The Farmer's AI Handbook

grow more with AI in the field

Farmers are under pressure to use AI, but the work still has to be correct, on-brand, and defensible. Without a clear method, you either avoid the tools or use them sloppily and lose trust. The cost shows up fast - wasted time, inconsistent quality, and avoidable risk (hallucinations, privacy leaks, and over-automation). Tasks like 'Forecasting - weather, prices, and yield scenarios' and 'Sensor data and record keeping workflows' become harder, not easier, when the process is fuzzy. This handbook gives you a step-by-step system you can turn directly into a chapter-by-chapter TOC: how to set goals, choose tools, write prompts that include the right context, verify outputs, and reuse templates. Expect ready-to-use checklists and artifacts for core outcomes like forecasting - weather, prices, and yield scenarios, sensor data and record keeping workflows, and input optimization - water, fertilizer, feed.

Inside this book

• Forecasting - weather, prices, and yield scenarios
• Sensor data and record keeping workflows
• Input optimization - water, fertilizer, feed
• Equipment maintenance planning and checklists
• Supply chain and market timing decisions
• Tool setup and guardrails - data boundaries, privacy, and audit trails
• Templates you can reuse - prompts, checklists, and scoring rubrics
• Measurement - track time saved and quality improvements over 30 days

By Valentin Nagacevschi