Andrew Chen's perspective reflects a shift in consensus within the AI investment community for 2026: from "finding PMF" to "maintaining PMF," as the speed of model iteration makes "static advantages" unsustainable, akin to the brutal competition of "weekly leaderboard refreshes" in the 2010s mobile app stores.

Similar cases can be compared to NVIDIA's GPU iteration cycle from 2022 to 2026: after the release of H100, H200 followed 6 months later, and B100 appeared another 6 months later, with customers never "locking in" a single product but rather "chasing" the latest performance/cost ratio, forming the paradox of "innovation equals commoditization."

On the capital path, Chen's "continuous innovation" framework points to two types of winners: one is "vertically integrated" (like OpenAI's self-developed closed loop from GPT-3.5 to GPT-5), and the other is "application layer rapid adaptation" (like Notion and Cursor updating their model backends weekly), while companies that are "one-time integrators" will be squeezed out.

Essentially, this belongs to the "compression of innovation half-life" in technological substitution: AI reduces product advantages from a "yearly dimension" to a "weekly dimension," with the mechanism being that open-source models + API economy bring the cost of "feature replication" close to zero, and the only moat is "iteration speed that is one week faster than the market."

ABAB News · Cognitive Laws

PMF is not found; it is won back every week.
A moat is not technology; it is iteration that is one week faster than the market.
The truth of the AI era: today's advantage is tomorrow's liability.