Building production AI agents requires context engineering over prompt engineering. A production failure with Metabot revealed that locally optimized components created contradictory signals in the LLM's context window. Three key patterns emerged: LLM-optimized data representations with structured templates, just-in-time
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What we were building (and why it’s hard)What broke: local optimizationWhat worked: context engineering over prompt engineeringThe benchmark problem in AI analytics agentsBuild for chaos, not happy pathsTry it yourselfSort: