The AI Agent Path to Prod: Building for Reliability
summary
Transforms a naive customer-support agent into a production-ready workflow using n8n and GPT‑4.1, starting from a scoped use case (free‑trial tickets are ~15% of volume) and a 14‑day extension policy. Adds structured JSON outputs, an eval loop that pulls cases from Google Sheets and runs repetitions (initial 3 runs showed a missing internal note in 2/3), then tightens the system prompt and examples to reach consistent 3/3; adds prompt-injection detection, human‑in‑the‑loop escalation, rate limiting and an error‑handler.
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chapters (9)
- 0:00Introduction
- 1:09Why reliable AI agents
- 5:05Viable scope for AI agents
- 8:14Naive AI agent in n8n
- 12:53Evaluations for reliability
- 17:53Evals like unit tests
- 20:45Edge cases and prompt injection
- 26:10Guardrails for production
- 30:47Next steps
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