Andrew Ng’s graph-based agent design claims a 90% efficiency gain
Roger_M_Taylor · x · 2026-07-22
A thread claims Andrew Ng built an agentic knowledge graph that improved agent efficiency by 90% by replacing ad-hoc tool search with graph-based retrieval.
Core idea
- Embed every tool and search by meaning, not just keywords.
- Because semantic similarity is not the same as correctness, represent tools as a graph.
- Retrieve the full path needed for a task, not just one tool.
- Turn the process into data so the sequence becomes explicit and reusable.
The post frames this as a practical, one-hour course on graph engineering for multi-step agents.
Related event: Evolution of AI Agent Architecture: From Loops to Graph Engineering(8 posts)→
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