Cyberstarts' "Sunrise program" invests in talented founders pre-idea. They leverage their network of CISOs to identify intense, unsolved problems, pre-sell a solution sketch, and only then build the product. This demand-first approach generates an extremely high hit rate.
The firm's thesis focuses on a rare founder type: a technical expert who also deeply understands how new technologies shift human behavior. This avoids the common pitfall of building technology in search of a problem, leading to products with innate market pull.
To win the best pre-seed deals, investors should engage high-potential talent during their 'founder curious' phase, long before a formal fundraise. The real competition is guiding them toward conviction on their own timeline, not battling other VCs for a term sheet later.
Precursor Ventures makes "directional people bets" by investing smaller checks ($150-250K) in top-tier founders to fund their search for a viable business concept. This strategy prioritizes founder quality over the initial idea, recognizing that great founders can pivot to find product-market fit.
Exceptional founders like Kyle Hanselowen of Huntress identify and commit to underserved markets, such as cybersecurity for SMBs, long before they become obvious. Their success hinges on this unique market view and the personal grit to evolve and reinvent themselves as the company scales.
Instead of pitching an idea upfront, the founders first conducted broad interviews, asking security leaders for their top 5 problems. Only after identifying a recurring pain that matched their thesis did they switch to phase two: presenting a specific solution to validate its acuity and demand.
Casado argues that the market creates the company, not the other way around. He first determines if a market is viable and growing, and only then asks if the founder is the right fit for that specific market, reversing the common founder-first VC mantra.
VCs struggled with Axonius's pitch because the problem had existed for years with no solution (a "why now" issue). The founder overcame this by having the VC put him in front of Fortune 500 CISOs. When every CISO told the VC it was a top, unsolved priority, the market validation was undeniable.
By using an unsupervised machine learning model to filter thousands of teams based solely on founder profiles, a VC can significantly de-risk its pipeline. Investing in this pre-screened pool alone would yield a 24% graduation rate, far above the 14% market average, even before applying human judgment.
Cyberstarts' founder learned from his first startup, which invented CAPTCHA, that a great technology doesn't guarantee a business. He now advocates for reversing the process: find a painful market problem first, identify paying customers, and then build the solution for them.
Small, dedicated venture funds compete against large, price-insensitive firms by sourcing founders *before* they become mainstream. They find an edge in niche, high-signal communities like the Thiel Fellowship interviewing committee or curated groups of technical talent. This allows them to identify and invest in elite founders at inception, avoiding bidding wars and market noise.