Redpoint Ventures' Erica Brescia describes a shift in their investment thesis for the AI era. They are now more likely to back young, "high-velocity" founders who "run through walls to win" over those with traditional domain expertise. Sheer speed, storytelling, and determination are becoming more critical selection criteria.

Due to the nascent and highly specialized nature of AI, VCs find that traditional expert networks are no longer effective for diligence. Instead, they must rely on curated personal networks of deep specialists who can genuinely assess new technologies and teams.

The firm's strategy isn't to back every foundation model. It centers on identifying singular talents whose past work demonstrates a unique ability to achieve foundational breakthroughs. The belief is that in the current AI landscape, a few specific individuals can move the entire field forward.

Benchmark's successful AI investments (e.g., Sierra, Langchain) weren't the result of a top-down thematic strategy. Instead, their founder-centric approach led them to back exceptional individuals, which organically resulted in a diverse portfolio across the AI stack before it was obvious.

Unlike prior tech waves where founders aimed to build companies, many top AI founders are singularly focused on achieving AGI. This unified "North Star" creates a unique tension between long-term research and near-term product goals, leading to unconventional founder and company dynamics.

With AI tools enabling anyone to build a product, technical execution is no longer a reliable signal for VCs. This creates a rise in "grifters," forcing investors to filter for deeper traits like authentic obsession, high learning velocity, and a compelling "why" behind their mission.

Benchmark's diverse AI portfolio (data centers, agents, dev tools) is not the result of a top-down, thematic strategy. Their "entrepreneur out" model focuses on backing exceptional founders first, which often leads them to invest in nascent categories before they become widely recognized.

Ilya Sutskever's new company, focused on fundamental AI research, is attracting growth-stage capital for a high-risk, venture-style bet. This model—allocating massive funds to exploratory research with paradigm-shifting potential—blurs the lines between traditional venture and growth equity investing.

The investment thesis for Harmonic AI was twofold: backing Vlad Tenev, a proven founder who is still rapidly learning and improving, and supporting a differentiated strategy focused on reinforcement learning for mathematics, which sidestepped the costly race for general-purpose AI models.