How Defy Owns 17% of Their Best Companies Without Following On Every Round

Neil spent 12 years at General Catalyst, watching a firm grow from a tight Cambridge partnership into a global platform. He saw the strengths of both models up close. But when he left to co-found Defy a decade ago, he was making a deliberate argument: that for early-stage venture, a small, co-located partnership that argues through every deal together will outperform one built around process and investment committees.

At Defy, all investment professionals work out of the same office four or five days a week. Partner meetings are called when there is something worth deciding, not on a fixed calendar. If a compelling deal appears on a Monday, the team convenes by Wednesday rather than waiting for the next scheduled slot. Neil is quick to note that this does not mean large platforms make bad decisions. It means the two models are optimized for different outcomes, and Defy has chosen to optimize for fund-level multiples at the early stage.

A significant reason speed is less of a competitive weapon than it might appear: roughly 75 percent of Defy's deal flow is proprietary. These are founders Neil and his partners have known for years, ideas they may have helped conceive, relationships built before a financing process ever began. When three quarters of your portfolio was never shopped to market, the pressure to move in 12 hours largely disappears.

Neil traces his investment framework back to two companies he was personally involved in building from scratch. The first was Vitrue, a social media marketing platform he helped conceive at General Catalyst in the early days of Facebook and Myspace. The opportunity was clear: brands had no real way to engage audiences on social platforms, and the data those platforms held was being left entirely unused.

Neil and a colleague wrote a business plan, found a CEO named Reggie Bradford, and made one of his first investments at GC. Within a few years, Vitrue grew revenue roughly 200x and was eventually acquired, returning nine figures to General Catalyst.

The second story involves Brian Lee, a serial founder Neil had backed previously through his board seat at The Honest Company. At the beginning of Defy's Fund 2, before the AI wave that followed ChatGPT, Brian called with an idea: use AI to grade collectibles. Today, that business, Arena Club, built in partnership with Derek Jeter, has scaled to nine figures in revenue. There was no revenue for the first couple of years. Defy invested anyway, based entirely on the person making the call.

Neil calls this the third bucket. Markets matter. Preparation matters. But the quality of the founder is the variable that most reliably separates outcomes. At Defy, that conviction runs deep enough that partners attend founders' weddings, show up at their kids' sports games, and consider them genuine friends.

In 2019, Defy backed a team of two former Special Forces Marines and two Stanford engineers building unmanned drone technology for defense applications. The original thesis was a traditional venture bet: a small check, a meaningful ownership stake, a hardware and software company to grow.

Within a year, the founder called to say he did not need more capital. Government grants were funding the business. Contracts were coming in, so Defy pivoted the relationship. Instead of investing more in the original company, Reveal, they built something alongside it: Fairwater Labs, a platform to create and incubate new defense and dual-use technology companies from scratch.

That decision was made when US defense was widely considered uninvestable by venture. One customer, slow procurement cycles, a Democratic administration. Neil heard all the objections. He invested anyway. Fairwater Labs has now created ten companies in that sector. Reveal itself has grown into what Neil describes as a multi-business-line platform selling to the US government, comparable in structure to Andril.

The lesson Neil draws from this is not about defense specifically. It is about being willing to let a relationship evolve further than your original underwriting ever anticipated, and being present enough to spot where that evolution is leading.

Defy launched with a thesis of 20 to 25 portfolio companies per fund, distributed across seed and early-A investments, with the explicit belief that strong founder selection could produce consistent multiples without relying on a single power-law outlier.

Two things have changed that math significantly.

First, AI has compressed the capital required to start a company. Defy now writes initial checks as small as one to two million dollars, enough to cover early operating costs, with the intention of following on quickly with a larger commitment once the relationship is established. Because companies can reach profitability faster and raise later rounds at dramatically higher valuations, the traditional Series A and B rounds have become less common in Defy's portfolio. What used to be a bridge round is now often the last institutional check before a large growth-stage raise. This has pushed Fund 3 toward 30 or more core investments rather than 25.

Second, the platform model has added a layer of complexity to the portfolio count. Fund 2's US defense platform, Fairwater Labs, has already created 10 companies and is on track for 20. Fund 3 has two platform bets: one building crypto rails and infrastructure, another focused on second-order effects of AI over a five-year horizon. Each platform will create 10 to 15 additional companies. That brings Fund 2's total portfolio to roughly 45 companies, well beyond the original target.

Neil is direct that this expansion was not planned but has proven to be an advantage: creation-stage investing at the inception of a company allows Defy to set ownership levels from the ground up.

Defy made its largest capital call on April 1, 2020 when venture capital investment was down roughly 80 percent industry-wide. The firm called its portfolio companies, offered bridge capital, and bought secondary shares from founders who needed personal liquidity, employees who were leaving, and investors who had lost conviction. Not one LP called to complain.

Neil attributes this to the LP base Defy has cultivated: 100 percent US-based, roughly 90 percent endowments and nonprofit foundations. These are among the longest-horizon investors in the world. They do not chase quarterly marks. They want multi-decade compounding. Defy has grown from 17 LPs in Fund 1 to 25 in Fund 3 by adding two or three institutions per fund rather than broadening to a larger, more heterogeneous base.

The same contrarian logic applies to sector timing. Defy started the crypto infrastructure platform when Bitcoin had crashed to $15,000 and the industry was in free fall. It began investing in US defense venture when the political and market consensus was that it was unworkable. And it began investing in AI logistics, test proctoring, and collectibles grading years before large language models made AI a household conversation.

Neil points to an anecdote from his Harvard Business School graduation in 2000. Half his class left for San Francisco to start companies at the peak of the dot-com bubble. He took it as a signal to do the opposite. That instinct has become a core part of how Defy selects both sectors and entry timing.

One of the more revealing statistics Neil shares: Defy owns an average of 17 percent across its seven highest-marked portfolio companies. He argues that no early-stage manager in the country can match that number without relying on mid-market private equity mechanics.

How they get there:

The common thread is conviction. Neil is explicit that Defy does not use these mechanisms in every company. Where conviction is absent, the strategies do not apply. But where it exists, they pursue ownership aggressively because, as he puts it, the marginal dollar of ownership at the early stage is the highest-returning dollar in the portfolio.

Neil opens this section with a joke and then gets direct: the patterns visible in hindsight are consistent and painful.

The most reliable predictor of a bad outcome is an integrity signal early in the relationship. An inconsistency in diligence. A founder who is not fully forthright. Something small enough to rationalize past. Neil's view is that you should not rationalize past it. In nearly every failed investment he has observed across General Catalyst and Defy, there was a moment where a signal was noticed and set aside. It always returned.

The second pattern is founders losing control of their own operating decisions by over-indexing on external noise. VCs who promise to invest at a future milestone and then move the goalposts. Friends and fellow founders sharing advice that is more opinion than signal. The result is founders who optimize for what they believe the market wants to see rather than for what their company actually needs. Neil's advice is to protect the levers that allow you to control your own trajectory, maintain runway, use AI to operate lean, and not spend toward a fundraising narrative you cannot sustain.

He closes with a note that Defy has backed founders whose companies did not work, and will back many of them again. Failure handled with integrity, transparency, and respect for employees and investors is not a disqualifier. How someone exits a hard situation tells Neil more about who they are than how they ran a company that was working.

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