TLDR Tech / AI
Auto-Improving Software
Bedi runs an entire agent development lifecycle through five Claude Code prompts that scaffold, harden against spec, add capabilities, fix eval failures, and reconcile drift between docs, code, and config across his Agno-based platform. The Improve loop derives 8-12 probes from an agent's instructions, runs each against the live container via cURL, judges PASS or FAIL from container logs, then iterates up to five rounds picking levers like tightening rules, swapping tools, or bumping num_history_runs until probes pass, while Hill Climb runs the saved eval suite and fixes regressions in place.
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