LLM Integration Checklist for Product Teams Shipping to Production

Shipping an LLM feature is not a prompt contest. Production means you can explain what data the model sees, how you measure quality, and what the UI does when the model is wrong or slow.

Start with a single high-value workflow — support deflection, summarization, or a guided form — not a general assistant. Narrow scope makes evaluation possible.

Define retrieval and tool boundaries early. If the model can read customer data or call write APIs, treat that like any other privilege escalation: least access, audited logs, and human confirmation on irreversible actions.

Instrument latency and failure modes. Users forgive a slightly wrong answer less than a spinner that never resolves. Cache, stream, and degrade to deterministic UI when providers flake.

Finally, own an eval set. Ten golden tasks beat a vibe check. An AI consultant should leave you with harnesses and runbooks — not a demo that only works on Wi-Fi in the office.