Cooper Saye joins OpenAI to work on recursive self-improvement evaluations, signaling AI safety’s new frontier

Cooper Saye, a former engineer at Jane Street and fintech company Ramp, joined OpenAI on July 31, 2026, as a Member of Technical Staff. His focus: recursive self-improvement evaluations.

What RSI evaluations actually mean

OpenAI is actively recruiting for roles in Recursive Self-Improvement Safety, with job postings based in San Francisco that specifically mention designing experiments and conducting evaluations to mitigate potential risks.

In English: OpenAI is building a team whose entire job is to figure out whether AI systems are starting to accelerate their own research capabilities, and if so, whether humans can still maintain control over the process.

Saye’s announcement on X highlighted his enthusiasm for contributing to efforts aimed at accelerating AI research through RSI evals. He also noted that the team at OpenAI is hiring for roles specifically focused on measuring progress toward RSI.

Loss of control is the specific risk category that these evaluations are designed to address. When an AI system can improve its own code, training methods, or architecture without human intervention, the traditional safety playbook, where humans review and approve each iteration, starts to break down.

The industry-wide pivot to RSI safety

Saye’s hire isn’t happening in a vacuum. OpenAI, Anthropic, Google DeepMind, and Meta have all been increasingly vocal about the urgent need for safety mechanisms in response to RSI risks. Industry letters have called for governance mechanisms capable of moderating AI development in response to the specific dangers posed by recursive self-improvement.

Saye’s background makes him an interesting pick for this kind of work. Jane Street is one of the most quantitatively rigorous trading firms in the world. His time at Ramp, a corporate card and expense management platform, adds a different dimension in building systems that are reliable at scale while managing risk in real time.

What this means for investors watching AI

There are no cryptocurrency assets directly associated with this development. The growing investment in RSI safety roles signals that major AI labs are preparing for a world where AI systems can meaningfully contribute to their own development cycle.

For crypto markets specifically, the AI-agent narrative has been one of the most durable themes since 2024. Tokens associated with AI infrastructure, decentralized compute, and autonomous agent frameworks have attracted significant speculative capital. The formalization of RSI as a safety discipline at OpenAI could reshape how investors evaluate the feasibility and timeline of autonomous AI systems.

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