Topic archive
3 essays tagged Production AI. Practical notes on what happens after the demo: prompts, tools, review packets, evals, rollback, and production ownership.
The AI POC is not the hard part anymore. The hard part is turning a promising demo into a service with ownership, evals, traces, cost controls, and a rollback path.
A latency chart will not explain why an AI answer was wrong. Production LLM systems need traces, sources, tool calls, prompt versions, eval results, and human decisions.
Financial-services AI agents can be useful, but autonomy without permissions, audit trails, segregation, evals, and rollback is just operational risk with a nicer interface.