Recently, I spent some time with friends where we ended up talking about career growth. One of whom was at a standstill of which opportunities to pursue if at all. But another of whom offered advice through a pair of interesting lens. One I felt interesting enough to reshare.
When you pursue a new opportunity, especially one where you have strong agency and potential autonomy to influence business outcomes, there are three possible outcomes during the duration of your role.
Success
Failure
And not succeeding
Do note that failure and not succeeding are not the same thing. Failure is when you aim for something and it ends in a negative outcome. Not succeeding is after doing all you that you do, the outcome is still, give or take, the status quo. You haven’t moved the needle for the better or the worse.
At a smaller company, failure is oftentimes business closure. Not succeeding is either a small outcome or the evolution of a fast-growing startup to a lifestyle business with no noticeable impact on the industry. At a larger organization, failure is actually pretty hard. It could be the closure of a department, a re-organization, and very rarely, a negative inflection point for the business. More often than not, it’s not succeeding, which is just maintaining the status quo. Naturally, success is good regardless of organization size.
Failures are seen more charitably at smaller organizations. Larger organizations magnify the echo chamber and press. But in both worlds, they’re seen as your mark on the world. Evidence that you’ve tried. Not succeeding, on the other hand, is often worse at large organizations. Why? Because your career stalls. The more ambitious you are, the worse your career stalling will impact your career. The longer you stall, the harder it is to earn back the momentum. So unfortunately, the worst outcome an ambitious individual can get is not succeeding at a large organization. Death by a thousand cuts.
And the unfortunate truth is that large organizations have a lot of inertia. “Strategy tax” in the words of Bret Taylor. Or as a very senior allocator who recently left their large organization told me: “Some of these layers (at institutions) are there to sap the courage out of your investment decisions.” And you can easily delete the word “investment” out of that sentence.
If you fail or not succeed (not bad, not good), the liability of it not working is put on you the larger the organization. So you take on the tax, burden, career stall if the bad outcomes happen. If you fail at a smaller institution, no one blames you because you took a risk and tried your best and things didn’t work out, they blame the institution.
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The views expressed on this blogpost are for informational purposes only. None of the views expressed herein constitute legal, investment, business, or tax advice. Any allusions or references to funds or companies are for illustrative purposes only, and should not be relied upon as investment recommendations. Consult a professional investment advisor prior to making any investment decisions.
There’s been this term that’s been thrown around as of late. By GPs. Funnily enough, not by a single LP so far. The “AI-native” venture firm.
Somehow everyone seems to think they’re the only ones doing so. But they’re not. While not everyone approaches it in the same way—and the definitions do get muddled a little—there is a growing audience of GPs building a firm leveraging agentic tools.
So, inspired by a recent conversation with my man Arkady, here’s me offering my definition of what an AI-native VC firm is. It’s a set of workflows that even the large incumbents cannot replicate by adding more people to the problem, despite the fees they draw. It’s where technology is at the core of the firm, as opposed to humans. It’s where experience actually becomes an inhibitor to investment innovation. Call it the legacy tax. Or experience tax. Or as Bret Taylor puts it, the strategy tax.
In a recent Uncapped episode, Sierra‘s Bret Taylor put it this way when speaking of SaaS business models. “In these moments of big platform shifts, what were your strengths can become weaknesses. […] You start to say that ‘Well, I don’t want to just start from scratch. We’ve got all these assets. So how do we do it in a way that takes advantage of all of our assets.’ And so all of a sudden, you’re like, ‘Let’s not just build a great product. Let’s transition from this product to that product.’ […] ‘That’s our strength, we should play to our strength.’ And you start to basically make all these decisions that sound sound very clever because you’re playing to your strengths. And in practice, if the technology wave is bigger than the category, which I think the web was as an example, you end up chipping away at doing a pure play value proposition.
“It can also work with business models though. In that time, you have perpetual license software and moving to software-as-a-service, that’s a huge change for a business to make. For your customers, that goes from being CapEx to OpEx. For you as a company, it changes ratable revenue. Shantanu did this at Adobe. Very few companies can make that transition. You have to sell it differently. You have to compensate salespeople differently. Revenue recognition is different. So you have the product strategy tax. You have the business model strategy tax. You have even the incentives of sales people—there’s a strategy tax. […] All the advantages that you had, all of a sudden, become anchors that are holding you back from doing the right thing.”
But I’m probably not the only one that can see the transposition of venture models on this analogy of SaaS models. I’ve also been in a few rooms where LPs are starting to slow to halt their pacing into investing in AI companies and funds. If so many of these products can be built overnight with Opus/Cowork, Codex, Cursor, Replit, Base44, Emergent, OpenClaw (and all of its clones in the last 2 weeks) and the list goes on, how many of these application layer AI companies will be stripped of their value almost immediately. And likely, in one month’s time from writing this piece (if not within the next few weeks), the list may already be obsolete.
In fact, I was catching with my LP friend (who’s not technical) last week and he used one of the above tools to build a portfolio management tool in two hours that has more functionality than what I’ve seen from companies trying to solve the exact same problem who’ve raised up to 9-figures. And I wish I could say I was joking. He told me, “Tools for us have historically been limited by the marriage of domain expertise and technical expertise. Most of us didn’t have both. But with these tools, they solve the technical expertise part, which empowers domain experts to build their own tools. So why bother paying for any other tool that doesn’t have the same depth of data that I’ve accumulated across decades?”
Henry Ford has that line many of you are probably aware of, “If I had asked people what they wanted, they would have said faster horses.” Most investors—big and small, multi-stage and emerging, generalist and specialist, solo GP or partnerships—are building faster horses.
So an AI-native firm has to reimagine the way the venture business is done. That isn’t an AI-written memo. That’s not just an agent strapped onto a data scraper. Assume everyone at some point can discover and find every company out there. Today’s firms who claim being AI-native (in my anecdotal experience) are highly focused on sourcing. What pools of data aren’t actively being collected now that software can relentless dig into. Today’s firms aided by AI are leveraging tools to make more informed investment decisions. The picking. It still requires, for the most part, a human in the mix to make the final call. There are very, very few, arguably no one, truly leveraging AI nativity to win deals.
In venture, there used to be the classic question VCs would often ask founders: “What’s stopping Google from what you’re doing?” Now it’s “Why can’t OpenAI or Anthropic just do what you do?” Analogously, why can’t a16z or GC do what you do? Historically, the answer, if there is a good one, is tied down to:
Business model and portfolio construction, which is still a valid point if you plan to stay as a first check purist.
Or, it’s come down to the person. You have lived experience that no one else does in cybersecurity or leading healthcare systems. You have privileged relationships no one else has. You’ve built communities that are centered around you as the central node. It’s usually been a “people” answer.
But with AI-native firms, the answer must be technological. Even if large firms were empowered with the idea, why will they still fail in the technological implementation of it? Why can’t these large multi-stage funds:
… “see” the volume you do? Are you pulling data from non-obvious hubs or non-public datasets? How defensible is it in the longer term?
underwrite deals at an earlier stage like you do? Are you doing diligence at scale? How do you get the “truth” from sources that other firms powered primarily by human capital cannot?
provide the portfolio value (at scale) like you do? Do you give your portfolio companies access to the same systems you’ve built? Can they leverage your tools to empower their customers and/or talent?
provide the same liquidity opportunities to LPs at a predictable pace like you can? Not sure if agentic software will be good enough here for now, given how much humans themselves are still figuring this out. But a goalpost for some visible future.
provide their co-investors with the same value as you can? This one might be hard. There’s always the balance of what is unique to you versus unique to others. The more you share, potentially, the less of an edge you’ll have. But my stance has always been, if access to certain analyses or information will be inevitable at some point, it’s better to be the rising tide that raises all ships than the last drop of rainwater in the ocean.
provide LPs with the same depth and/or breadth of value like you do? This last one is probably not something any AI-native firm I’ve talked to is focused on, but given that all venture firms are marketplaces at the end of the day, answering this question would be extremely powerful.
I’m not saying that’s the only way to do business. That’s not the only way to invest. I’m confident that even when GPT 15.0 and “Opus” 9.4 comes out, there will still be firms that operate primarily around a core set of individuals as opposed to technologies. We have mass-produced cars, but there is still a great demand for hand-crafted luxury vehicles. The same is true for fashion and accessories. So yes, there will still be a world even if they’re not the largest players by market cap where people prefer the luxury of the human touch.
Stay up to date with the weekly cup of cognitive adventures inside venture capital and startups, as well as cataloging the history of tomorrow through the bookmarks of yesterday!
The views expressed on this blogpost are for informational purposes only. None of the views expressed herein constitute legal, investment, business, or tax advice. Any allusions or references to funds or companies are for illustrative purposes only, and should not be relied upon as investment recommendations. Consult a professional investment advisor prior to making any investment decisions.
