AI is being such a big reset in how companies are run that past success could end up being a liability.
Mike Volpi, a partner at Index Ventures and former chief strategy officer at Cisco — where he oversaw more than 70 acquisitions in under five years — believes we are in the middle of a genuine generational break in how venture capital and entrepreneurship work. And his warning isn’t about technology — it’s about the danger of having got things right before.
There is, Volpi says, a big generational shift right now between classic entrepreneurship, classic venture, and this new generation of AI venture, and some people are more predisposed to it than others. The last thing he would add — and the thing he considers most important — is to be very careful about past success. This is very true for individuals, and it’s also very true for firms. The more success a firm has had, the more — to use an AI term — reinforcement learning there is of how things were done.
And if the world shifts to a place where things are done a little bit differently, that reinforcement could be applied very incorrectly.
Volpi ties this directly to the struggles of operators who built careers in the SaaS era. He thinks this past-success reinforcement loop explains why so many executives from pre-AI SaaS find it genuinely difficult to adapt — because they’ve learned a whole set of things that don’t make sense anymore. The whole concept of software is changing.
The economic logic he lays out is precise. Most venture capital firms are focused on making money on software companies, and that foundation is based on the idea that software is complicated, expensive, and takes a long time to build. It costs very little to make lots of it, but it costs a lot to make the first edition of it. So you end up in a world of high fixed costs, which you need to sell to as many people as possible. Every business model starts looking like that. Then you move into an AI era, which takes the cost of making software way down. You’re completely shifting the core assumptions on how a business is built.
The implications of that shift are hard to overstate. The SaaS model — spreading the enormous cost of building software across a large enough user base to make the unit economics work — was the governing logic of an entire generation of startups and the venture funds that backed them. If that cost collapses, so does the rationale for a lot of what the industry has been doing.
Volpi isn’t alone in seeing this. Satya Nadella has argued that SaaS applications “will collapse” in the AI agent era, as the business logic that made these platforms valuable migrates to an AI layer sitting above them. Dario Amodei has warned that the SaaS model of amortizing software-building costs across millions of users could soon be obsolete. And Naval Ravikant has gone further still, declaring that pure software businesses are now uninvestable — the moat of being able to build software others can’t has simply closed. The market appears to agree, with software stocks underperforming broader indexes even as the rest of the Nasdaq holds up. What Volpi adds to this conversation is the human dimension: the difficulty isn’t just structural, it’s cognitive. Firms and executives that succeeded by internalizing the old rules have the most to unlearn. The reinforcement loop that built their careers is the same one now working against them.