The hardest problems building this weren’t in the LLM logic, but in everything around it —-observability, access control, and managing context across dbt, Tableau, and code. Finding the balance between a strict semantic layer and LLM agency was tricky. Too rigid and it loses llm magic, too loose and reliability breaks
What worked for me and my users was leaning on instructions + AGENTS.md + metadata as a lighter abstraction layer — structured enough for trust, but flexible enough to keep the model useful.
If you’ve been exploring similar ideas or trying to productionize AI analysts, I’d love to hear how you’re approaching it
What worked for me and my users was leaning on instructions + AGENTS.md + metadata as a lighter abstraction layer — structured enough for trust, but flexible enough to keep the model useful.
If you’ve been exploring similar ideas or trying to productionize AI analysts, I’d love to hear how you’re approaching it