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Auto-Improving Software

Auto-Improving Software

AI X
Ashpreet Bedi runs full agent dev cycles through five Claude Code prompts that auto-test with probes and self-heal eval failures.
What: Bedi's workflow uses five Claude Code prompts to scaffold, harden, and improve agents on the Agno platform. The Improve loop generates 8-12 test probes from agent instructions, runs them via cURL against live containers, judges pass/fail from logs, then iterates up to five rounds adjusting rules, tools, or parameters. Hill Climb runs saved eval suites and fixes regressions in place.
Why it matters: Shows Claude Code evolving from coding assistant into a full dev environment with autonomous iteration and validation loops, blurring the line between human-guided and self-directed software improvement.
Decoder
  • Agno: Platform mentioned for agent development (specific details unavailable from source)
  • num_history_runs: Parameter adjusted during improvement iterations as one of the optimization 'levers'
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