# The production LLM checklist: controls to verify before launch

URL: https://infro.io/blog/production-llm-checklist
Author: INFRO Editorial (https://infro.io/blog/editorial)
Publisher: INFRO
Published: 2026-08-10
Last modified: 2026-09-11
Last reviewed: 2026-09-11 (next review due 2027-03-10)
Topic: Routing and reliability
Format: Checklist

> A production LLM launch is ready when quality, reliability, data handling, security, observability, cost, rollback and ownership each have explicit evidence. A successful demo is one test case; production readiness is the system around it.

Use this as a launch review, not a reading exercise: each item should end with a link to the evidence — an evaluation run, a load-test result, a policy, a dashboard — or an explicit decision that it does not apply. Items are grouped by the team that usually owns them.

## Quality and product behavior

A demo proves the happy path. Production needs to know how often the model is wrong, what happens when it is, and whether a release made it worse.

- [ ] A versioned evaluation set drawn from real and difficult traffic, with acceptance thresholds agreed before the run.
- [ ] A regression run for every prompt, model or retrieval change, blocking release when a threshold is missed.
- [ ] Output contracts (JSON schemas, tool arguments) validated on every response, with a defined behaviour on failure.
- [ ] Grounding and citation checks where answers depend on sources.
- [ ] A human escalation path for high-impact decisions, and product copy that communicates uncertainty.

## Reliability and rollback

Provider quotas, timeouts and streaming interruptions are ordinary events at production volume. Decide the behaviour for each before it happens.

- [ ] Client and request deadlines set explicitly, not inherited from an SDK default.
- [ ] Retryable errors classified; deterministic request errors are not retried.
- [ ] Same-model failover to another provider account tested before any cross-model fallback is allowed.
- [ ] Failure injection run for a timeout, a 429, a 5xx and malformed output, with the observed behaviour recorded.
- [ ] A configuration-level rollback for model, prompt and routing changes.
- [ ] A named incident owner and communication channel.

## Security and data

Model access is a credential and a data path at the same time. Both need an owner.

- [ ] Every key has an owner, an environment, a model allowlist and a spend ceiling.
- [ ] Provider credentials live in one place; applications do not hold raw provider keys.
- [ ] A written decision on prompt and output retention, including who may read captured payloads.
- [ ] DPA and subprocessor list reviewed where your customers require it.
- [ ] Irreversible agent actions require explicit authority, separate from permission to call a model.

## Observability and economics

You should be able to answer "what happened to this request" and "where did this week's spend go" without exporting anything.

- [ ] Every request traceable by id to its model, provider, attempts, latency, token counts and estimated cost.
- [ ] Alerts on error rate, fallback rate, malformed output and latency, each with an owner.
- [ ] A cost-per-successful-task baseline for each important workload.
- [ ] Soft budget alerts and hard ceilings scoped narrowly enough that one workload cannot starve another.
- [ ] Spend attributed by project or feature, reviewed weekly with the model and prompt changes that moved it.

## Revision history

- 2026-09-11: Turned each section into a verifiable checklist, removed an unsupported control count from the title, removed the promotional template sections and generic FAQ, and corrected product wording to the current BYOK model.