Agriculture is the oldest industry in the world — and one of the least represented at AI conferences. In this episode, Sam talks with Jeremy Groeteke, CIO of Syngenta's vegetable division, about how a company operating in 90+ countries with 50,000 employees is building AI infrastructure to help feed the world.

Topics covered:

• Syngenta's approach to merging AI, data science, and physical science in agriculture
• Using computer vision for early disease and pest detection in crops
• Why general-purpose LLMs like ChatGPT and Claude give farmers overly generic recommendations — and why domain fine-tuning matters
• The shift from data lakes to data mesh at Syngenta
• Single-agent vs. multi-agent AI architectures — and why accuracy often favors single agents right now
• The "metadata problem": why having data isn't enough without context about how it was collected
• Cropwise AI — Syngenta's tool for turning insight into actionable recommendations
• Why agriculture's long biological cycles make it a poor fit for typical VC/tech timelines
• Advice for technologists looking to break into agtech

Guest Bio:
Jeremy Groeteke is CIO for Syngenta's vegetable division, overseeing digital strategy for an organization that provides crop protection, biologicals, digital tools, and genetics to growers in over 90 countries.

Connect:
Find Jeremy on LinkedIn to learn more about Syngenta's work in AI and agriculture.