Practical Guide to AI Agent Architecture: Constraints in Code, Not Prompts

bigdata · x · 2026-08-26

This article outlines nine practical rules for building AI agents that perform real work. Key takeaways include:

Put hard constraints in software, not prompts: Models excel at flexible reasoning, while ordinary software handles state, permissions, and predictable control flow. Let the model handle ambiguity, but delegate calculations, permissions, and fact-checking to trusted code to prevent unacceptable failures.
Grant only the necessary autonomy: Avoid giving agents more autonomy than the job requires, as excess autonomy creates unnecessary risks.

The piece emphasizes that reliable systems must explicitly delineate the boundaries between model capabilities and traditional software logic.

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