Intel / video

You’re Not Thinking Big Enough: Rebuilding Food Systems with AI Agents — Cody Menefee, Firecrawl

Source: youtube.com
Author: AI Engineer
Date: Published Sep 23, 2026

Context

The grazing assistant proposed in this talk would recommend where a herd should feed next, with a farmer confirming the move. It would combine animal locations, drought conditions and grass-height observations to support a decision that still requires inspecting pasture conditions.

The proposal separates controlling animal movement from deciding where animals should go. GPS collars can provide virtual boundaries, but the assistant would also need reliable pasture measurements, relevant farming knowledge and access to collar software. Those are described as unresolved requirements. The intended contribution is help with the recurring grazing decision, with the farmer retaining approval.

Key takeaways · AI-distilled

Cody Menefee says only about 3% of cattle finish on pasture largely because of labor: good rotational grazing means moving the herd, fences, and water to a new one-day paddock every day.
GPS collars with virtual fences can move animals, but he argues they solve the fence, not the decision: grass regrows differently after drought, rain, or trampling, so someone still has to go look.
His proposal puts a in the loop, fed animal locations, drought conditions, and grass height (for example from a cheap trail cam aimed at a measuring stick), to suggest the next paddock for a human to confirm.
He lists three blockers: a grazing knowledge base (he is scraping farmer YouTube and papers into Open Pasture), a vision layer for biomass and biodiversity, and collar makers that lock out outside software.

Terms in this piece · Glossary

LLM — A large language model — the neural network behind tools like Claude and ChatGPT, trained on huge amounts of text to predict what comes next.

Read the source www.youtube.com