You’re Not Thinking Big Enough: Rebuilding Food Systems from First Principles with AI Agents

Official Schedule Context

Most of the AI world is still thinking too small. We’re building SaaS wrappers and GTM agents while

real-world systems are still run through fragmented knowledge, delayed feedback, and human

guesswork. In this talk, I’ll show how I’m building an outdoor agentic system for pasture-raised

livestock operations using LLMs, a Firecrawl-curated knowledge base, drone and satellite imagery,

and geo collars to monitor pasture, guide animal movement, and support better decisions across

cattle, sheep, poultry, and more. I’ll cover the architecture, retrieval and grounding, human

approval loops, and what broke first: hallucinated confidence, weak environmental grounding, sparse

evals, and the gap between a smart answer and a safe action. It’s a case study in building agents

for the physical world, and a broader argument that AI’s real upside is in rethinking real-world

systems from first principles.

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