Talking AI CEO of Alteryx on Why AI Agents Need Real Business Logic
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Jan 20, 2026 Andy McMillan, CEO of Alteryx and a former product leader, shares insights on how AI can empower data analysts rather than replace them. He discusses the critical role of business logic and how analysts can turn complex data into actionable insights. The conversation highlights the evolving nature of analyst tasks, the importance of data preparation, and AI's potential in automating workflows. McMillan emphasizes the need for tailored datasets and the balance between building in-house solutions versus purchasing software to meet specific business logic requirements.
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Prepare Curated Data For LLMs
- Build purpose-built data assets and calculators that encapsulate business rules before exposing them to LLMs.
- Let analysts own those assets so AI provides accurate, company-specific answers.
Semantic Layer Needs Operational Context
- A semantic layer describing data labels is insufficient without 'when to use' and 'why' guidance.
- Analysts provide the procedural context and clarifying questions AI needs to act correctly.
Limit Scope To Prevent Hallucinations
- Create narrow, well-defined datasets (not the full warehouse) for LLM interaction to avoid hallucination.
- Use analysts to summarize and validate those datasets before enabling conversational queries.
