Andrew Ng outlines four practical steps for building agents from loops to graphs
theomitsa · x · 2026-07-24
A repost of Andrew Ng’s PDF lays out four agentic workflow steps for moving from simple loops to graph-like systems.
- Reflection: let the agent write, have a second prompt critique it, then rewrite — a self-review loop can outperform a smarter model with no feedback.
- Tool use: add search, code execution, and APIs; otherwise the agent is mostly hallucinating.
- Planning: ask the agent to break the task into JSON steps before execution and replan when a step fails.
- Multi-agent: split roles across a team — one writes code, one reviews, one tests.
The post frames these as practical wiring patterns for building better agents today, starting with a critique step and then adding more structure as tasks get harder.
Related event: Evolution of AI Agent Architecture: From Loops to Graph Engineering(8 posts)→
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