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Building an agent loop
How to build the smallest controlled agent — a loop that observes state, lets the model choose a tool, executes it, incorporates the result, and stops on a designed condition — and why autonomy has to be engineered with budgets, stop states, and deterministic control rather than assumed to emerge.
Questions in this set
- What makes a system an agent?
- What are the parts of an agent loop?
- When should you use an agent instead of a workflow?
- Can we build a minimal agent?
- How does the model choose an action?
- How are observations returned to the model?
- What makes an agent stop?
- How do you prevent infinite or repeated actions?
- How should failures be handled?
- Where should deterministic code remain in control?
- How do human approvals enter the loop?
- How do you trace an agent run?
- How do you test an agent loop?
- How do you know the agent is better than a simpler design?
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