Has Venture Capital Mistaken Speed for Progress?

Since joining Glilot, the question I hear most often has nothing to do with AI itself – it has to do with time. LPs ask whether exits will happen sooner. GPs debate whether holding periods will compress. Founders wonder whether AI lets companies scale and get acquired years earlier than before.

It’s a fair question. Diligence that once took months can now take weeks, and capital moves faster than it used to. But I’d frame the real question differently: has the speed of investing changed our expectations more than it’s changed the underlying work of building great companies? Sitting between LPs who fund our conviction and GPs who act on it, my answer, after many of these conversations, is yes.

What AI Has Actually Changed

AI has genuinely upgraded venture’s operating model. Founders build with remarkable efficiency; small teams now do what once required entire engineering organizations. Investors synthesize market research in minutes and evaluate competitive landscapes at a scale that would have been impossible a few years ago. Fundraising has shifted too – companies often arrive at first meetings with more polished products and clearer data, though this varies by sector and stage. On the LP side, reporting is faster, and questions that once took a week of pulling data can often get answered in an afternoon.

That’s really good. But it carries a risk. In our enthusiasm for faster ways of working, we can start assuming the outcomes themselves should arrive faster too. AI has compressed many of the activities surrounding venture investing without rewriting the mechanics of building businesses that endure. Confusing operational speed with value creation is one of the more subtle risks facing our industry right now.

What It Hasn’t
Venture has always run on asymmetry – a handful of exceptional investments can define a fund, and finding them has always required technical insight, conviction, and patience. AI strengthens those capabilities, but the qualities that separate extraordinary companies from merely good ones are still resistant to automation.

Enduring companies are built through thousands of decisions about product, hiring, customers, pricing, and execution that compound quietly, long before the market notices. AI changes how quickly founders reach each decision. It doesn’t change how long it takes good decisions to add up to an obviously great company.

Cybersecurity makes this vivid. It’s one of the fastest-moving sectors in tech, yet the process by which great cybersecurity companies become trusted partners to enterprises hasn’t sped up nearly as much. Large organizations still evaluate vendors carefully, and mission-critical infrastructure still depends on confidence that takes time to earn.

The same pattern holds more broadly: many companies now reach product-market fit faster than a decade ago, but becoming genuinely indispensable to customers tends to stay a long game. The companies that define categories rarely do so because they moved fastest in year one – more often it’s because they kept making better decisions than competitors, year after year.

Friction vs. Judgment

This is where the conversation inside venture is starting to shift. We increasingly celebrate speed as if it were the objective itself: how quickly diligence finishes, how fast capital deploys, how soon companies scale. These are useful questions, but not the most important ones.

Venture has generally rewarded firms not for the fastest decisions, but for the right ones. Faster diligence is valuable because it can lead to a better decision, not because it finishes sooner. AI-assisted sourcing matters when it surfaces founders who’d otherwise be missed, not just more of them.

What This Means for Founders, GPs, and LPs

For founders, there’s never been a better time to build – but the same tools are available to everyone, so speed alone is becoming less of a differentiator. The edge is shifting to what AI can’t replicate: customer understanding, technical originality, resilience, and the ability to earn trust over time.

For GPs, the logic is similar internally. AI should free up time for the work that actually compounds returns: understanding founders, evaluating technical differentiation, and helping portfolio companies through inflection points. The best investors have never been distinguished by how fast they gather information, but by how well they interpret it.

For LPs, this argues for a different set of diligence questions. Rather than asking how much AI has sped up a manager’s process, it’s more useful to ask how AI has improved the quality of their decisions, and whether the firm has a repeatable way of identifying exceptional founders. Speed alone can reward the wrong behavior – it’s possible to move fast and still make worse decisions. In my own conversations with LPs, the ones I particularly value don’t ask only about our impressive speed; they also ask about our conviction, and whether we can defend it years later.

The Discipline of “Not Yet”

The best firms should use every tool that makes them genuinely faster: admin, research, internal process, portfolio support. But that efficiency shouldn’t reduce the rigor applied to investment decisions, or rush an exit before a business has reached its potential. Some of the most successful venture-backed companies got there not by pursuing the earliest possible liquidity, but by continuing to build and pivot long after they had the option to stop.

The View from the IR Desk

Working in investor relations puts me between institutional investors and venture managers – one side focused on distributions, the other on building extraordinary companies. Both are right. The job isn’t choosing one perspective over the other; it’s resisting the temptation to assume that because everything moves faster, value creation does too.

My conversations with LPs are rarely just about performance. More often they’re about conviction and repeatability, and about how technology is changing not just the companies we invest in, but how we invest. I’ve come to think that’s what IR is really for – translating the realities of company-building to investors, and bringing the priorities of institutional capital back into the venture ecosystem.

AI will keep reshaping venture capital in ways we can’t fully predict. Some of those changes will make us faster; the best will make us smarter. The firms that define the next decade will likely be the ones that understand the difference – using technology to remove friction, not judgment, while holding onto what has always produced exceptional outcomes: intellectual honesty, disciplined decision-making, and real partnership with LPs and founders alike.