When a massive investment's core premise fails early (like at Thinking Machines), the best move is to treat it like a failed seed deal. Investors should seek to wind it down, accept a small, quick loss, and redeploy the returned capital into successful ventures rather than attempting a painful turnaround.
A core part of a16z's growth fund strategy is to invest in companies the firm's early-stage team passed on. This acts as an internal "fix the mistake fund," providing a structured way to correct errors of omission and get a second chance at breakout companies.
Large, multi-stage funds can pay any price for seed rounds because the check size is immaterial to their fund's success. They view seed investments not on their own return potential, but as an option to secure pro-rata rights in future, massive growth rounds.
Sam Lessin predicts massive losses for seed VCs backing companies branded as "AI businesses." These ventures are too capital-intensive and commoditizable to generate traditional venture returns, even if they become massive. AI should be a tool, not the business model itself.
The most dangerous venture stage is the "breakout" middle ground ($500M-$2B valuations). This segment is flooded with capital, leading firms to write large checks into companies that may not have durable product-market fit. This creates a high risk of capital loss, as companies are capitalized as if they are already proven winners.
Beyond product-market fit, there is "Founder-Capital Fit." Some founders thrive with infinite capital, while for others it creates a moral hazard, leading to a loss of focus and an inability to make hard choices. An investor's job is to discern which type of founder they're backing before deploying capital that could inadvertently ruin the company.
Deciding whether to invest more capital into a struggling portfolio company is a major point of conflict. The management team advocates strongly for the infusion, believing it can turn things around. However, investor experience shows that such 'bridge' rounds are rarely successful, making it a difficult decision.
The SoftBank Vision Fund's "capital as a weapon" strategy is fundamentally flawed because it creates an adverse selection machine. Companies that rely solely on massive capital infusions to win, rather than product or market advantages, are often weaker. True market leaders attract resources organically, making huge, preemptive checks a poor basis for an investment thesis.
Rather than abandoning an investment category after a failure, some VCs intentionally fund the same idea again in a new company. This strategy is not about repeating mistakes, but a high-conviction bet that the core idea was simply ahead of its time and that a change in timing or underlying technology will enable its success.
The persistent "never quit" advice is "venture capital bullshit." Since VCs can't recoup their investment, their only rational move is to encourage founders to keep trying against all odds. For founders, it's often better to quit, reset the cap table, and start fresh rather than waste years on a failing venture.
Thinking Machines Lab, founded by ex-OpenAI leaders, raised $2B pre-product. Its current struggles, including executive departures and inability to raise more funds, suggest investors are shifting focus from founder hype ('vibe founding') to concrete products and business strategies.