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Discuss agent architectures and share learnings with the community.
Discuss agent architectures and share learnings with the community.
The LangChain brand spans an abstraction library, a graph runtime, an eval/observability platform, and an expression language. Teams that blur them ship the wrong tool for the layer. Here's the clean mental model.
Letting agents riff produces great demos and terrible audits. Explicit planner–worker–critic loops encode rejection at the orchestration layer. The same move as scaling-your-no, but structural.
Everyone name-drops hooks and skills. Almost nobody explains when to use which, and conflating them builds brittle agents that break on the second edge case.
Generation is solved. The bottleneck is judgment, and the specific, learnable, scalable form of judgment is saying no to confident AI output, and knowing exactly why. Most teams let every one of those noes fall on the floor.