An agent loop alternates model planning, typed tool calls, observation, and stopping. Constrain tools and permissions, validate arguments, cap steps and spend, isolate failures, record traces, and evaluate end-to-end task completion plus safety.
Make interfaces and ownership explicit; add versioning, access control, monitoring, canary rollout, rollback, and a plan for delayed labels or human review.
Get asked follow-ups live, then receive a scored report — like a real MLE interview loop.
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