In this episode, Dr. Sebastian (Seb) Benthall joins us to discuss research from his and Andrew's paper entitled “Validity Is What You Need” for agentic AI that actually works in the real world.

Our discussion connects systems engineering, mechanism design, and requirements to multi‑step AI that creates enterprise impact to achieve measurable outcomes.

Defining agentic AI beyond LLM hype
Limits of scale and the need for multi‑step control
Tool use, compounding errors, and guardrails
Systems engineering patterns for AI reliability
Principal–agent framing for governance
Mechanism design for multi‑stakeholder alignment
Requirements engineering as the crux of validity
Hybrid stacks: LLM interface, deterministic solvers
Regression testing through model swaps and drift
Moving from universal copilots to fit‑for‑purpose agents

You can also catch more of Seb's research on our podcast. Tune in to Contextual integrity and differential privacy: Theory versus application.

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Why validity beats scale when building multi‑step AI systems