With GPT‑6 Astra and GPT‑6.1 Sol, Codex, and Daybreak for cybersecurity, this AI lab builds agents that focus for days and improve with use.

Every company has its own workflows, tools, edge cases, and definitions of success. ⁠(opens in a new window)Third Moment Research⁠(opens in a new window) believes the best agents should be really good at that specific work and should improve their capabilities the more they’re used.

The company is building a self-improving AI system around that idea, using OpenAI’s latest models to understand agent behavior, identify recurring weaknesses, and automatically create thousands of synthetic scenarios around those problems. The team uses those scenarios to improve agents, repeating the process as new issues emerge.

Codex, GPT‑6 Astra, GPT‑6 Sol, and GPT‑6.1 Sol support the system’s research and computational work, enabling Third Moment to run 10,000 agents at once on investigations lasting 36-48 hours. The company also uses Daybreak to test the security of the environments where agents work.

One of Third Moment’s early applications is in the field of quantitative finance given the clear measure of success. This domain provides a concrete setting to study how agents work and where they struggle. The team uses Codex to find and address problems in the research environment.

In one instance, it used Codex with GPT‑5.6, the latest GPT model at the time, to analyze thousands of recorded simulation trajectories (the agents’ actions and the environment’s responses) alongside timestamps and the codebase.

Codex uncovered a bottleneck: backtesting a trading strategy across a year of order-level US equity data took several hours.

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