ISOM 260 · Session 8

Multi-Agent Workshop

45:00
45:00 30:00 15:00 0:00
Build the Researcher Agent
15 min · 45:00 – 30:01
  • Define the Researcher's system prompt
  • Set structured output format (Key Facts, Statistics, Trends, Confidence)
  • Test on "AI agent enterprise adoption trends"
Build the Analyst Agent
15 min · 30:00 – 15:01
  • Connect Researcher output as Analyst input
  • Define pattern identification prompt
  • Generate insights + recommendations
Add Editor + Run Full Pipeline
15 min · 15:00 – 0:00
  • Build Editor agent (fact-check + clarity + score)
  • Wire all three agents into run_pipeline()
  • Run end-to-end and compare with single agent
Open Notebook in Colab
Phase 1 — Researcher
  • Start with a clear role: "You are a specialized Research Agent"
  • Force structured output with "Return EXACTLY this format:"
  • Include a confidence level for accountability
Phase 2 — Analyst
  • Feed researcher_output directly into the analyst's user message
  • Tell the analyst: "Don't just restate — find what the researcher missed"
  • Require specific fact IDs to prevent hallucination
Phase 3 — Editor + Pipeline
  • Editor receives BOTH researcher and analyst output
  • Use a quality score 1–10 for measurable feedback
  • Compare: Is the pipeline output really better than single agent?