What's this about?
A multi-agent framework built on CrewAI for conversational business intelligence: five specialized agents operating in a sequential pipeline to process natural-language queries into analytics and insights.
What exactly is a "sequential pipeline" of specialized agents?
Rather than one agent doing everything, the work is split into stages with a different agent per stage — one interprets the question, one writes the query, one runs it, one interprets results, one writes the summary — each handing off to the next. The appeal is that each agent has a narrow job with a focused prompt, which is easier to get right and easier to debug. The cost is that errors propagate forward with no way back: if the question was misinterpreted at stage one, every subsequent stage does excellent work on the wrong question.
Why is this worth noticing?
- It's an unglamorous but honest picture of where multi-agent systems are actually deployed — business intelligence, not autonomous research.
- The sequential-pipeline pattern is what today's Grading the Graders paper is aimed at: each stage needs verification, and without it the pipeline's reliability is the product of its stages.