AI agents look magical in demos and fragile in production. Tool failures, looping plans, and silent policy violations are the usual culprits.
Constrain the action space
Give agents a small, well-tested tool set with typed inputs. Broad tool catalogs increase accidental damage and make evaluation harder.
Memory with retention rules
Short-term conversation memory is not a database. Persist only what you need, encrypt sensitive fields, and expire stale context.
Guardrails before autonomy
Require confirmation for high-impact actions, log every tool call, and enforce allowlists for destinations and data classes.
Evaluate continuously
Ship with golden-task suites and regression checks on prompts. Without evaluation, every model upgrade is a production gamble.