Discuss agent architectures and share learnings with the community.
Tabular enterprise data needs schema-aware retrieval, SQL or semantic layers, and explicit join logic. Dumping rows into chunks and embedding them is why agents confidently cite the wrong quarter.
Glue-code automation wins when MCP tools are idempotent and the workflow owns retries, not when you chain hopeful API calls and pray the agent recovers.
A three-person team ships production software no human writes or reviews. Down the hall, experienced developers get measurably slower with AI, and never notice. The distance between them is the most important gap in software, and no tool can close it.
LangGraph makes state explicit; CrewAI abstracts roles. Neither is 'better'. The choice is whether your team needs inspectable graphs or faster role-based prototyping.
