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Building Production-Ready AI Workflows
Mujtaba · · 8 min read
Most AI prototypes impress in a meeting and then quietly fail in production. The model was rarely the problem — the system around it was.
Four things every AI workflow needs
- An evaluation set that runs on every change
- Guardrails on inputs, outputs and tool permissions
- Tracing of every model call and tool call
- A clear human-in-the-loop path for low-confidence cases
Treat prompts and model versions like code: versioned, reviewed and tested. Treat cost and latency as product requirements, not afterthoughts.