, or –

No, no. Nobody goes to the local Indian place for an office lunch. There needs to be a unified office lunch option.

The traditional Indian place is optimized for evening service and delivery – not for square, folded bags and self-service checkouts.

Youssef’s venture wishlist

🏛️ Next-Gen GovTech Customer Service: Let citizens “call the government once” and resolve issues immediately while remembering everything about them and their needs. Bonus points if you chart a vision for the future of the government’s operating system.

⚒️ Good Jobs for the American Worker: Full-service marketplaces with advantages on either time-to-train or cost-to-train across sourcing, training, evaluation, and placement for the physical “Atoms” economy where human skill, intuition, and service will remain valuable (health, construction, climate, care, education, manufacturing).

📈 Enterprise-Grade Tools for SMBs: AI-driven marketing, CFO, training, and tax platforms for small business once reserved for the Fortune 500. AI unlocks expert talent small companies could never pay for or attract.

💊 Modernizing Government Benefits: Real-time eligibility, care-coordination, and home-based support in Medicaid—especially for high-need, low-income, and high-cost populations.

👵 Aging & At-Home Care Infrastructure: Operating systems, tooling, financial infrastructure, and copilots for informal caregivers plus reliable home-health and skilled-nursing for an aging population.

🤖 AI for the Frontline: Turn smartphones into on-site experts for frontline teams in energy, healthcare, construction, waste management, and retail. Stand out by showing uses beyond surveillance and closer to worker superpowers and a more dignified, safer worker experience.

Other insights

🏗️ Domain Expertise > Pure Code: As software creation is democratized, deep workflow knowledge becomes the durable moat.

🚀 Founder Traits: Healthy obsession, relentless velocity, true customer empathy, and hands-on industry experience matter most—especially in regulated or relationship-based markets.

🕰️ Patience Pays in Regulated Sectors: Higher compliance and capital hurdles slow go-to-market but create defensibility when solved. It helps to have worked for your customer.

🌟 Inspiring, Human-Centric AI: The future lies in tools that augment labor—eliminating the dangerous, dirty, and dull tasks—rather than replacing workers.

📚 Capturing Tribal Knowledge: There’s white space to preserve retiring experts’ know-how, turning PDFs, spreadsheets, and lived experience into searchable, trainable data sets for the next generation of field AI.

Full Interview

So usually we just start with your description of the fund and your strategy—whenever you want to share, kind of overview-wise.

I'm an investor with AlleyCorp. We're one of New York's oldest and probably most active early stage funds. The strategy is to be early and to bet on New York across sectors and categories. We also have incubation in our ethos. Our founder, Kevin Ryan, was the godfather of New York City tech back when the city was the center of everything else—finance, law, retail, media—but not tech. He founded a string of awesome New York City-based companies from MongoDB to Business Insider, Zola, Gilt, et cetera.

That’s really the fund thesis. We're investing out of our latest vehicle, a $250 million fund from pre-seed to Series A. A little more than half of our founders are based in New York City and half are elsewhere.

I joined a couple of years back to help build out our Economic Infrastructure vertical with my colleague Tanya Beja, who leads our team. The thesis there is simple: we saw an opportunity to invest in non-obvious, generally regulated and under-digitized sectors where, if you have an intervention that works, the impact upside is tremendous—for families, individuals, and institutions—and there's a lot of financial return.

In practice, it means we back founders who change the way people learn, both in K-12 and beyond; the way they earn—accessing earnings opportunities, growing careers, navigating changes in labor; and the way people access care, both care for underserved populations and broadly things like childcare and benefits, particularly government benefits.

In practice, it has looked like creating entirely new categories - upskilling / access to career advancement education (Stepful), pharmacy infrastructure in low-income communities (Alchemy), changing the landscape of government RFPs and vendor selection (ToughLeaf), or building tooling for SMBs where solving that pain point is useful for them and their labor pool (Upwage).

What is different about investing in regulated industries?

A couple of things. One, you need to have more patience because the friction when going to market is just higher. You have many more compliance requirements, in some cases capital requirements for the startup to demonstrate that, hey, if I'm going to work with the government or a bank, I need to be around for more than a couple of years. Often—and this is actually the case in education, government, and healthcare—there's a real emphasis on impact and outcomes for the end user. Increasingly, AI for labor is one of those categories where companies also want you to demonstrate that there's no disparate impact on their labor pool. So you should demonstrate that you've trained on really strong, comprehensive data.

Are there any concepts or mental models that you rely on the most when you're doing this investing?

There are four characteristics I over-index on when investing in founders, and then I’ll give you an example that came to mind from one of our startups.

The first is we really like to see someone who has a healthy obsession or compulsion—ideally it's aligned with their startup, but not necessarily.

The second is data points from that person's life that show they have energy, velocity, and can execute at really high speed. So there's purpose, but also the ability to move quickly, fail quickly, succeed quickly, and learn.

The third is that they have very clear, deep empathy for their customer—ideally because they've been the customer. It's different from sympathy, which is like, "I have an idea of your pain, I’ve run a survey." Empathy is really knowing it because you've experienced it.

Then on experience—experience matters. If you're in a regulated industry, a high-friction industry, or a relationship-based industry, it helps to have serious experience. Ideally, you’ve been in a leadership role within an incumbent institution or a high-growth startup that served that institution.

So those are the four things we look for.

On the obsession piece—Carl Madi, who's the CEO of Stepful, was a colleague of mine at Uber. He runs a company that's dramatically changing how people access healthcare careers. It’s a digital, asynchronous, AI-enabled school for physician assistants, medical assistants, phlebotomists, and higher-level technician roles in healthcare.

He said he first started working on it during Covid. He would do his day job from 7 or 8am till 7 or 8pm, and then work on Stepful from 8pm till 1am. He did that for months. His obsession was figuring out how to stem the tide in healthcare careers at a time when hospitals couldn’t hire enough people, and patients were going without care because there weren’t enough nurses. New York was importing nurses from other parts of the country at 2-3X premium. He just had that obsession and worked on it nonstop until, according to him, he found it unbearable to do anything else but Stepful.

What was surprising about what you just said is you said the obsession doesn't have to be aligned with the startup. Is that what I understood?

Yeah.

So what would that be? What's an example of that?

A good example would be someone who is obsessive about a topic area that demonstrates increasing levels of intrigue, excitement, and ability to go deeper. In some sense, it can be corny. You could be obsessive about a sports team and analytics for sports, and talk about how you've built out a spreadsheet over the years of characteristics for the type of basketball player you should have on your fantasy basketball team, and the things you've honed in on as a basketball fan. I share that because I'm an obsessive basketball fan. The ability to not just be at this high level and say, "I like basketball, that's a cool thing, I watch it," but to demonstrate depth, intrigue, and a desire to build something to improve your understanding of the game and your depth and experience—I think that's exciting. Do I plan on building a basketball startup? No. But I think we look for that obsession in people. Ideally, it's a healthy compulsion or obsession. In Carl's case, of course, he was obsessed with serving the very people that are deeply connected to his startup. So, not a bad bet for us.

You've shared your obsessions and I’m wondering if you have any non-consensus beliefs that drive your investing so far.

Yeah, I think there are two. I mentioned experience before. I want to back people who've been in an industry for a bit. One is actually around— a lot of folks are deeply interested right now in finding the highest level, highest capacity technical expertise for people building in AI or near AI. I think that's important if you're building, call it, a foundation model. But my perspective is that as software development becomes fairly democratized, the emphasis on founders will shift to domain expertise more and more. Anybody can whip up a great app or tool, but can you build something that has deep knowledge embedded in it about the workflow of the person who's supposed to use it? The small accounting shop you're supposed to help with their day-to-day or customer acquisition. Or the community health clinic that really struggles to schedule people and follow up with seniors. That's where I think value will accrue—not just with someone who's highly technically competent. You're going to need both working together.

The second, and this is just a personal kind of desire of mine—I want to invest in AI that's inspiring. I think we've talked about this one-on-one. The people building AI tooling are just as important as the thing they're building. I want to work with people who are looking to supercharge others' work using AI and who see an opportunity to have AI and labor work together versus apart. I don't buy a future where software solves everything and takes over people's jobs. I want to invest in a future where people's jobs—especially the most dangerous, dirty, challenging, monotonous parts—are made easier or eliminated entirely, so they can do stuff that's fun and exciting. That's the type of inspiring AI I'm looking to back.

You're saying that programmers won't have jobs?

I wasn't saying that.

I thought you were saying that if you know the customers with AI, you can write the product without product expertise.

Production-level code is different than a super basic demo or app. But it is true that, as a founder or small business person, you can do way more with less, especially around building software. Jevons Paradox is an interesting one. You bring down the cost and the ability to do things, and then there's just way more demand for software.

Yeah. I think the best essay I've seen on that recently was Tim O'Reilly's—about how you make software more accessible and cheap to build, and then everyone will do it. I think it still requires clarity of thought.

Yes.

Even if AI handles all the race conditions and scaling—maybe eventually even highly secure, highly scalable production code—you still have to think clearly about what you want. A lot of people know an industry and their users, but don't practice that kind of clarity about what they actually want the software to do.

Yes.

And AI could fill in something. It'll do something, but it may not be exactly what you want if you haven't thought clearly about it. That's my sense of it. But maybe that's because I still value my computer science education, which may be obsolete at some point.

So let's get into the ideas. Are there any specific ideas you're excited about right now?

Or things you'd like to find or fund?

Yeah, I think there are themes that are top of mind for me and that touch on this learning, earning, care angle, but also my background. If the last three years have been about building AI tooling for office workers, I think the next two, three, four years are for bringing AI to the field—anyone who's not at a desk and working in a taxing, laborious, high-stress frontline job. So it's for low- or moderate-income people in energy, construction, waste management, retail, health. How do we give these powerful tools to them in a way that dramatically improves what's arguably a more stressful and more challenging way to do your job, which is out in the field versus behind a computer screen?

The second is around government effectiveness, specifically state and local government, which spends something like $140 billion a year on tech alone—not including people, paper, or all of these non-automated processes. There’s an idea I’ve toyed around with: government’s not known for its customer service, but what’s next-generation customer service for government? Does picking up the phone and calling the government become the primary mode of interaction with services in a way that's easy, seamless, remembers who you are, understands your family situation, and can pull up the paperwork you've submitted before?

There’s a whole host of other things: procurement, asset management, especially where regulatory permitting limits innovation. When I was at New York State, we had a process for allowing telecommunications companies to rent space on light poles and physical infrastructure we owned. It was a very slow process. The ability to bring broadband to people and scale it was limited because we had a very manual process for knowing where the asset was, what they wanted to do with it, and how we could quickly allow and charge for it. So that’s government effectiveness.

The third is around Medicaid and modernizing Medicaid. 35% of Medicaid members are disabled. A very high proportion of Medicaid spend is specifically on long-term care. How do we focus on high-need, high-cost populations more effectively—especially people aging at home rather than in a hospital? Can we build technical rails for eligibility verification? A good example: upwards of 40 states have eligibility systems that are over a decade old for Medicaid redeterminations. If we live in a world where there’s less money for Medicaid, we need to put those dollars to greater use—less on admin and overhead, more on serving people.

The fourth theme, and this gets at the democratization of software, is that a lot of enterprise tools that were once only available to big companies can now be made available to small companies. These tools are connected to processes that SMBs needed much more money and people to do but couldn’t access—like marketing and sales support, CFO office and financial management, employee training and onboarding, tax. If I'm a small business, I can’t hire a design person or a marketing person. That’s exciting because small businesses are by far the largest driver of employment growth over the last two decades, and my hunch is they’ll remain so.

The fifth one, which I touched on with Medicaid but has broader implications, is the aging population. What do we do, especially for the part-time and unofficial caregivers in their lives—the child, the niece or nephew, the partner managing their care? It's about bringing a much higher quality, more reliable supply of home health and skilled nursing support to that population. It’s managing their eligibility, especially if they're dual eligible for Medicaid and Medicare. It's like a companion operating system for people in my generation and the one ahead, juggling responsibilities of care for both parents and children, and in some cases, other loved ones.

I think founders building in those spaces are going to be pretty well served because they feel like fairly resilient, lasting categories.

That's a lot there. I'd love to talk more about AI in the field because I have a sense that many workers have experienced computers as tracking them and telling them what to do. I think of gig workers—like, okay, got my assignment, go do the next thing. And you're talking about a situation where field workers are telling the computer what to do. That seems like a big change.

Am I thinking about that the right way?

Yeah, I think the best way to think about it is ChatGPT has made my life as an investor, and someone who is doing a whole lot of diligence on a bunch of different sectors at any one time, way easier and simpler. It’s allowed me to read more, think more, and converse with another party—even if nobody's in the office at the time—and trade ideas. Extending the capacity of people in really challenging jobs in the field is an area I think is amazing.

So I'll talk about the most recent investment we made. It's a company in stealth, but it gives an idea of what this might look like for the $150B home care industry. It’s an AI operating system to modernize home care agencies, who dispatch caregivers and home health aid to someone’s home to care for them, if they’re elderly, recovering from a severe injury, or live with a disability. The range of services varies, from doing physical or swallow therapy, bathing and moving people, or checking that they’ve taken medications and eaten. Today’s process is broken and painful for discharge facilities, families, and staff: whether an agency is scheduling a home health aide for the first time or a cancellation occurs last-minute, a 24/7 on-call scheduler sifts through lengthy PDFs and spreadsheets to find names and phone numbers for aides who might be available to take the shift (one-by-one, she texts and calls them to see who might be free). The process is both stressful, slow, and inefficient, adding immense stress to the scheduler’s life and resulting in some painful delays for families: when interviewing one aide who cares for children with disabilities, I learned that some families resort to calling an ambulance for an overnight facility stay when their caregiver cancels. AI dramatically improves this process, giving back the scheduler her off-hours, while intaking new requests for caregiver matches seamlessly and bidding out cancelled shifts quickly and effectively based on someone’s zip code, availability, training, and the family’s preferences.

Another example, one I found really exciting, was in climate, where many good-paying jobs are being created for working class Americans. Oftentimes, someone working on a well or a construction site installing solar panels, when something breaks, has to call someone in an office and ask, “What do we do? Can you send over the documentation? Can you talk me through it?” The information lives in PDFs, old SOP documents and diagrams, and email attachments. This results in delays, safety issues, and for small contractors, missed deadlines.

So is there a way to put the guy in the office in your pocket? Can you take a photo of the site and ask, “Has this been built correctly? Why is this down? What does our SOP or safety manual say?”—without delaying progress? That’s exactly what you mentioned earlier. Rather than people taking orders from a robot, they’re giving the orders to the AI in a way that helps them.

Yeah, I think getting the data is really key because it's not like you can just crawl the web and suddenly know how to repair this piece of energy infrastructure.

The domain expertise is useful here. I talked to a founder a few months ago who's building in this space. They had been at a leading climate and sustainability company for probably a decade and a half, then worked at an AI company building tooling in-house, and now they're building their own company. They knew with immense precision how these contractors and companies operated. They also recognized that most of the insight lives in PDFs, Excel spreadsheets, and emails. Training on that company’s internal data was really key. It wasn’t something you could just Wikipedia. Getting back to the prior mental model, I think depth in an industry and experience is going to be really important now.

I’ve heard of a company doing the procedure manual approach for law enforcement. There’s law, there are policy procedures—cops are supposed to go back to their car and flip through a big manual and be like, “The suspect's inside, can I break this door down? What’s the legal test?” That’s one type of problem where it's all written down, so you can imagine an LLM going through it and knowing that body of knowledge. That’s useful.

What I was talking about in terms of the data is some of this field work, I imagine, is sort of written down, but not really. Like, how do I do maintenance on this device? How do I repair this thing? How do I build this thing? What if someone made a mistake in construction—how do I debug? Some of it's written down, but I think a lot of it’s not.

So that's a big challenge in building these types of companies.

Totally. And that leaves room for data capture and data infrastructure. There are a few companies I’ve talked to who are solving the tribal knowledge problem in these sorts of industries. Their whole job is to ask, how do I make sure that—especially if your workforce, like in the case of CPAs, where something like 75% are retiring over the next five to ten years—but if we're talking about field work, it could be construction, it could be logistics—how do I make sure that when that man or woman retires in the next five years, we don’t lose all their tribal knowledge? Can I shadow them, interview them, digitize the content they’re writing down in a way that extends their capabilities for the desk worker?

We’re getting more and more used to being recorded all the time in our Zoom calls. For field workers, I think there’s still resistance to being tracked, although it does happen—GPS tracking, for example. But is someone going to wear AR goggles to record all this tribal knowledge? I don’t know. Cops have had to wear something now in many jurisdictions. They turn it off when they can. It's an interesting question.

I think that’s where the incentives really matter.

So if I felt like, Miles, you were going to penalize me by having your Grain note taker on this call, I would have said, hey, no, no Grain note taker. Sorry, I don't want that. But if I think it's going to be valuable for your ability to recall the conversation and actually go back and forth with me in a dialogue, that's awesome. I might ask you for the transcript so I can go back and critique myself on it. The incentives are super important in these industries.

The other thing I’ll say is there are industries that are so supply and labor constrained that the last thing employers should be doing is upsetting their labor force and coming across as overly invasive or punitive. Instead, they should be thinking, how do I make you stick around longer? How do I make this a long-term career for you?

Whether it’s the skilled trades or the care economy, employers are well served not to alienate their labor force here.

Tahira’s venture wishlist

🌐 Tech-enabled access to government benefits – Platforms that help people discover, verify eligibility for, and seamlessly claim public benefits.

☂️ Next-gen insurance & claims automation – Software underwrites new or rising risks (e.g., climate-driven blackouts for restaurants, gap-coverage for high deductibles) and use AI-first claims processing to slash payout times.

🏭 Embedded fintech for SMBs – Vertical SaaS marketplaces that digitize opaque, offline processes (like food contract manufacturing) and embed working-capital or purchase-order financing at the point of transaction.

🌾 Financial tools for overlooked segments – Products designed for rural households, gig workers and 1099 earners that lack employer-provided benefits (e.g. portable retirement solutions, income smoothing and affordable credit).

👵 Retirement resilience – Modern, low-fee, portable alternatives to 401(k)s that convert savings into guaranteed lifetime income and protect older Americans from fraud and volatility.

Other insights

💡 Problem-first, tech-second – Focus on founders with deep understanding of customer pain.

💰 Profit and impact can coexist – It is possible to build highly profitable businesses that serve low- and moderate-income consumers ethically; tech bends the cost curve to make smaller ticket sizes viable.

🏗️ Embedded distribution is a moat – Partner channels (employers, vertical SaaS, merchant platforms) offer low-CAC access, proprietary data for better underwriting, delivery at the exact moment of need, and borrowed trust with hard-to-reach users.

🧑‍🤝‍🧑 Founder > model – At seed, ResilienceVC underwrites the founder’s ability to navigate pivots and regulatory shifts over a 5- to 10-year journey—the average VC-founder relationship now outlasts the average U.S. marriage.

📈 Crowded top, vast middle – While many startups chase affluent urban customers (and battle soaring CAC), the real white-space lies in huge, underserved markets (e.g.lower middle income consumers, rural businesses and aging Americans).

Full Interview

An easy place to start is an overview of your fund and your strategy.

Resilience VC is a seed-stage fund. We focus on early-stage startups in the fintech space, specifically startups leveraging fintech to build financial resilience for American consumers and small businesses. When we think about the financial state of most American consumers and small businesses, it's pretty dire. Seventy percent of Americans are not financially healthy. They aren't able to manage their day-to-day finances, weather inevitable shocks and risks, or save for the future. We focus on models that build financial resilience—helping people increase earnings, reduce expenses, mitigate risks, and build assets. In doing so, we can create a population that is more financially stable, secure, and resilient. That's the focus of the fund.

And when do you get involved in companies? What's the typical check size?

We invest at the seed stage, and these terms mean different things to different people. For us, seed means the company has a product live in market and some early customer and revenue traction. We don't invest pre-product or pre-revenue. We want to see some proof of concept—evidence that customers are willing and able to pay for the product and data on initial customer usage. We come in with an equity check, typically in the million-dollar range, and work with these companies. We often take a board seat and work closely with founders below the board level on operations to help them reach product-market fit and develop a scalable, repeatable model. With future rounds of capital, they can then accelerate growth and impact.

When you're thinking about investing in a company, what are the mental models or concept patterns you find yourself relying on?

I don't know that I necessarily have a go-to mental model per se, but there are a few things that are central to the way I approach investing. One is that I really want a product and a business built around a deep understanding of the customer and the customer's needs. So often, especially in the tech world, you see products that are a technology solution looking for a problem—especially with new technologies. GenAI today, crypto and blockchain a few years ago—you see people saying, "We want to leverage this technology for the sake of the technology," not, "We want to leverage this technology because it's the single best way to solve this customer pain." And I think the latter is what's really critical.

Any business model that’s going to be successful has to be built on a true understanding of customer needs and really be solving a pain point. People are not typically willing to pay for something that isn't a real issue. It has to be solving a need that’s not being met today, or, if it is being met, it has to be significantly better than the status quo. Because there are always switching costs—people tend to stay where they are unless they have a real reason to move. So I think that’s really critical.

I also think—and this is part of the rationale for the fund strategy itself—we have to focus on large markets. We see a lot of companies continuing to fight for the top of the market, for middle- and high-income consumers, and it's incredibly competitive and crowded there. Customer acquisition costs are skyrocketing in those segments. Meanwhile, the majority of the population isn’t being effectively served. For the companies that figure out how to build relevant, quality, affordable products for those segments, they’ll be first movers in a massive market, with huge room for growth and returns.

So, with a deep understanding of customer needs and a focus on large market opportunities, I really see the low- and moderate-income segment, and the small business segment in the U.S., as large, deeply underserved markets.

The third thing I’ll mention in terms of my approach to investing is a real focus on the founder. We come in early. We know the business model will evolve, the revenue model will likely evolve. We're taking a bet on a founder or founding team to navigate that evolution, go through pivots, and respond to a changing and volatile market, new regulation—all of that. So it's about finding a founder I want to work with for the next five to ten years. The average founder-funder relationship in the U.S. lasts longer than the average marriage today. These are long-term relationships, and we want to approach them as such.

So, for me, taking time to get to know a founder, understand their motivations, their experience, their trajectory, and what they want out of this is really critical.

So you mentioned customer pain, large market, and team. Those are certainly important. I would say that other investors probably share most of that. Do you have any non-consensus beliefs that you think inform your investing differently than others?

Yeah, and part of this is linked to the market opportunity I was talking about. But really, first and foremost, it's that businesses can make real profits while ethically and responsibly serving lower-income customers. Historically, lower-income customers have not been served because it wasn't particularly profitable. So they were either not served at all or served with really predatory and extractive models. I very much believe—and hopefully, this is becoming more of a consensus viewpoint—but I think there's still a lot of people who think that profits and serving underserved segments are mutually exclusive. There is huge opportunity to reach lower-income segments of the market. It looks different, and you have to design differently for them. They are going to have lower balances, smaller transaction sizes, their behaviors are going to be different. You may need to invest more in certain elements of the customer journey—into onboarding, into customer support—because they're new to these products. But it doesn't mean you can't profitably serve them. That's where I think technology plays a really important role. Technology can fundamentally transform the cost curve, make it profitable to serve these segments. We're really excited to meet the founders that see that opportunity.

I think I'm understanding you. You're saying that technology offers lower transaction costs, lower cost of service. Therefore, you can support a customer who may not have as much to spend or as many assets or transactions.

Exactly.

Any investments or examples you want to share that you've been excited about recently?

I'll go into a couple of examples, but before that, I want to make one more comment. Certainly, technology can make it cheaper and more profitable to serve these customers, but it's still hard. That’s one reason we at Resilience focus on embedded fintech. Going direct to consumer and paying a lot to acquire customers unfamiliar with your product or category is challenging. Embedding your offering in other products, services, channels, or value chains where those customers are already engaging or transacting creates huge advantages—from a distribution perspective, a data perspective, a delivery perspective, and a trust perspective.

On the distribution side, you often have access to a captive customer base that you can tap into at zero or very low incremental acquisition costs. On the data side, when you're embedded, you can often access data—often proprietary data—on those customers, which lets you better target products, better underwrite, and reduce risk. The delivery advantage means you can deliver those financial products seamlessly at the right moment in the user journey, which creates a better user experience and typically leads to higher usage, loyalty, and retention. Those factors drive profitability in significant ways.

Finally, there's the trust advantage. When it comes to serving people with financial tools, trust is critical. By working through embedded channels—through partners, whether employers or other core products and services these customers need—it can be easier to build trust. That’s another element that can make the mass market, particularly the lower end, profitable and serviceable in ways it historically may not have been.

Let me share a couple of examples from our portfolio that exemplify this—one on the consumer side and one on the small business side. On the small business side, one of the first investments we made from the fund was into a company called PartnerSlate. They focus on small businesses in the food and beverage space—small food and beverage manufacturers. About 30,000 new food products come to market each year in the U.S., and the majority are brought to market by small businesses. When these businesses start to grow—they might be producing at home or in a local commercial or test kitchen—they get their first grocery store contract and have to ramp up production significantly. They aren’t going to build a manufacturing line in their house; they typically find a contract manufacturer to meet the demand.

And historically, finding a contract manufacturer has taken a small food and beverage brand about twelve months. It's a pretty analog process. Most of these contract manufacturers don't have much of a digital presence, so they are cold calling or cold emailing hundreds of manufacturers to try and find who has the right capabilities and capacity to run a production line for them. Often in that time, they may lose a purchase order they had or just be stuck for months.

So PartnerSlate built a platform to help match small food and beverage brands with contract manufacturers. They can help those products get to market much faster as a result. Even once a small food brand finds their contract manufacturing partner, they still have a real challenge. They have to pay upfront for the ingredients and manufacturing, but typically don't get paid until 30 to 60 days after they deliver product to the grocery retailer.

So there's this two to three month working capital gap they face. PartnerSlate not only does the matching, but has embedded a working capital product into their platform to help address this need. They can offer purchase order financing at attractive terms to these small businesses, not only enabling them to better connect into the supply chain, but also providing that critical financing.

One of the founders has been deep in the contract manufacturing world for a long time. His wife worked at a small food brand that struggled to find contract manufacturers. He saw this pain point directly, went deep into that space, and built this business around a need he understood very well. They focus on serving this segment of businesses that struggle to scale otherwise and embedded a fintech product onto a platform that's not inherently a financial services platform, but can deliver that financing at the moment in the user journey when someone's found their contract manufacturer and is trying to figure out how to pay for ingredients and manufacturing upfront.

Rather than stopping the process and going elsewhere to find a third-party lender who doesn't understand their business, they can get a loan directly through the PartnerSlate platform—with someone who knows the business, knows they're ready to go into production, can match the credit disbursement with the timing of when that product is going into production, and carry much lower risk than a third-party lender would.

Very cool. Curious what themes you're most excited about when you look towards the future.

There's a lot that keeps me excited. I will say there are a number of areas where I see huge opportunity to solve a customer pain point or to innovate and create efficiencies in a market that isn't efficient today. As we talked about with PartnerSlate, the contract manufacturing world—finding a contract manufacturer is offline, inefficient. How do we digitize that? How do we bring efficiency to it? How do we layer in the financial product? I think that's the approach we take to a lot of spaces.

One we're looking at closely right now is government benefits. It's really challenging for most people to, one, find out about these benefits, two, understand whether they're eligible, and three, actually apply and get them. What are ways that technology can be leveraged to make that process more efficient at any or all of those stages: awareness, eligibility, and actual application?

I think that's a really interesting area. And you've seen nonprofits step into it. What do you think of the business models that make sense for that kind of startup?

Historically, it's been nonprofits, social workers, folks like that helping people connect to these benefits. But there's absolutely room for for-profit businesses in this space. Even in our portfolio, for example, Alice is a company that helps employees—hourly wage workers, typically—better access pre-tax benefits on a real-time and contribution-free basis. What they've done is found a party incentivized to help employees access these benefits: the employer.

If the employer knows their employee can get money back equivalent to an entire week of wages in a given year, that's meaningful. The employer is willing to pay a small amount to help their employees get access to those benefits. That's one example of a business model where the employer sees value. We see a lot of employers in industries with incredibly high turnover rates, where employees often miss work because they lack reliable transportation, affordable commuting options, or access to childcare that enables them to come to work.

The employer has a vested interest in solving these challenges because it means that employee will be more reliable. So they're willing to play a role in helping pay for those benefits. There's an opportunity to ask: who in the value chain has an interest and is willing to enable the end customer, who may not always be able to pay for this product themselves? The embedded approach allows us to say: who else in their value chain might be? In this case, the employer. That's one example of a for-profit business model there.

You see plenty of deals. Are there any startups you wish existed that you could invest in?

I would say there's a lot I wish I could see in a number of spaces, and I'll point to a few. I think the insurance world broadly has a lot of room for innovation, and there are many risks people have that aren't effectively covered today. I'd love to see the rise of a new set of insurance products. There are companies starting to do this. I looked at a company recently called Sentinel that is looking at insurance related to newer challenges we're seeing. As climate change results in more extreme weather events, we’re seeing more things like power outages and blackouts.

Imagine a restaurant. If there's a blackout for a day or two, not only are they unable to open, which is a huge revenue loss, but if the power goes out, all the ingredients in their refrigerators get ruined. There's a real cost to these businesses if an event like that occurs. Historically, there hasn't been a way to insure against that risk. You could insure against flooding from a storm, but not against lost revenue or ingredients from a blackout. Yet events like this are on the rise.

Can we find a way to insure those types risks in a way that is easy to do? I think technology, especially advances in AI, can make insurance claims much easier and faster. Why should we have to send an appraiser to someone’s home to calculate the value manually of every damaged item if there's flooding, when we should be able to take a video around the room and have AI estimate the value of the items and damages? That could mean a claim gets processed significantly faster, someone gets their payout faster, and their home repaired faster. That’s a space that comes to mind right now where there’s huge room for innovation.

One of the things I wonder about the insurance space is whether the fragmentation, state-by-state regulation, is a barrier to innovation.

Certainly, that can be a challenge. I think we're not going to see a lot of new startup insurers because of the capital requirements to be a risk-bearing entity. But there is room for models working on the claims management piece we just talked about, the distribution acquisition piece, and the product piece—partnering with regulated insurers to have them underwrite those products. They can be an MGA, they can drive distribution. So I think there is plenty of room for startups to play in that world.

You mentioned insurance—other startups you wish existed?

That's one I've been thinking a lot about recently. I was reading an article last night on title insurance, for example, and how that's one of the insurance products with the lowest loss ratio.

Insurers get paid to insurance against something that almost never happens.

Exactly. It's an incredibly low probability. Yes, it's a high payout if it does occur, but the probabilities are so low that it's one of the most profitable products out there. Yet it's effectively cartel-controlled in terms of pricing. I think there's a lot of room in that space. There are so many insurance products—gap insurance, for example, is a really interesting space. Insurance that helps you pay for deductibles and copays so you're not out of pocket. It's something I've been thinking about in the last 24 hours, so that's where my mind is at the moment.

Title insurance is one that has been personally very frustrating because it feels like something that fundamentally is an information product. We've got information on paper somewhere in all of these government buildings not accessible.

This is also one of those things— in the US, we don't have a central federal repository of real estate ownership. We have state, often city or county-level records of transactions. So it's not to say someone owns this; it's to say the last recorded transaction on this home was purchased by this person. There's certainly room for innovation even with that infrastructure layer. If we could improve that, we could eliminate the need for products like title insurance.

Are there any other specific customer profiles or problems that you'd want founders to be thinking about? You talked about lower income—anything more specific?

Within the low and moderate income population, there are specific groups that remain particularly underserved. We see a lot of startups focusing on urban areas, but there are people living outside of urban areas—more rural customers, farmers in this country—who are underserved by financial tools. There aren't good products necessarily tailored to them.

Older Americans are also typically underserved by financial services. They're often targeted in more fraudulent ways and with scams. Ensuring someone is financially stable and resilient through retirement is a huge opportunity.

You were talking about other business models. 401(k)s were created to allow executives to get bigger bonuses on a tax-advantaged basis. They weren’t created as a retirement saving solution, though that’s how they're used now. But they are, in many ways, not optimal. They’re not portable, they don’t follow you from job to job, and they often have significant fees, which slows your capital growth. The responsibility still falls on the individual to figure out how much to invest. You don’t know when you’re going to retire or how long you’ll live. As we’ve moved away from pensions, we’ve lost the idea of guaranteed income through retirement. I’d love to see a set of products like that return, with better solutions for people managing their financial lives as they approach retirement.

On the flip side, younger people in this country don’t have great, non-predatory, entry-level financial tools and capability-building. With the rise of the 1099 economy and gig work in the U.S., gig workers are often not well served. Historically, we've relied on employers to provide key financial services—like health insurance and retirement savings—but people who don’t get those through an employer need other ways to access them. That’s just a sample, but there are many segments where there’s real opportunity.

Chauncey’s venture wishlist

🏭 Tech‑Enabled Services in ‘Dusty’ Industries: Apply AI + software to businesses that still run on paper or spreadsheets. Think accounting, benefits administration, etc.

🤖 Personal Automation & Agentic Workflows: Voice‑first or “pocket companions” that ingest scattered data to bring Superhuman‑level productivity to consumers.

🩺 Health‑Span: New diagnostics and delivery models that let consumers manage longevity and chronic conditions themselves, especially in personalized spaces.

⚡ Infrastructure & Hard‑Tech: Anduril‑style moonshots to rebuild U.S. infrastructure, defense, or energy with novel hardware‑software blends.

🌎 Industrial Software: Esoteric but giant markets like procurement, duty‑drawback, carbon auditing, or facility retrofits where SaaS can unlock hidden savings.

Other insights

🕵️ Primary Research Edge: Conviction comes from dozens of first‑hand customer and expert calls; this includes insight from the high density of talent and domain expertise in our own portfolio; desk research alone is a commodity.

🕰️ Timing Is the Riskiest Variable: Willing to bet on ideas slightly “early” if team & market insight are exceptional.

👩‍🎓 Founder‑Market Fit, Credentialed or Scrappy: Either deep insiders or relentless outsiders who earn unfair insight.

⚖️ Skepticism on Roll‑Ups: Compared to vertical SaaS, PE‑style roll‑ups are hard to execute without killer integration DNA.

🎩 Open to Weird Bets: Mining the moon, 28‑hour‑day hacks, or robot‑roofing companies are fair game if the problem is colossal, the market is there, and the founder uniquely qualified.

Full interview

Tell me about XYZ Venture Capital.

XYZ is an early-stage venture firm primarily focused on pre-seed and seed rounds, along with opportunistically small Series A investments from our core fund of $200 million. We also have an opportunity fund of $130 million, which is for Series B and beyond, mostly for existing portfolio companies to continue concentrating capital. We are very ownership-oriented, typically targeting between 10% and 20% when we invest at the early stage. We aim to be a long-term capital partner for our companies that reach escape velocity.

Did you have any particular trends or big opportunities that you wanted to talk about?

Historically, XYZ has invested in enterprise, fintech, and the public sector. We have a good amount of density and strength in both defense tech, like Anduril and Apex Space, and modern social services, like Chapter – helping expand access to more Medicare benefits. But across the board, we are drawn to overlooked industries that have not seen much technological innovation, which often leads to opportunities in tech-enabled services like Rivet for corporate taxes or Ranger for QA. We’ve also explored climate software, procurement, and AI applications. We really like niche subjects that might seem boring to others, but we find them very exciting.

That means you can get a good price if other people aren't thinking about it — it's neglected – and therefore valuations are lower? Why focus on "boring" things?

We think that focusing on less popular areas can sometimes lead to better pricing, but the pricing advantage is more about investing early rather than the industry being "boring," though they can go hand in hand. When this is the strategy, you are investing when it's just two people and a dog, as Rob Hayes, an investor I worked with at First Round, used to say. There's often better pricing, but I think some of the greatest outcomes in venture have been non-obvious. Regarding "boring" industries, we get excited about founders who are deep domain experts, obsessed with a problem that others might find mundane, but where they see a greenfield opportunity. So, our investing is very founder-centric.

I think "boring" can also be correlated with things that were established earlier and therefore might be large markets. If you can build something better in those areas, you can sell a lot.

If you can improve an existing process of something that’s considered arcane and outdated, that’s an opportunity. If someone says, “It’s always been done this way,” that signals an opportunity.

And I think "exciting" markets are often correlated with markets that don't yet exist. It’s a bet that many people will want to buy something new.

Yes, that’s true. Founders who are very vision-driven, who believe the world will change in a certain way even if it hasn’t historically, and who are betting on shifts in consumer behavior, are exciting but involve significant risk. Often, those are what Parker Conrad called “compounded startup” bets or what Josh Kopelman would call a “domino rally,” where many things have to go right for it to succeed. But those can lead to the biggest outcomes in venture every so often you just have to believe multiple things at once.

Do you avoid doing things where the industry has to be created or grown substantially?

No, we don’t. We are drawn to opportunities that feel large rather than incremental. This can range from pitches by people who want to mine the moon for resources to those building new infrastructure in different countries. For example, we were early investors in Anduril. We also invest in healthcare, especially in regulated industries with a lot of friction, complexity, and hard technical problems.

Are there any more specific themes that you’re excited about?

From a consumer perspective, I think there’s a lot of room for automation. I dislike the word “productivity,” but I think much more could be automated in daily life. I see an opportunity in synthesizing data and taking action on it, ideally with a voice interface. This might be a bit nebulous, but I envision a sort of companion in your pocket where you can tell it things that need to be done, and it collects data from different places. This might be an agentic workflow of some sort. I know there’s no investment to make more hours in the day, though my partner Ross Fubini would love a 28-hour day. I think there’s a new opportunity in personal productivity, and there’s a growing willingness from consumers to pay for things that make their lives easier. At a certain tipping point, AI will become mainstream for the mass market.

You saw Superhuman be able to charge a lot for email, which people thought they were getting for free or ad-supported before.

Exactly. And that’s still largely on the enterprise side. I don’t know the exact breakdown between consumer and enterprise for that company, but even little things like Skylight, a digital calendar for families, show potential.

I bet Skylight becomes a big business. I haven’t fully explored its functionality, but they allow you to forward your email to automatically add events to the calendar. There’s still friction, like how it figures out which class my kid is in, but we’re getting closer to that sort of automation, which is exciting.

I heard someone describe being a parent these days as being an executive assistant for your kids, and how great it would be to delegate that work.

My partner Ross’s chief of staff said yesterday, “I’m the chief of staff to Ross. I’m also chief of staff to my one-and-a-half-year-old, Zoe.” That’s accurate. Depending on how many people you’re managing, the coordination and logistics are significant. There are personal pain points where I’m excited for people to build automation, even between multi-app technologies. We see many companies doing this in enterprise, automating workflows, but less on the consumer side.

Another theme is preventative care and increased health span, one might put this in the longevity camp. Many founders are entering healthcare, thinking about care delivery, new consumer products, or new ideas in data collection, all geared toward increasing quality and length of life. That’s exciting.

And have you made investments there? Or do you want to?

I want to make investments because there’s a growing trend of people taking their health into their own hands, realizing the system won’t do it for them – along with new consumer behaviors and willingness to pay. I’ve been looking at functional medicine and new care delivery models, anything biomarker-related. I don’t have a clear thesis, but I see a shift where more people are diagnosed with autoimmune issues or other problems and are trying to navigate it on their own. New companies like Function Health or blood marker companies like Life360 show that the appetite is there.

Who’s that guy doing the biohacking – Bryan Johnson? He’s next level, but he’s pointing to broader trends in health and wellness that we are seeing being widely adopted.

I think it’s interesting how hard it is to time the market. When I was at Wired Magazine, this movement was called “the quantified self” and was a big topic for biohackers and longevity enthusiasts. That was over a decade ago, and a lot of it is just now coming to fruition.

Maybe it's timing or maybe it’s because he looks good in pictures, but he’s gotten a lot of attention. He’s saying what Ray Kurzweil wrote about 20 years ago: stay alive until you get uploaded. Everyone reacted like, “That’s weird!” Johnson is saying the same thing, and many people are reacting with, “Oh, buy me some supplements.”

Venture is often about whether there are new iterations of old ideas. Webvan led to Instacart, which succeeded because of timing.

Similar need but a very different approach.

Yes. The technology shift was mobile adoption enabling Instacart. Market timing is a big challenge in venture. Getting it wrong leads to failure or a need for enough capital to fight another day. This is all compounded by how quickly AI is moving right now. New technology unlocks emerge every day allowing for newer solutions even as existing ones are only getting off the ground.

Bill Gross from Idealab seems to think that’s the most important factor. How do you know if the timing is right?

You don’t. We are all using our own crystal balls to predict the future. My process relies heavily on primary research. It’s the only edge we have. Everyone can ask ChatGPT for information, but I love calling people in and around the market, whether they’re the target customer or industry experts. I gather anecdotal data points and do background checks on founding teams to understand why they’re exceptional. Team, idea, and market timing are all important. I’m most willing to take risks on market timing.

It sounds like you believe you’re forced to take risks, so you might as well focus on the other things. And it sounds like you believe in founder-market fit. Why is this founder the one to solve this problem?

Yes, very much so. But they don’t necessarily have to come from the industry. They need to have done the work. If they’re not from the industry, I like to see that they’ve done things like becoming an outsourced CFO for private practices to understand payments and revenue cycle management before building a new company in that space. I like to see founders get credentialed in their industry, like taking a tax or claims exam. I like to see them understand how the industry works currently and do everything they can to understand it deeply.

Does that detract from their outsider beginner’s mind approach?

Not necessarily. I think there could be two archetypes here. One is from the industry, knows it deeply, and has a theory on what to build. In that case, I like to challenge the founder with, "What have you learned that you didn’t believe before?" I want to see how quickly they are adapting and changing and challenging their own beliefs in customer discovery, and hear how they decided this was the right idea.

The other archetype is someone learning about an industry and coming in with a beginner’s mindset. In that case, I try to understand how deeply they've navigated into that market to give themselves an unfair advantage. You can bet on either archetype, but the diligence and work you do to understand whether that person is the right founder for the company are slightly different.

Are there any startup ideas you wish that you could invest in?

The last three investments I’ve made were in healthcare, energy, and education. I’ve also invested in companies selling into HR, developer tools, and tax automation. The range of what we do at XYZ is vast!

Right now, I’m spending the most time on tech-enabled services. These are traditionally service-oriented businesses where the application of AI can make things faster, cheaper, and better. I’ve been talking to many companies selling into SMBs or automating arduous tasks.

Within tech-enabled services, I’m more interested in companies building vertical solutions rather than the current venture trend of using a private equity playbook to roll up businesses and automate workflows.

I’m looking for founders in these "dusty," forgotten industries that have seen little to no innovation in the technology they use daily.

Do you think those kinds of M&A-driven businesses are VC-backable?

I'm negative on that right now. It feels easier said than done. You see many firms investing in rolling up tax firms or QA firms. I'm skeptical but open-minded to see how it plays out. Do you see anything like that happening where you’re investing?

I’ve certainly thought about those ideas, about starting various M&A-driven companies. I liked, but don't totally agree with, the piece by Slow Ventures on Growth Buyouts. They were trying to say there's the IPO path, there's the build-a-software-startup way, and then there's a third way in between. Some people talk about a third way as being like a Silicon Valley Small Business or a one-round-and-done startup. But they were talking about a third way where you buy your customer because they're too slow to adopt technology, you buy customer margin savings, and then you buy more for expansion.

They have a great example with Metropolis buying the parking garage company. The jury is out. I’m more in the software-enabled bucket plus the third way when maybe the company progresses to a later stage. But with multi-stage funds, they're taking big bets in the space of, "Here’s $20 million, go buy up a bunch of these and see how it goes." I think we’re in the early innings of seeing that strategy play out.

I’ve seen a robot roofing company. Rather than start by selling robots to roofing companies, they’re selling directly to homeowners. It’s vertically integrated. I understand if you have such adoption problems with your customers and a genuinely better solution, not just reducing margin but increasing margin and reducing costs, why you might choose to vertically integrate. It’s a different choice, though, if you’re going to be M&A-driven, which is a specific skill set And if you don’t have much experience with M&A, it can easily backfire.

That’s the awareness piece in backing different founder archetypes: Is this person curious, a lifelong learner, and do they know they don’t yet understand how to do M&A? Are they able to hire and attract someone who can work with them on that?

It goes back to the founder archetype — digging deeply into who that person is, their motivation, and their humility and awareness regarding the skills they need to acquire or develop. That’s yet another reason I take a very founder-centric approach.

Any other things you want to mention that we haven’t touched on?

One thing we didn’t highlight as much is that we’re definitely open-minded to “weird and wacky” ideas. We’re very open to someone trying to solve a really big problem, like, “How do we build more infrastructure in the US?” And then exploring what technology needs to be built, both bits and atoms, to accomplish that.

Matt’s Venture Wishlist

💼 Intuitive Marketplaces: Interest in conversational AI interfaces that help users navigate complex decisions through preference-based recommendations, particularly in areas like fashion and travel.

🏛️ GovTech Innovation: Interest in tools that streamline government processes, including FOIA request management systems, factoring marketplaces for government contractors, and better data infrastructure for government agencies.

🔄 AI-Enabled Roll-Ups: Opportunities in consolidating fragmented, service-oriented industries and applying AI to create efficiency and value, with particular interest in government vendors and service providers.

🛡️ Novel Insurance Models: New insurance products, such as protection against sophisticated scams targeting the elderly, particularly when combined with preventative technology.

🔎 Research & Advisory Marketplaces: Solutions that help buyers navigate the increasing noise in vendor landscapes, providing authoritative research and à la carte data points instead of expensive comprehensive reports.

Other insights:

🌐Rise of Entrepreneurship: AI is enabling a new wave of entrepreneurship by reducing barriers to entry, allowing non-technical people to build technology solutions more easily.

🏢 Government Data Monetization: Potential for government agencies to better leverage and potentially monetize valuable datasets they generate, particularly for large corporate users.

Full Interview

Tell me about Max Ventures.

Max Ventures invests at the earliest possible stages, often pre-seed and pre-product. We pride ourselves on being a day zero fund, meeting talented entrepreneurs when they're considering what to do next or just after launching. Our third fund closed a few months ago, bringing us to approximately $100 million in AUM across all funds.

What industries do you focus on?

We're primarily a generalist fund, but about a third of our investments are in healthcare, where we've established a strong track record. We're also developing a focus in insurance after incubating a company in that space, which gave us deep industry insights.

How does your incubation strategy work?

We've built eight companies over the past seven years. Our approach involves identifying market problems, developing solutions with venture-scale potential, and partnering with exceptional talent. Unlike many studio models, we structure our cap tables fairly, recognizing that founders will be working on these businesses for a decade while we're involved for about a year. Beyond direct returns, the incubation process introduces us to a proprietary network of talent and opportunities we wouldn't encounter through investing alone.

What technological trends are you tracking?

AI is creating opportunities across multiple verticals. For consumers, we're seeing potential for intuitive marketplaces that use AI to understand user preferences in fashion, travel, and other areas. For example, what if you could go to a fashion website and upload images of what you like, and get recommended items you’d actually want to buy.

"Intuitive marketplace"? Is that like talking to AI for purchasing advice?

Yes, it's having a conversational interface where I can express my preferences about travel, fashion, etc. The AI would respond adaptively - if I mention disliking white dots on clothing, it acknowledges and avoids patterns. Or if I say I don't like hotels near noisy main streets, it surfaces quieter options that match my aesthetic preferences.

So it's adding search parameters not built into the original site, remembering preferences, and searching across different dimensions.

Exactly. The question is whether this becomes one big system or if there's room for different approaches.

And does the data live on the seller side or buyer side? I've been wanting a way to carry my data when interacting with LLMs without giving them everything - perhaps using privacy-preserving methods like homomorphic encryption.

Maybe there's a middle ground where platforms like Etsy, Expedia, or Mr. Porter keep proprietary datasets but build better tools around them. They could ask 5-6 orientation questions when you visit, let you upload outfits/brands you like, and then remember you. It's not as seamless as a fully portable solution, but it keeps data siloed if that's preferred.

Interesting.

More broadly, AI is democratizing entrepreneurship by making technology development accessible to people without traditional coding skills. You can bring products to market faster, which will result in an explosion of entrepreneurship.

As a former Obama White House official, there are trends in government that I like.

Like what?

I think there's an opportunity for a factoring marketplace for government contracting. The idea was inspired by a similar concept proposed for healthcare between providers and payers.

In situations where there's a significant time lag between invoice submission and payment, factoring becomes valuable. While healthcare might be challenging to underwrite due to claims denials and rejections, government contracting is particularly promising because the government almost always pays (essentially "triple A" reliability, the payment delays stem from bureaucratic processes, not payment intention, and the current payment process is extremely manual requiring multiple signatures and approvals.)

A factoring marketplace would be especially valuable for smaller government contractors (not the Lockheed Martins of the world). These long-tail contractors face inconsistent payment timelines despite the government's eventual reliability in paying. This kind of marketplace doesn't currently exist but could benefit both contractors and potentially government efficiency.

Why doesn’t that exist already?

Some analog versions of government contract factoring do exist, particularly for specific programs like SBIR grants, where banks will bridge funding gaps between winning and receiving payment.

To properly underwrite government contracts at scale, you'd need a platform that ingests and evaluates all contracts across the diverse government ecosystem (federal, state, county, municipal) and sectors (defense, energy, education, health services).

I haven't seen a broad, holistic digital marketplace tackling this, or even one focusing on a specific sub-sector. Building lending marketplaces is challenging - you need upfront capital, likely need to fund initial deals yourself, and require backing from major lenders like BlackRock.

Beyond factoring marketplaces, there's growing interest in "AI roll-ups" - where investors buy outdated service-oriented companies and apply AI solutions to create value. VCs are funding companies pursuing roll-up strategies in analog, service-heavy industries with long tails of small businesses or sole proprietors (accounting, insurance sales, etc.) that could be transformed with AI. Some new funds focus exclusively on this thesis.

What are some of the opportunities you’re seeing that are overlooked that could definitely be enhanced with AI?

One specific area I'm exploring is FOIA (Freedom of Information Act) request processing. Having worked in government, I know FOIA requests are extremely painful and time-consuming, requiring extensive manual work from compliance and legal teams.

While some software solutions and consultants already serve this need, there's potential for an elegant AI solution that could ingest data more efficiently, generate more accurate FOIA responses, and pull information from different departments automatically. This solution would be highly transferable across different cities and counties because the fundamental requirements are similar enough to make the product exportable to multiple government entities.

Currently, governments don't commercialize or monetize their valuable data assets. For example, when the Department of Energy or NOAA funds climate research on specific watersheds, the resulting data is incredibly valuable to energy companies, insurers, and reinsurers. Yet this data is often made available as open source.

Similarly, transportation data and public health data are being leveraged by private companies like Google and Uber without governments receiving compensation. There could be a way for governments to monetize this data, perhaps with a tiered approach where individuals and small businesses can access it for free, but larger corporations would pay.

GPS is another example of government data that has generated tremendous value in the private sector.

Weather prediction as an industry has been built almost entirely on government data. Despite this, it seems policy decisions have historically been intentional about not charging for access to these valuable data resources.

There could be a tiered approach where government charges corporations for data access while keeping it free for individuals, with the revenue improving data infrastructure for everyone. Current OpenGov data sites, even the best ones, are difficult to navigate.

This improved data infrastructure could help smaller cities, counties, and less sophisticated states enhance their data capabilities. One ambitious idea would be creating a government-side "EHR" (Electronic Health Record) for citizens. With your Social Security number and tax return data properly integrated, the government should automatically know your eligibility for food stamps, housing vouchers, and other benefits.

Currently, data is scattered across different government agencies in isolated pools. Creating a comprehensive data warehouse for each individual would provide tremendous value both for citizens and for reducing government bureaucracy.

Many other countries automatically file taxes for citizens. If you're a W2 employee with an uncomplicated situation, the government already knows what you earned and could calculate your taxes, giving you a chance to review for errors. This approach has been blocked in the US by two main constituents: tax preparation companies who would lose business, and anti-tax advocates who prefer that filing remains painful because they believe it maintains resistance to income taxes.

Empowering government with technology faces resistance from special interest groups that prefer the status quo. There's an emerging issue with new technologies making it easier to apply for government benefits, grants, and contracts - the government lacks the technology to efficiently evaluate the increased volume of applications, creating potential bottlenecks.

If we're creating tools that make application submission easier, we should simultaneously develop technology to help government process this influx. Many startups aren't considering both sides of this equation.

Regarding other opportunities, vertical-specific AI agents show promise, particularly in compliance - a manual, costly process across healthcare, government, and insurance industries. An AI solution here would be elegant.

The insurance industry, especially reinsurance, presents opportunities through live data and updated underwriting models. This extends to non-obvious sectors like shipping, transportation, and construction.

A concerning area is elder scam protection insurance. Modern scams are becoming dangerously sophisticated - for instance, using voice harvesting from robocalls to create manipulated audio that could impersonate someone to their elderly relatives.

Scammers could use voice manipulation to request funds from elderly parents, saying something like "Hey mom, can you transfer me some funds?" I wonder if there's an opportunity to create a specialized insurance product that would protect elderly people from such scams. This could cover situations where seniors transfer money from their accounts due to fraud, especially in cases where banks refuse liability.

It could be interesting to combine an insurance product with software that helps defend against scams.

My family and I have created a safe word system to protect against voice scams. Unless the caller uses our predetermined safe word, we know it's a scam. We were careful not to discuss this safe word near phones or recording devices - we went for a walk in the woods to establish it. Now if anyone contacts a family member claiming to be one of us but doesn't use the safe word, we immediately know it's fraudulent.

Any underserved areas you find interesting?

As AI reduces content creation costs to nearly zero, the marketing noise in B2B will increase dramatically. Two ways to combat this are authoritative research and word-of-mouth recommendations. Two of our portfolio companies reflect this thesis, Elion which is the premier expert research marketplace for healthcare technology and Noble, which is becoming the ubiquitous word-of-mouth or warm-referral option for people making software decisions.

For less complex decisions like choosing a CRM or hotel, talking with previous users is invaluable. Could this approach work for government buyers overwhelmed by RFP responses?

Research and alternative data present another opportunity. Currently, when I need specific stats (like "aviation market in Colombia"), I encounter research marketplaces charging $5,000 for entire reports when I only need one data point. I've never been targeted by Gartner with an ad offering just the stat I need. I'd gladly pay $100 for a single data point rather than $5,000 for a full report.

There's an opportunity to disaggregate research reports into a la carte products - like Getty Images but for data points, charts, graphs, or specific paragraphs from research reports.

That's interesting. General market stats do show up in SEO, but not narrow stats that follow you around.

Google performance ads exist, but I've never been targeted on Instagram with Gartner offering a graph of exactly what I searched for. Market data is either inaccessible ($5,000 reports), untrustworthy (random Google image search), or occasionally in trusted sources like the Wall Street Journal.

This interview has been edited for length and clarity.

Katelyn’s Venture Wishlist

🧑‍⚖️GovTech: Developments in procurement tech and efficiency to make government processes smoother and more competitive, replacing outdated systems with nimble, private sector solutions.

🌐 Decentralized Systems: Growth in platforms that allow individuals to own their online experiences, moving away from centralized, ad-driven models to empower user agency and data privacy.

⬆️ Entrepreneurial Shifts: Shifts towards more work being done by entrepreneurs over employees will require different systems. Technology that powers digital native jobs or helps SMBs and solo-preneurs.

📚 Efficacious Edutainment: In a world of AI-generated slop, there is still a need for high-quality, curated content delivered in a gamified and immersive way.

Other insights:

🧑‍✈️ Founder Experience Advantage: Founders with deep, firsthand knowledge of the problems they're addressing have a competitive edge, particularly in fields like education, where understanding customer needs is crucial.

⚖️Venture Viability of AI: Skepticism about the venture scalability of AI solutions that do not fundamentally change business processes or offer clear, differentiated outcomes. AI allows for greater capital efficiency.

🏦 Private Market Dynamics: Insights into the dynamics of private financing, with an expectation of increased liquidity and more sophisticated market mechanisms evolving to facilitate easier asset trading.

Full Interview

Tell me about Avalanche.

Avalanche invests pre-seed and early seed in companies that transform how people learn, earn and own using technology. We focus on founders who are building their life's work. They have noodled on a problem for a long time and then come up with a solution that they believe can fix a key gap in the industry they are trying to disrupt.

When you talk about a founder having deep experience with a problem, what advantages does that give someone? What counts as deep?

For example, we were the first investor in a company called Prisms, which is the world’s first spatial learning platform in which students learn core math and science. The founder was an MIT-trained engineer and then a classroom STEM educator for secondary schools. She also built the STEM curriculum for Success Academies, the premier charter chain in New York City, and worked for the New York Department of Education. While there, she got a grant from the National Science Foundation to build a math and science curriculum in virtual reality because she saw that the best practice pedagogy for students to learn these concepts was having real-world problems using spatial reasoning and being immersed in that full environment.

Having been in the public education system, she understood the things that the big school district customers would need in order to make a purchase of a new math curriculum. She invested in efficacy studies early on, which showed that it was a highly impactful program, starting with the key hinge point of middle school math. If you don't make it through middle school math, your life outcomes are severely impacted. The public system has a lot of accountability mechanisms built into it around students learning these math outcomes.

Anarupa, having seen firsthand the opportunity, was up for the challenge, knowing that by building this business to be successful, she would need to be on a plane every single day, meeting with superintendents of big school districts and going through school board processes. I don’t think anyone else could build this company.

How did you pick “learn, earn, and own” as your investment focus?

Well, it's the journey every successful person must go through in a capitalist society.

First, you learn to read, and then you read to learn, and then you learn to learn, and then you learn to earn and become productive. Someone pays you for your labor and then ideally you turn your labor into ownership, whether that's like a 401k or owning your own business, or owning equities.

If you're able to turn your earnings into ownership then the government has to step in and provide the infrastructure and assets to provide for your quality of life, which is why we also focus on government efficiency. It's this underappreciated backbone of society that goes through everything.

One of our massive avalanche trends is that many of our traditional institutions are decaying. They haven't kept up with technology and are built for a more centralized, slower-moving world. They need to be reinvented. Technology companies that allow individuals to be empowered to succeed in that journey will rise to prominence as the traditional institutions that people rely upon begin to disappear..

What are some of the other avalanches you’re anticipating?

One of them is the power of decentralized and open-source data architecture to allow people to own the instance of their experiences online.

I was an early investor in Bluesky as it pivoted out of Twitter. The idea was that almost every social media organization is in a walled garden where you're beholden to a specific algorithm, often ad-driven, looking to keep you engaged on the platform.

Bluesky was a Jack Dorsey project for which he gave an R&D grant out of Twitter. He hired the CEO Jay, who spun it out entirely as a new organization and raised a venture round for it ~18 months ago. Bluesky is just one instance on top of decentralized architecture called AT Protocol. For most of 2024 they had about 5 million users, usage was steady, and then all of a sudden, the election happened and a bunch of organizations realized that they were not getting very good engagement on X/Twitter because they couldn't control their experience.

Bluesky has this ecosystem that works and people came over en masse and the network went from 5 million accounts to 25 million accounts in a few weeks. They were adding about a million users a day after the election. Now, growth has slowed pace, which is good because they need time to build out the infrastructure for the next phase of growth.

That's a very clear avalanche of the institutions of Internet 2.0 that people were always dissatisfied with but had no alternative. The alternatives looked nascent and maybe not ideal, but suddenly, people's imagination shifted.

Another avalanche made more evident in the election is the push for government efficiency and last-mile delivery of public goods. The Department of Government Efficiency has ignited excitement in the popular psyche. For such a long time, GovTech has been such a deeply unsexy area. People thought, “don’t sell to the government, don't even talk to them.” It was seen as a monopoly where you wouldn’t be able to get anything through. And now, people are more optimistic that things can change and have to change.. Government is a core institution in our society that needs to have the effectiveness of a high-performing private sector organization.

Do you have a more specific GovTech thesis?

One of the theses we've already invested behind is called from red tape to red carpet about the rise of procurement tech. The key linchpin of the government is the procurement process. Suppose you make RFPs easier for younger, more nimble private sector organizations to bid on, increasing choices in a potentially more competitive way. In that case, you will be able to replace the old and stodgy elements of government with better quality.

We need more competition and private sector delivery of those traditional government functions.The same thing applies in education or healthcare. How do you get people who are not directly government employees to be delivering outcomes for the public?

What's your current obsession?

One thing I've been thinking a lot about is the very amorphous services and software continuum. As AI bounds ahead, to get real productivity, you have to get the human-technology integration right. I feel like you still see a lot of people in technology operating in silos, without thinking about how this actually implements into a real context.

Is that about building a business process around it or making it something people can buy with the right pricing and packaging? Or is it something else?

Well, sometimes I think, “is this even venture-scale?” Is it just Services 2.0? Ultimately, the most effective humans who use these tools will continue to be the most effective. And these are not true technology companies. I think a lot about how the venture game is changing.

People are talking a lot about paying for outcomes. Instead of selling software that helps you do a business process, you just pay for the outcome. I've heard more talk than seen it actually happening. Like service as a software?

I did a site visit to a company that said, “We predict the future.” But they didn’t predict the election correctly, and it’s unclear how accurate their models actually are. Maybe more hype than reality in terms of outcomes.

In contrast, I toured a fantastic K-8 school last week that teaches kids how to be entrepreneurs. Super exciting. I had a two-hour meeting with the principal and at the end, I asked about this hot AI education company. She had never heard of them before.

Nothing about this inspired school requires what the AI education company offers. They say you can create lesson plans with a couple clicks, but at the best schools, they don't need to do lesson plans the day before. They have their own curriculum and the ChatGPT-generated lesson plan is not moving the needle.

On nights and weekends, I think about how much I should be investing deeply in these AI-enabled tools, which look like they've gotten all this traction very quickly. Is it overbuilt, oversold and going to be disappointing? Maybe some will win, some will not.

So, I don’t think we know yet but I believe there will be a bifurcation between almost all online jobs and all offline jobs.

You yourself founded a services business and are not traditionally not seen as VC backable. Does that change if it's mainly AI and it's undercutting price-wise what was traditionally a services business but is delivered by software and a lot fewer employees?

I don’t know. I see many AI-enabled companies with few employees deliver, I wonder why they are raising money. Do they want a nicer office? They might want to ‘grow faster.’ Also, as the AI-services are undercutting price-wise, it might be hard to build a profitable business as you can’t charge as much, and competition is fierce. Where will the margin come from?

That AI prediction company in New York I mentioned had a large office and they were getting paid $30k to do a piece of consulting work. That’s not very much. That either could have been a whole McKinsey study in the past or it was just a tiny piece of the puzzle that the AI model could spit out almost instantly. Without a series of change management and human touch elements, it might get commoditized quickly.

Do you have any recommendations for founders and like customer profiles or problems that you think are being neglected?

High-quality content is still king. With AI-generated slop, there will still be a place for high-quality, engaging, thoughtful content that's curated. I’m not sure if that’s venture-backable, but maybe someone will find a way to do that.

Everyone is an entrepreneur or they'll have to learn to think like one. That means that everyone will be or have their own LLC, where interactions will be more contractual. The atomic unit of the economy will be the individual acting as an entrepreneur. There certainly are a slew of fintech companies that see that and are building behind it. But I haven't seen one that is at my stage and I'd like to back a business that really understands this.

Anything else?

Private companies will choose to stay private longer. There is way more demand for alternative assets and different financing options. At the same time investors are getting pushed to return money to their investors. We will see more marketplaces that seamlessly offer people liquidity and real-time pricing on assets that were more complex and highly illiquid in the past.

Databricks just raised their Series J of $10 billion size. This is unprecedented late-stage financing in terms of size. They’ve taken a bunch of money from some asset managers who have collected money from a bunch of other people. Isn't this just like a public market mechanism but with high fees?

Time will tell, and the pressure may build up in unpredictable ways. It will be fascinating to watch and is certainly something to pay attention to as an early stage investor.

This interview has been edited for length and clarity.

Alex’s Venture Wishlist

🚄 Renting Scale: Small businesses increasingly "rent scale" by leveraging platforms like Ramp or Brex to achieve mid-sized business efficiency with minimal resources. Alex is looking for applications of this model across verticals and regions, in particular: ZenBusiness (business registration and regulatory compliance) and Flychain (complete finance suite for healthcare practices, including accounting, treasury management, revenue cycle management) globally and in non-healthcare verticals.

🏢 Zetwerk for other manufacturing hubs: Zetwerk is an Indian company that coordinates manufacturing at thousands of factories, allowing companies to source multiple products in India through a single interface. Alex is looking for similar companies in other emerging markets – particularly Mexico.

💸 Stablecoins: Stablecoins are showing potential beyond crypto-native companies (Example: Bridge: stablecoin infrastructure for global transactions; recently acquired by Stripe for $1.1B).

👵 Silver Tsunami Opportunities: As baby boomers retire, the majority of US SMBs will lack an owner/operator and be too small for private equity. Business models that provide the capital to transition these businesses and simplify expertise to manage them will be attractive in the US.

📈 AI-Driven Small Business Investment Bank: Inspired by a success in Japan, AI platforms can streamline small business investment banking, enabling bankers to handle transactions efficiently.

🌍 Global Healthcare Opportunities: Fair, transparent, and modern insurance companies that support healthcare access and delivery. Models like Sidecar Health in the US (Alex was an early investor and Board member) are examples of cash based health. Vertical delivery platforms like Maven Health in the US for women's care, or Livongo on Diabetes are powerful models.

Other insights:

🐪 Camels vs. Unicorns: Build "camels," not unicorns, by prioritizing resilience, strong unit economics, and long-term sustainability, rather than blitzscaling at any cost.

📉 Mini J-Curves: Pursue growth through repeated, smaller cycles of profitability and funding rather than a single deep J-curve, to mitigate financing risk.

🌎 Geo Arbitrage: Innovation flows both ways. Proven models in emerging markets, can also be applied in the US.

Full Interview

Tell us about your fund and strategy.
My quick story: I grew up in Canada. My mom is Belgian and grew up in Africa, my dad’s American. I have a big Eastern European family, my godmother’s from China, and my aunt is from Argentina. So, perhaps it was inevitable that I’d run a global VC fund.

Our strategy is around geo-arbitrage. If you look at the number-one tech company in any market around the world—China, India, Africa, Korea, Latin America, Southeast Asia—they’re all pretty similar. They’re often "Amazon for X."

Our focus is on the next two to ten companies in these markets. Our model is to identify proven scaled models that exist elsewhere and partner with entrepreneurs working in those categories in new markets. We aim to bring these often highly impactful, demonstrable approaches to other places. We’ve built a platform to execute that playbook as early as possible.

And you’re on Fund One?
Yes, Fund One. But in many ways, this is year 12 of my journey doing this. I spent five years at Omidyar Network and then five years with Cathay Innovation. In both cases, I was based on the West Coast but worked with a global portfolio.

Given that you have this view of venture globally, is there something that US VCs are missing?
One of the reasons I love the concept of this Wishlist newsletter—and I think it’s brilliant—is that Wishlist is, in some ways, the theme of our fund. Our strategy is to pick a model we like, and that becomes our wishlist to find and test in other places. Our wishlist is public; I literally have it on my website, and we update it every quarter. Around 75-80% of the companies we meet align with that wishlist.

Let me talk about one macro theme we invest in and a couple of specific business models I’m looking for right now.

I think we’re going to see small businesses increasingly able to "rent scale." What I mean by that is, historically, small businesses had to grow into medium-sized businesses to compete and benefit from economies of scale and scope, and medium businesses eventually became large ones depending on the industry.

Today, a small business can rent scale. For example, using something like Ramp or Brex, a small business can access financial controls similar to those of a mid-sized company, but with just one person in finance instead of a full team. In our portfolio, Flychain does something similar in healthcare. We're looking for applications of that model in other verticals and geographies. That’s one item on our wishlist.

Another example is ZenBusiness. ZenBusiness allows small businesses to start, run, and grow by handling everything from business formation to bank account setup. Because they know where you live, what you do, and your business needs, they can offer tailored services. We think this model is highly applicable in other geographies. We’ve backed one vertical-focused company in the U.S. and a couple of similar plays in other markets.

Finally, I’ve been thinking a lot about how small businesses can achieve scale in procurement and distribution. We’ve invested in a few B2B marketplaces and seen models emerge in India that haven’t yet appeared in other emerging markets—or even in the U.S. We’re actively looking for those opportunities.

Years ago, people might have said, "How do you learn what’s happening in the U.S. and carry it to emerging markets?" But you just mentioned something interesting—that there’s something happening in India that’s not happening in the U.S. and might apply here. Can you say more about that?
Yeah, and I’ll start by saying I’ve been lucky enough to back seven unicorns. The biggest company I’ve ever backed is actually an example of this model. The first iteration was in Russia, the second and third were in Europe, the fourth—depending on how you look at it—was in Latin America, and only then did it come to America. This was in the digital banking space.

I think we’re seeing a pattern where global ideas can emerge from anywhere and scale everywhere.

In India, one of the biggest emerging categories has been B2B marketplaces. These marketplaces digitize parts of supply and demand, merge them with vertical software, and provide embedded fintech. This is playing out in manufacturing, construction, FMCG, industrial inputs, and other verticals.

Let me talk about one company—we just announced their round this week. One of the big shifts that happened recently is the move from supply chains centered in China to a "China +1" strategy. India has been a significant beneficiary of this shift. A company called Zetwerk has created a platform for manufacturing in India, connecting thousands of plants. They look like the biggest manufacturer, but behind the scenes, they handle complex sourcing, delivery, quality control, and more.

We believe this model should work well in many other geographies. Right now, perhaps the most exciting market for nearshoring and friendshoring is Mexico. We’ve met most of the companies there doing this and backed a company called Prima. That’s an example of the globalization and cross-pollination of innovation we’re seeing across different markets.

Are there any “why now” trends you’re seeing that unlock opportunities? AI is an obvious one, but are there other areas where new capabilities—whether from consumer shifts, new markets, technology advances, or regulatory changes—are driving things you’re looking at?

Let me talk about two trends. One is a bit "hot" right now that I didn’t think I’d be excited about but am spending a lot of time on. The other is a big demographic shift.

The first is stablecoins. I’ve been an early investor in crypto personally since 2013—I bought my first Bitcoin then—but I’ve never invested other people’s money into crypto or adjacent business models. I haven’t had conviction around an actual business model solving real problems, particularly within our geo-arbitrage model. I’ve also avoided cross-border foreign exchange or remittance models because I didn’t think they were disruptive enough. By the way, I’ve been wrong about some of those.

Now, I’m actually pretty excited about stablecoins and what’s happening there. We’re starting to see proven models and early exits, like Bridge a few weeks ago. If crypto trading volumes keep increasing and interest in stablecoins grows—not just from crypto-native companies but from others as well—I think this space could become really interesting.

The second trend I’m focused on is the "Silver Tsunami"—the wave of baby boomers retiring, maybe getting sick, passing down their businesses, and so on. I’ve been really interested in what happens to the businesses they own, especially in cases where the kids don’t want to take over, there isn’t a trained workforce, or the businesses are too small for private equity. That applies to about 80% of small businesses, like my mom’s medical practice with just one employee.

There are exciting new plays emerging around this transition. We’re spending a lot of time on the business side of it, but more broadly, the Silver Tsunami as a whole is a fascinating trend to watch.

How are people solving this in other countries?
One of the models we’ve seen, with a lens on global becoming cross-border, is in Japan. One of the fastest-growing unicorns there is an AI-driven small business investment bank. It simplifies onboarding by understanding what the business does and automating many banker workflows. This allows a banker to handle 20 or 30 transactions at a time instead of just two or three. It also matches buyers and sellers and helps pitch deals appropriately.

That model has scaled terrifically in Japan, and we think it could work similarly here. We’re actively looking for interesting companies executing this playbook. This model could also work well in Europe, Korea, or other markets. We believe it has a lot of potential globally.

Have you spent more time on cash-based health?
I was an early investor in Sidecar Health, which is in that space. I’m obsessed with three trends in healthcare and continue to focus on them. Geo-arbitrage in healthcare is a bit trickier—you have to squint to find global models directly applicable to the U.S., and it’s challenging in the other direction too.

The first trend is greater transparency in pricing. Anything that promotes that is very interesting, including marketplaces and foreign travel plays.

The second is giving more agency to customers, allowing them to choose and define value. That’s a fascinating area, and we’re seeing some exciting developments.

The third is vertical delivery in healthcare, like what Maven Health does for women or what Livongo did for diabetes. Depending on the market and reimbursement models, some of these approaches might work in other places. We’re going into this space with an open mind.

When you think about the themes you’ve shared, are there any specific customer segments or profiles you’d direct founders toward, or is that not really how you think about it?
That’s less how we think about it. I’ve mentioned three broad customer segments: one is around the Silver Tsunami and boomers, another is small businesses, which we consistently focus on, and the third is consumer. Those are broad categories, but what I really like is when there’s a dislocation event—a reason for change from one thing to another. That’s where we tend to spend time, rather than focusing on a specific demographic need.

You’ve also written a book. Can you share a little about it?
I’d be happy to. I wrote a book called Out Innovate: How Global Entrepreneurs from Delhi to Detroit Are Rewriting the Rules of Silicon Valley. It was published by Harvard Business Review Press and has been translated into Chinese, Korean, and Spanish, with more languages coming next year.

I wrote it out of frustration. When I started the book, and even today, the conversation about building startups outside Silicon Valley was dominated by a single place and approach—Silicon Valley itself. But when you look at top entrepreneurs worldwide, their stories often run counter to the conventional wisdom here.

I interviewed about 100 unicorn founders and exited founders globally to uncover what worked for them. The result is a playbook for building startups around the world, which aligns with the driving force behind my fund and my broader work.

And how does that tie in with your Substack?
The Substack is a continuation of that conversation. I run a newsletter called 99Tech, which serves three purposes. First, it features the stories of founders that others might not have heard of, highlighting not just what they do but how they do it and the lessons we can learn. Second, it shares some of our firm’s learnings about what we’re seeing around the world. Third, it occasionally includes guest posts from other VCs and market leaders to share their perspectives and foster collaboration.

Is there anything from the book you’d like to highlight, like a concept or mental model, aside from cross-border themes? Are you looking for "camels" or something else?
When I wrote the book, which came out in 2020 during COVID, the prevailing best practice for startups was blitzscaling and pursuing growth at any cost. At the time, I was advocating for a different approach: building while managing burn, with strong unit economics and a long-term outlook. I described this as building camels.

Camels are resilient, efficient, and can endure tough conditions while still thriving. You can still aim to become a unicorn—a billion-dollar camel—but it’s about how you build to get there. This philosophy has become more widely accepted today—it’s a more centrist, reasonable approach.

As a VC, I’m looking for companies that can grow fast but do so in a responsible, controlled way. This focus on capital efficiency influences how we select business models. We partner with founders who share this philosophy, aiming for repeated success. If you retell the story of a startup a hundred times, this approach increases the odds of successful outcomes for the founders, investors, and customers.

What is the magnitude of the trade-off, or how do you quantify the balance between extreme growth and unit economics—or what you call responsible growth? How do you know if you’re growing enough, or if you’re sacrificing too much upside by being "responsible"?
I don’t think it’s black or white—it’s more of a spectrum. For instance, Chris Yeh, who co-authored Blitzscaling with Reid Hoffman, is a friend and blurbed my book. When we discussed this topic, I’d probably agree with Chris in saying there are models, like consumer marketplaces, that are winner-take-all. In those cases, if your competitor has raised a lot of money, blitzscaling makes sense.

On the other hand, there are models that clearly don’t benefit from that approach. My perspective is that most businesses fall somewhere in the middle—they’re not true winner-take-all. That’s where the philosophy of responsible growth fits in.

My bias is that most companies should aim to have a sustainable unit economic model from the beginning. Understand your metrics, like LTV, and then make a decision: do you raise venture capital, and how much growth are you targeting? This is where the trade-off lies—how deep you want your J-curve to be.

What I’ve observed, especially outside Silicon Valley, is that instead of one deep J-curve, many founders create "mini J-curves." They grow a bit, return to near-profitability, then raise more for a specific purpose or timeframe, repeating this cycle. These more modulated dips are something I’ve seen in companies that have scaled significantly outside of Silicon Valley.

For founders reading this, who should be in touch with you? Is it people based outside the U.S. building businesses aligned with one of these themes? Is that the way to think about it?
Yeah, I’d say so. About a third of our portfolio is in America, and two-thirds is global. We only invest in a handful of proven scale business models at Seed, Seed Extension, or Series A. If you’re building something de-risked somewhere else on the planet and raising at those stages, come talk to us—that’s potentially in scope for us.

This interview has been edited for length and clarity.

Gale’s venture wishlist at VITALIZE:

💼 Horizontal Work Tech: B2B software for horizontal applications relevant to any industry, like customer success, operations, and data.

📊 Proprietary Data Models: Companies leveraging proprietary data as a core differentiator.

🏠 Verticalized AI: AI-enabled solutions tailored to particularly sleepy industries. Built Right, for example, serves home services providers with integrated tools for lead generation, operations, and marketing.

Gale’s venture wishlist personally:

🌍 Sustainability: Innovations in sustainable materials, replacing Styrofoam and plastic with eco-friendly alternatives.

🐾 Pet Tech: Advancements in animal nutrition, pet health, and other services in the rapidly growing pet market.

Other insights:

🤖 AI Hype: Generic AI companies are not compelling. Without strong differentiation and proprietary data, AI startups are commoditized and overvalued.

💰 First Principles Valuation: Valuation is a math problem, aimed at ensuring 30x returns are realistic given traction, potential scale and multiples at exit, and capital requirements to get there.

📈 Shifts in Pricing Models: Enterprise is more reluctant to buy SaaS subscriptions, and is shifting toward transaction-based pricing models that align with customer behavior.

🌐 Community as a Driver: Community is increasingly attractive component to B2B business models, given the role of influencers in shaping adoption.

💡How to Find Ideas: Don’t brainstorm what you think people want. Figure out something in your life that genuinely interests you. Research, talk to people, and see what rises to the top.

🧤Founder-idea fit. Founders have to do what they love. A strong fit between personal interests, background, and the problem they choose to work on trumps anything else.

Full Interview

Tell me about Vitalize.
Vitalize is a venture firm that invests in work tech. I define work tech as B2B software that dramatically improves work outcomes. These are big ideas that create huge gains for companies and/or their employees. This includes horizontal applications relevant to any industry, like customer success, operations, and data, as well as vertical applications within sleepy but very large industries. There are often opportunities to dramatically transform how work is done today, and we look at those as well. Our fund, Fund II, is $23 million. We write checks of $250k to $750k at the seed stage.

How did you get interested in that area?
I've been investing since 2012 across many different sectors. When I look at my track record and the founders I've backed, I've found the most success within software. Specifically, the people element of work tech is interesting because we want to improve lives—whether at the employee, client, or executive level. The companies we gravitate towards are doing meaningful work to improve the lives of those groups along with company outcomes.

Are there any concepts or mental models you use when thinking about investing in this area?
Many companies fit within our work tech definition, and it’s intentionally broad. My approach to investing is about finding a magical mix: an interesting concept in a big and growing market, led by a founder with great experience and the passion to take the business forward for however long it takes to succeed. We also love to see a proprietary data element in the models we back.

For example, I’ve said for many years, I don’t invest in AI itself—I invest in platforms, big ideas, and data. In my opinion, data holds much more value than AI, which is becoming increasingly commoditized. I’m not looking for features, "me too" products, or slight improvements over what exists. That’s why I focus on ideas that are dramatically transformative. AI is often a part of what we invest in, but I’m not interested in companies that position themselves as “AI for X.” That’s not compelling to me.

So that sounds like maybe a non-consensus belief. You see AI companies getting markedly higher valuations?
Yeah, I think this is going to play out like the recent crypto bubble. What I see coming across our desk is tons of the same thing. For example, generating sales leads using AI—lead gen with AI. It’s so easy now with off-the-shelf tools, and yes, it makes sense compared to how things were done 5, 10, 20 years ago. But now, there are so many of them, and people are inundated with content—they just don’t work. There’s not enough differentiation in those models.

Any other non-consensus beliefs you want to highlight?
This was interesting—it just happened this morning. After I said our firm would pass on the investment, the founder mentioned, “Every single woman I’ve talked to that runs a VC fund has told me that we don’t have enough ARR or our valuation is too high, whereas men are much more interested.” I told her I don’t really think this is gendered, but it does bring up a non-consensus view. Maybe women are more likely to have it, I don’t know, but I’m basically underwriting a math problem.

What is the state of the business today? The valuation today? How much capital do they need to raise in the future? How much revenue can they get to, and at what revenue multiple can they exit? I bring that math back to today and ask, can I 30x my investors’ capital realistically? The higher the valuation today, the harder that becomes.

I don’t believe I should throw money at a company just because I like it if the terms today don’t make sense. I don’t have to always be under a $10 million cap or anything like that—some VCs are very strict around terms. But if something is crazy hot and everyone wants in, that doesn’t make sense to me unless all pieces are in place. I need to believe in the founder, the market, and the business model, and it has to make sense when I do the math.

So what is the last investment you made that you were thrilled or excited about?
Our latest one is Built Right. I don’t often invest in SMB, but I did this deal in the home services industry. Built Right provides a solution for small providers like landscapers, roofers, and drywall contractors to manage their business. It covers lead generation and managing their operations.

What sets them apart is their AI element. They can create a website in seconds, but it’s different from Squarespace or other existing tools because they integrate with Google Business, Yelp, and other platforms these owners need for marketing. There’s a data layer underneath that makes everything seamless, connecting the tools these providers are already using. It’s automatic but also very smart, and that’s the differentiation—the secret sauce.

They’ve grown their ARR extremely fast. It’s been a really fun business to watch. The founder is very focused on the home services industry and plans to continue building solutions specifically for these providers. I think this focus is a trend we’ll see more of, especially with AI solutions. We’re moving away from horizontal applications toward more vertical solutions tailored to specific industries as the tools get better and better.

So customers want something customized for their industry?
I think so. This is a good example—it’s not just a lead gen tool. I see so many generic lead gen solutions that don’t really work. Built Right is relevant because it integrates with the tools and systems these providers already use, which are specific to their business. It wouldn’t necessarily work for someone in a different industry.

I’ve also seen lead gen solutions specific to the legal space and other industries. Verticalization within AI tools is becoming more common because it’s so easy to get them off the ground. I think this trend will continue.

Are there any other trends you're watching that represent big opportunities?
This is more of a contrarian view, but it’s also a trend I’ve noticed. The buying behavior at companies has dramatically shifted in the last couple of years. Companies are more hesitant to buy software with recurring models, even though VCs historically have preferred those. Going forward, I think there’s less certainty that these contracts will remain. Businesses are moving toward transaction-based pricing models.

For example, the one we invested in together, Miles, is a great example. In hiring, subscriptions don’t work—they want to pay per hire. What Twill is doing is brilliant, both for its focus on community and network, and for its transaction-based pricing. It’s not 100% a service model; it’s a productized transaction that buyers can access at a reasonable price. I think more companies will adopt that pricing model.

And you mentioned a trend around community. Is that something else you’re investing in?
Yes. People are at the core of much of how I think about investing. Historically, brand has been about pricing, product, and packaging. Those things are still important, but the people-side is now even more critical.

Who are the influencers buyers are paying attention to? Who are the thought leaders in a community? Who’s managing that community? What are the community members doing for each other? These dynamics are shifting how people interact with solutions, both at the consumer and business levels.

I’m seeing a lot of community-based plays right now. I might not invest in a pure community business, but a business with strong community elements is very smart.

You see tons of deals and have for years. You’ve mentioned seeing lots of “AI for X.” But what’s missing? What do you wish someone would create?
In the software world, what buyers and executives are ready to adopt is a key factor. Companies need time to evolve and keep up with technology because there’s a human element to software adoption.

Personally, I think we’re ripe for the next stage in a lot of areas, especially sustainability. For example, why are we still using Styrofoam and plastic when better materials already exist? It’s beyond me why companies aren’t embracing that. I think we’ll see a lot of progress there in the coming years.

I’m also passionate about the animal space. As an animal lover, I believe we’ll see advancements in areas like animal nutrition, pet health, and products and services for pets. It’s a huge market, and I think we’re still in the early stages. These are the two areas I’m most excited about—sustainability and pets.

Are there any customer profiles or problems you’d direct founders towards? You mentioned sustainability and pets—anything more specific or anything within Vitalize’s focus?
I always think founders should pursue something they love. It’s going to take at least three years of running a business before you feel like you really have something, and there are so many ups and downs in the journey. You know this, Miles. I’m in year 12 of building and learning VC funds, and it’s a lot.

You have to love what you do because there will be tough days. I don’t advocate sitting down and brainstorming what you think people want. Instead, figure out something in your life that genuinely interests you. Start researching, talking to people, and see what rises to the top. Follow that, rather than forcing an idea—it hardly ever works.

So you’re advising founders to ensure there’s a strong fit between their personal interests, background, and the problem they choose to work on?

Definitely. That should trump everything else.

This interview has been edited for length and clarity.

Matt’s venture Wishlist: 

• ℹ️ Aggregating public information: Matt has invested in companies like GenLogs that uses sensor data and computer vision to track truck movements and Cloverleaf AI that aggregates town hall and public meeting data. 

• 🚚 Supply chain optimization: Capturing digital exhaust and actively digitizing supply chain data creates opportunities for AI-powered digital transformation of the supply chain. 

• 🌊 Data collection moats: These could come from the ability to collect evanescent data (e.g. public live streams that disappear otherwise), with collection supply constraints (e.g. fixed data collection points), or scale 

• 🧑‍💼 AI products that focus on middle managers: these managers are “front line” buyers for productivity-enhancing AI products, and often have decision authority for shorter sales cycles than traditional enterprise products. 

Other insights: 

• 🚦 “Vertical” data collection can serve “horizontal” customer use cases: GenLogs and Cloverleaf both aggregate a single type of data that is valuable to different industries, with varying use cases. 

• 🔭 Projecting implications of general purpose LLMs: Part of Matt’s focus on novel data collection is to ensure that GPT 5, 6, and 7 increase rather than erode the value of data-based companies.

• 🔗 Combination of data sources: Some companies can create value by combining novel data sources with existing public or commercially available data, such as in out of home advertising.

Full interview

How would you describe the focus of most of the investing you're doing today?

Unlike funds that develop a fixed thesis for three to five years, we can be more opportunistic and adapt our thesis as the market changes.

One area we're particularly interested in is hyper-contextualized data and its strategic use versus mere data acquisition. We're looking at companies that gather public domain information in innovative ways. This can involve using edge computing to capture sensor data or leveraging publicly available datasets combined with proprietary internal or customer data. The goal is to deliver and maximize value to end customers.

We're not just talking about building large language models for the future, though that's a possibility. Instead, we focus on how companies use existing data sources to create significant outcomes for their customers. 

I'd love you to share a few examples that illustrate the types of data and opportunities you've seen.

One of my favorite companies in our portfolio is GenLogs. They're based in Virginia and are building a national network of sensor data along highways. They're targeting billboard operators and employing computer vision algorithms to track truck movements across the country.

What's fascinating about this is their innovative use of public domain information. Instead of placing people on every bridge to inefficiently monitor truck traffic, they've identified 100 to 300 prime locations nationwide to monitor truck movements effectively. This addresses a significant problem in the shipping and trucking industry, where 35% of trucks are driven empty. Improving efficiency here benefits greenhouse emissions, shippers, brokers, border control, hedge funds, and more by ensuring trucks are filled to capacity and operating efficiently.

On a completely different industry spectrum, we have Cloverleaf AI, based in Denver. They aggregate live stream links from town hall meetings across the country and use content analysis tools to understand the discussions. This information is valuable to various entities: if you care about net neutrality, it helps track relevant discussions; for a construction company, it provides leads on potential projects like pothole repairs; for Airbnb, it monitors HOA regulations. This data is valuable to everyone from local politicians to Fortune 500 companies.

We also have a company in the out-of-home advertising space, OneScreen AI, building the largest inventory of such advertising. They leverage publicly available information, sometimes for a fee, combined with proprietary internal data, to optimize return on ad spend. In an era of GDPR, the right to be forgotten, and CCPA, out-of-home advertising is becoming more attractive due to fewer online advertising restrictions.

I'm curious if you've thought about what makes for a good data source?

A key factor is how defensible and hard-to-acquire the data is. For example, with GenLogs and Cloverleaf AI, the defensibility comes from unique challenges in data collection.

For GenLogs, a freight logistics company, their moat is the strategic placement of cameras and sensors. There are few locations that make sense at scale for building this dataset, which creates a significant barrier to entry.

In the case of Cloverleaf AI, while the town hall meeting links are publicly available, aggregating them is labor-intensive. The value they've built comes from the significant man-hours invested in this process. In the future, scraping tools or generative AI capabilities might streamline this, but Cloverleaf AI's first-mover advantage and contextual knowledge give them a head start.

Additionally, understanding how to build and present data solutions to the right buyers early on is crucial. This involves developing alert systems and recommendation engines tailored to their needs. It's about contextualizing the information not just within its immediate environment but also in a broader macroeconomic or geopolitical landscape. Combining this data with other third-party sources can provide unique insights that competitors can't easily replicate.

Are there any other macro themes that you've been exploring?

What I like about this theme is its cross-industry applicability. Although I haven't done much healthcare investing, I see companies solving transparency issues around costs and improving patient outcomes by leveraging publicly available information combined with internal data from organizations like Red Cross or Blue Cross. This approach creates improved patient outcomes and is an area I'm interested in.

Looking at GenLogs, they use edge sensor data to monitor truck movements. I've seen companies applying similar technology for public safety and traffic management in public spaces. 

Regarding other specific themes, it's impossible to ignore AI. The challenge investors face is determining the long-term value of AI companies as new versions of generative AI platforms, like GPT-6 or GPT-7, emerge. Will these companies improve or become obsolete?

I focus on companies creating more efficient processes and delivering value quickly with verticalized AI models tailored to specific industries. For example, we invested in a company optimizing the government grants process, which is traditionally labor-intensive. Some companies have reached over a million in ARR in nine months, leading to high valuations due to rapid growth. 

I was curious if there are specific customer profiles you think are either non-consensus or underserved that you would point founders to explore more.

There is a lot of focus on selling to high-level executives or using a product-led growth strategy targeting engineers and end users who then advocate for the product within the organization. 

I think some of the most critical problems are being solved by middle managers. These managers are often understaffed and looking for ways to enhance their team's capabilities and resources.

Particularly with AI resources, middle managers can significantly benefit by turning a team of three into the equivalent of a team of five or more through automation and other enhancements. This approach can be more effective than aiming for enterprise-wide agreements, which can be challenging to secure. Instead, focusing on these middle managers, who may have easier sign-off authority, can facilitate more agile, high velocity sales.

This strategy differs from traditional enterprise sales and product sales that rely on single-license purchases. For example, Cloverleaf has had some success in this area as a business development tool, targeting these middle management levels. While I can't speak for their long-term strategy, they have demonstrated the potential of this approach.

Are there any other big shifts or compelling catalysts for significant opportunities that stand out to you?

Supply chain optimization is a big area of opportunity right now. Many have been searching for the next frontier of digital transformation, moving from pen and paper to a digital future. The inefficiencies within national and global supply chains are monumental. Companies that find ways to integrate data and automation can create substantial efficiencies.

One key principle I learned from CRMs like Salesforce is "garbage in, garbage out." Creating better, more consistent, and automated inputs will drive efficiency, especially in the supply chain space, but likely in other areas as well.

This interview has been edited for length and clarity. 

Sheel’s venture wishlist:

• 🌍 Macro-Driven Growth: Regions like India and Africa are experiencing rapid innovation and economic growth, creating strong tailwinds for venture investment. 

• 🧠 AI in Mental Health: AI augmenting therapists to address the growing demand for mental health services, allowing clinicians to serve more patients effectively.

• 🚚 AI in Supply Chain: AI applications in enterprise settings, particularly in supply chain management and quality control.

• 🚗 Autonomous Driving: Autonomous driving is one of the most promising near-term AI use cases, with the potential to create billions in enterprise value.

• 📱Cross-border payments: As emerging markets grow, there’s a need for payments infrastructure that can support increasing economic activity.

Other Insights:

• 💻 Software Business Models: The per-seat software pricing model may increasingly shift to a consumption-based model as AI reduces the need for multiple seats.

• 🤖 AI Hype vs. Reality: Be cautions around current hype around AI, particularly in consumer-facing applications. Current technology may be able to deliver more tangible value in enterprise use cases.

• 📈 Public Market Concentration: The concentration of value in a small number of large companies in the public markets, particularly those benefiting from AI, poses potential risk to the broader economy.

Full Interview:

I remember when you launched Amplo in 2017. It seems like you've scaled significantly since then. Can you share more about your journey and the evolution into Collective Global? 

Yes, we’ve come a long way since launching Amplo. We’ve expanded to three core funds with about 50 companies, covering a range of industries from software to fintech to AI.

About a year ago, I teamed up with Daniel Adamson to launch Collective Global. Daniel brought expertise in GP staking, while I brought my venture experience. Our goal was to create something broader than just early-stage venture. We realized that early-stage venture is just one of many ways to access the innovation economy. So, in a way, we rebranded the entire firm under the name Collective Global.

Now, Amplo is our venture arm, and we also have Elevate, which focuses on GP staking, and Tactica, which will focus on late-stage opportunistic investing. Our vision is to build a mini-Carlyle, offering a range of investment products. It’s been a good maturation of the business, and the team has grown nicely. When I started Amplo, it was just me. Now, with Collective, we have a full team, including my co-CEO Daniel, a COO, general counsel, chief compliance officer, and a strong investing team.

That sounds like an exciting evolution. Are there any specific business models or macro trends that you find yourself particularly focused on these days?

My focus is less on specific business models and more on macro trends. One big question I have is whether the current per-seat software pricing model will exist in ten years. With AI reducing the need for many seats, I think we might see a shift towards a consumption-based model. 

But more broadly, I’m interested in where the world is heading. For example, I’m very optimistic about regions like India, where GDP is growing at 7-8%, with a lot of innovation happening. The introduction of UPI, which allows frictionless payments with no interchange fees, and Aadhar, which has collected biometric data for over a billion people, has been transformative.

These developments have enabled more people to access banking services, vote, and engage in other civic activities. The IPO market in India has opened up, tech companies are going public, and the options trading market there is now larger than in the U.S. I’m also bullish on Africa, which, though not a single country, is seeing the emergence of cross-border businesses that are targeting large and rapidly growing markets.

Conversely, I’m cautious about regions where populations are decreasing, growth is stagnating, and fiscal situations are becoming untenable. As a venture investor, I’m looking for market opportunities where you can build large companies from nothing, and I believe macroeconomic factors are increasingly driving these opportunities. In the U.S., despite some challenges, I’m still optimistic because of the strong pace of innovation. However, I do worry that we sometimes get in our own way with policies that could stifle progress, like restrictions on skilled immigration.

Are there any other significant trends or sectors you’re particularly excited about right now?

AI is a hot topic, but I’m a bit skeptical of the current hype. I think the real winners right now are the infrastructure providers like Nvidia and the end consumers. The businesses in between might not fare as well. 

That said, I’m particularly interested in AI use cases that can generate real enterprise value. One area I’m focused on is mental health. There’s a significant shortage of therapists, and AI could help augment their work, allowing them to serve more patients effectively. For example, AI could check in with patients between sessions, freeing up therapists to see more people without compromising care quality.

Another area is cross-border payments, especially in emerging markets where mobile phone adoption has outpaced other technologies. As these markets grow, there’s a need for payments infrastructure that can support the increasing economic activity. 

I’m also spending more time looking at the public markets. This year, we’ve seen a small number of companies, particularly those benefiting from AI, drive most of the market gains. I’m concerned about the risks of such concentration.

It’s interesting to hear your thoughts on AI. Are there any other specific AI use cases or industries where you see significant potential?

We have a company called Axion Ray that exemplifies another thesis of ours: the potential for AI in enterprise settings, particularly in supply chain management and quality control. AI can help businesses run simulations, detect flaws in complex supply chains, and ultimately save millions, if not billions, of dollars. 

I also believe autonomous driving could be one of the most valuable AI applications in the near term. Companies like Tesla are already seeing significant advancements, and I think the technology is closer to being mainstream than many people realize.  We are investors in Helm.ai and their incredible full stack AI software could help all other automakers catch up. It could soon be safer to have autonomous vehicles on the road than human drivers.

Do you have any startup ideas or business concepts that you wish existed but haven’t seen yet?

I have a few ideas, particularly around aging and services for the elderly, given the stagnating population growth in many parts of the world. But let me get back to you with more details on that.

What about customer profiles or problems that you think are worth exploring for founders looking to start new businesses?

There are two types of businesses that I think work really well. One is consumer-focused businesses that bring massive value to millions of users, like Robinhood did with its beautiful UI and brand. 

The other is businesses that sell to large enterprises with substantial contracts. Where companies often struggle is in the middle—selling to SMBs or targeting a small subset of consumers. Those businesses can be harder to scale. So, if the goal is to build something big, it’s easier to focus on either end of the spectrum.

This interview has been edited for length and clarity. 

Dan’s venture wishlist:

• 🏦 Alternative Asset Managers and Other Next Gen Financial Services: The next generation of financial institutions.

• 🏢 PE & Insurance: Owning a piece of PE/insurance firms.

• 🎵 Music pricing: Digital distribution and data-driven finance business models that harness the music industry's changing value chain.

• 💊 Pharmacological super cycles: Financial services built around massive disruptive changes, like changes to health insurance caused by shifting life expectancy and healthcare needs heralded by GLP-1 drugs.

• 🧓 Aging market: Companies addressing the needs of an aging population by developing products and services tailored to the elderly.

Other insights:

• 🧑‍💻 Beyond pure software: Pure software is overinvested.

• 🕶️ Venture blind spots: The traditional venture funding model of raising money every couple years introduces existential financing risk that requires even higher returns, leading to false consensus on what can be “venture scale.”

• 📈 Compounding growth + capital efficiency: Businesses that can grow at target hurdle rates of 25-30% while maintaining low existential risk — by broadening what is considered “venture investable.”

  ---

Full interview

Is there a type of company or a particular idea that you'd love to fund?

As a firm, we look at the broader economy for which there is massive disruptive change and think about how we build financial services businesses around those changes. 

In general, my energy is less in software and more in the use of software to create the next generation of great financial institutions. My general view is that software is becoming less valuable. I think it's becoming much more commoditized. Plus, there are so many people trying to invest in software today. It's a very crowded space. Why try to compete with them when we can do our own thing that nobody else is really working on? 

So what are you thinking about these days? 

The equity value of a bank, insurance company, hedge fund, or private equity firm is quite high. You can compound equity at very high rates of return for many years on a very low dilution trajectory if you own the management company of a hedge fund, because the equity value of a hedge fund is quite high.

My team and I have spent some time studying these kinds of alternative asset management platforms that are publicly listed. And it's fascinating to study these business models. Can you deliver venture scale returns? The answer is unequivocally yes. That's one thing that's certainly occupying my mind right now.

Just as an example, the second largest private equity firm in Europe, which is called CVC Capital, went public in Amsterdam recently. And basically until relatively late, it was profitable since day one. And so part of the line of thinking here while everyone is trying to sell software to private equity firms, maybe venture capital firms should help start private equity firms and own a piece of the private equity firm itself.

Conventional wisdom would be that they don't scale fast enough, but they are nice, cash flowing businesses once you get them to scale.

How fast is fast enough? One of the things that I've thought about is a target IRR of 25-30% net of dilution on a net basis.

And really what you want is to fund businesses that can grow at this target hurdle rate, 25- 30%, whatever it may end up being, and can do so for many years and have relatively low existential risk associated with them.

That's the thing that a lot of LPs and GPs don't fully internalize. LPs have very long term capital, sometimes permanent capital, and they want VC to take a long duration.

But the way venture capitalists operate is they invest in a company, and two or three years down the road, the company needs to raise more money. And then two or three more years down, the company needs to raise more money and so on and so forth.

This doesn't make a ton of sense because each time you have to raise money, you're introducing existential financing risk. And oftentimes that existential financing risk is not the fault of the company, but for other exogenous reasons.

One of the things I think a lot about is: is it better to profitably double every year and have zero existential risk, or is it better to burn a lot of cash and 3x, knowing that every other year you take on a fairly substantial amount of existential risk?

In asset management business, your customers are investors, admittedly a different kind of investor than you might raise money from. Does that amount to the same thing that you're exposed to the same underlying risk of investor sentiment?

Well, not in the sense that in an asset management business, especially an asset management business with a long duration capital, you can be confident that the management fee stream will be there for many years. 

What are other trends you’re exploring at Deciens? 

My colleague Ishan has been very focused on the question of music and the changing value chain in the music ecosystem, especially around how music is financed, securitized, collateralized, and the payments associated therein. There’s massive disruptive change because of the role of digital distribution. If I can now watch my favorite artists on YouTube, why do you need a record label?

Is digital distribution a “why now?” Recently we’re seeing trends in establishing higher payout levels for streaming, which makes it more attractive. The changing interest rate environment also affects how people think about royalty streams and securitization. I'm not sure if that's a tailwind or a headwind. What’s your opinion? 

Ishan's really the expert here, so I don't want to overstep my own knowledge. My general view is that artists do not want to sell their intellectual property. They do it only because working with a record label generally requires them to do so.  

The second is digital distribution. 

The third is the use of data. Historically, the way that record labels underwrite artists is using something called A&R. And A&R is, broadly speaking, the taste of certain individuals. But using data, you can actually produce highly predictive forecasts of the decay curves of music over time, and finance artists based on the statistically accurate models of how their music will perform.

You can go from a non-data-driven ownership model, which uses something like an equity-like structure to a data-driven, debt-like structure.

We have a very important company doing exactly this called beatBread, which is quite a scaled player now. And Ishan's been working with them since they were basically two guys in the PowerPoint deck. And that's an incredible journey to watch, and I'm very thankful for Ishan's advocacy and work on that for sure.

What other themes are you exploring? What other opportunities are you spotting?

We have also been spending more time at the intersection of financial services and healthcare, especially around the impact of massive changes that are occurring. 

My general view is that I think we are going to enter a pharmacological super cycle. 

Innovation comes in waves. Then, there are years and years and years of, what you would call basic research to come to kind of like a tipping point. And then, the innovation really speeds up because it kind of builds on years and years of this research.

And so if you think that we're starting to enter a massive super cycle based around the GLP-1 drugs, that's going to be massive. There's a world in which literally every adult takes one once a week or once a month. And you may know that there's quite a bit of evidence that GLP-1s are effective on Alzheimer's and Parkinson's. It's effective on cardiac diseases. It's obviously effective on various metabolic conditions. It's surprisingly effective at helping people manage substance abuse and so on and so forth.

So if you think we're about to enter a pharmacological supercycle, that's going to have some real impact on many, it's going to have real knock on effects. 

What will this do to life insurance? And what opportunity does this create? With all these advanced biologic techniques for drug development and what is that going to do to the financial services industry? What is that going to do to the morbidity and mortality tables? And what is the opportunity in the insurance industry to play on this pharmacological supercycle?

So if lifespan increases, how does that change the health and life insurance industry? 

Well, in this case, it would be life insurance. Health insurance in the US is actually not insurance in the traditional sense of the word. It’s a misnomer that we call health insurance “insurance.” 

It's a bundle of things, including discounts and access. 

There's not the collective risk aspect of it. One way to think about it would be: if you have high risk groups, and if you use drugs, you become a low risk group. 

Can you charge the high risk group that is now low risk, medium risk pricing and capture super premium economics on that? How do you ensure compliance with the drug regime and so on and so forth?

You're talking about combining underwriting life insurance with a specific pharma regime?

If we're going to go through a pharmacological supercycle where obesity becomes something that is easily medically treatable through the use of these drugs, then there are lots of people who were “high risk” that will no longer be high risk. Is there an opportunity to create an insurance company that plays on that trend?

Conversely, I was saying in this, if we're going through a massive pharmacological super cycle where drug, where the next generation of biologic drugs makes massive changes to morbidity and mortality, that will have some very material knock on effects in financial services and in the economy broadly We should be thinking hard about what those are likely to be and how to invest against that trend.

Walmart has already said that they believe it will dramatically reduce the total addressable market of food sales in the United States.

This is the CFO of Walmart. We're not talking about some venture capitalist on Sandhill Road, spouting his mouth off. Walmart has already seen a reduction in food sales that they attribute to the rise of these drugs. You should go listen to their earnings call about it.

One final question for you. Are there any specific customer profiles or problems that you would want to point founders towards that we haven't touched on?

We tend to look for areas of great change. And within that, that is because we observe that change creates opportunity.

One huge change is the rapidly aging population in the United States. I see so many entrepreneurs targeting teenagers — and teenagers are great! But you know who’s better? Old people. They have money. 

I wonder why everyone focuses on teenagers over the elderly. 

Is it because they think teenagers are more likely to be early adopters and are easy to find initial customers? Is it because they themselves have been teenagers before? 

I don't have a great answer for you. I think what you mentioned is a valid theory. Another could be that they have teenagers at home. So, they see the problem up close and personal in their daily lives. 

As more people have to engage in kind of taking care of or being responsible for elderly relatives and that, there is a massive opportunity to build products and services for the retirees, for the elderly and their caregivers.

We've done some investing in this space. Good results so far, but I think it is a customer profile which is massively under explored.

This interview has been edited for length and clarity.