Agent building is easy. Context is where agents still fail.

Jeff Ng demonstrates that building agents has become trivial thanks to frameworks like Flu and Cloudflare, reducing a quarter-long team effort to minimal code. However, the core problem has shifted from engineering complexity to context management.

His live demo shows an agent confidently recommending a fix that caused a previous outage. The agent lacked Slack discussions, postmortems, and tribal knowledge. This failure would propagate silently as a background agent, misinforming humans and other agents.

Ng argues the real bottleneck is not model intelligence but context. MCP provides raw access but not understanding, overwhelming agents with irrelevant data and leaving them to resolve conflicts ad hoc. A context engine that synthesizes information from scattered sources is positioned as the missing layer.

This is clearly a product pitch, but the underlying signal is valid: as agent deployment becomes frictionless, context quality becomes the binding constraint. Teams will need to invest in institutional knowledge infrastructure before deploying autonomous agents safely.