Shipping an AI agent is more than wiring prompts to tools. Agents act, decide, and interact — which means small mistakes can cascade. Below is a compact, practical checklist you can run through before pushing an agent to production.
1) Define a narrow scope
Start small. Constrain the agent to a single well-defined task (e.g., meeting summarization, automated triage, research briefs). Narrow scope reduces unexpected behavior and simplifies testing.
2) Limit and validate tools
Expose only the tools the agent truly needs. For each tool, validate inputs and outputs and add conservative parameter limits. Treat external APIs as untrusted and sandbox them.
3) Add planning & step validation
If your agent produces a plan before acting, validate the plan steps against a whitelist. Reject or require human approval for any step that touches external systems or sensitive data.
4) Record full observability
Log every input, decision, tool call, and output. Structured logs make it far easier to debug and roll back when things go wrong.
5) Human-in-the-loop for high-risk actions
For actions with real-world impact (payments, deletes, outbound messages), require explicit human confirmation. Prefer asynchronous approval workflows over immediate automation.
6) Rate limits and backoff
Add throttles and exponential backoff for tool calls. This controls cost and prevents runaway behavior when something goes wrong.
7) Start with synthetic adversarial tests
Build a small suite of adversarial inputs and edge cases. Run these tests as part of your CI to prevent regressions when you change prompts or tools.
8) Monitor for drift and failures
Track key signals: unexpected tool error rates, confidence drops, or unusual action patterns. Alert and throttle before a minor issue becomes major.
9) Provide clear undo and audit actions
Design actions so they’re reversible or easily corrected. Keep an audit trail tying decisions to inputs, prompts, and versions.
10) Plan for safe rollbacks
Have a rollback plan that includes disabling automation, reverting prompt or model changes, and a human response playbook.
Shipping agents safely is iterative: start with conservative behavior, measure closely, and incrementally expand capabilities. If you want, I’ll convert this checklist into a short downloadable checklist PDF, or add a companion tool page that runs basic preflight checks for your agent deployments.