๐๐ด๐ฒ๐ป๐ ๐๐ป๐ด๐ถ๐ป๐ฒ๐ฒ๐ฟ๐ถ๐ป๐ด ๐๐ผ๐ฟ ๐๐
AI agents change how you build software. Engineering teams now use agents to write and test code. To do this well, you need agent engineering. This means structuring your codebase for AI.
AI agents fail when context is missing. They need a clear environment to work. Follow these four steps to prepare your repo:
- Create an AGENTS.md file. Tell the agent how to run tests and your coding rules.
- Build a fast test suite. Agents need quick feedback to fix errors.
- Use the STAR format for tasks. Define scope, tests, artifacts, and rules.
- Use sandboxes. Run agents in isolated containers to keep production safe.
The best teams treat agents as full contributors. They do not use them as autocomplete tools. This approach increases speed.
Pick the right tools:
- OpenAI Codex for general tasks.
- Claude Code for refactoring.
- E2B for secure sandboxes.
Start small this week. Write one AGENTS.md file. Give an agent one specific task. Measure the result.
Source: https://dev.to/onsen/harness-engineering-leveraging-codex-in-an-agent-first-world-14mo Optional learning community: https://t.me/GyaanSetuAi