How to implement autonomous testing harness that improves itself over time

How to implement autonomous testing harness that improves itself over time

This task can be performed using Autoagent

Autoagent: autonomous harness engineering for smarter, faster testing

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AutoAgent is an open-source framework for autonomous harness engineering where a meta-agent rewrites an LLM agent’s harness, runs Harbor benchmarks, and hill-climbs on scores. You define the loop in program.md and let it iteratively optimize prompts, tools, and orchestration.

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What to expect from an ideal product

  1. AutoAgent creates a meta-agent that automatically rewrites and improves your testing setup without manual intervention
  2. The framework runs Harbor benchmarks continuously and uses hill-climbing algorithms to boost performance scores over multiple iterations
  3. You simply define your testing loop in a program.md file and the system handles all the behind-the-scenes optimization work
  4. The tool fine-tunes prompts, adjusts available tools, and reorganizes workflow steps based on real performance data
  5. Each testing cycle feeds results back into the system, creating a self-improving harness that gets smarter with every run

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