Agents are easy to demo, hard to ship: a 13-step checklist for production-grade AI agents
goyalshaliniuk · x · 2026-10-04
Shalini Goyal argues that a production-ready agent needs far more than an LLM wired to tools. Her end-to-end flow: capture intent, authenticate and run safety checks, decide permission, plan and decompose tasks, retrieve context from memory/RAG/vector DBs, select tools with verified permissions, execute, validate accuracy and safety, re-plan or retry on failure, escalate risky actions to humans, respond, and log feedback. What surrounds the loop matters most: monitoring/tracing, audit logs, rate limits, secrets management, privacy policies, model and prompt guardrails, and incident handling. The goal is controlled autonomy with permissions, validation, observability, and human oversight — not maximum autonomy.
Related event: From Demo to Production: Engineering AI Agents for the Real World(2 posts)→
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