The Correct Way to Build and Manage AI Agents | Jared Zoneraich
Why better agents need fewer rules, the right tools, and their own tests, plus how to set up a manager agent to direct 10 cloud agents at once.
TL;DR
- Teams often overbuild their first AI agents by adding too many rules.
- Simple prompts, better tools, and self-testing are key to effective AI agents.
- Giving the model room to 'cook' with clear intent and constraints is more effective than deterministic instructions.
- Tool engineering, which allows agents to search code, read logs, run tests, and inspect changes, is crucial.
- Building evaluation metrics ('evals') after shipping an agent can be more practical.
- Cloud agents can perform tasks that local agents cannot, offering greater capabilities.
- One agent can be designed to manage and direct other agents.
- A demo showed one agent launching and managing a team of 10 cloud agents.
- Agents can prove their work before human review.
- Ideal tasks for agent teams include breaking large migrations into independent slices for parallel processing.