• AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
• grounding — Tying a model's answers to checkable sources — retrieved documents, live data, tool results — instead of letting it answer from memory alone.

Recursive self-improvement is already producing measurable wins in narrow loops — accuracy gains, architecture search, faster CUDA kernels — which is the concrete evidence base behind claims about automating research.

• videoHow to Generate Mergeable Code with a Context Engine — Peter Werry, Unblocked
• videoFinOps for AI Agents: Who Spent All the Tokens? — Tisha Chawla & Susheem Koul, Microsoft
• videoWhat If Your Chip Design Team Moved Like a Single Body? — Abduallah Mohamed, AIDAChip
• videoCoding Agents Don't Scale Themselves. Neither Do Your Teams. — Patrick Debois, Tessl

• articleField Report: AI Coding Agents in Scientific Computingopenai.com
• articleHow We Built Our Multi-Agent Research SystemAnthropic
• articleReal AI Agents and Real WorkEthan Mollick

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