AI+ Agronomists & Extension Workers
From Field Data to Farmer Impact with AI
The gap between field data and farmer impact is made of unwritten reports and untranslated research.
You're sitting on a stack of unread research, a queue of unwritten advisory reports, and extension materials that never quite reach the farmers they're meant for. AI doesn't replace your field knowledge — it accelerates the translation: from soil data to diagnosis, from technical bulletin to farmer-ready guide, from M&E spreadsheet to donor impact narrative. The CROP Protocol gives you the framework; 40+ prompt templates give you the workflow. Built by an AI engineering firm for agronomists and extension workers who know the gap between evidence and impact — and are determined to close it.
- 42 ready-made prompts: soil and crop diagnosis, fertiliser planning, extension materials, M&E reporting
- The CROP Protocol — the four-stage advisory framework from context-setting to portfolio-wide outcome tracking
- A dual-track approach serving both agronomists and extension workers with separate worked examples and 90-day plans
- A multilingual extension workflow for producing farmer guides, SMS advisories, and demo scripts at any literacy level
- A 90-day adoption plan for agronomists in private practice and extension workers in government and NGO programmes
Agronomist (crop consultant, soil scientist, precision agriculture specialist, agricultural advisor) or extension worker (government agricultural officer, NGO agricultural programme officer, rural advisory service officer, agricultural development worker) — holds an agricultural science qualification; works directly with farms or farmer communities; responsible for turning data and research into actionable field advice
Also for:Agricultural development programme managers; agricultural college lecturers training the next generation of extension workers; senior technical officers in agriculture ministries and development banks overseeing extension programmes
- Apply the CROP Protocol to structure AI interactions across the full advisory cycle — from field data collection to farmer-facing communication
- Use AI to diagnose crop and soil problems, develop evidence-based prescriptions, and generate input management plans
- Produce accessible extension materials (farmer guides, SMS advisories, demo day content) calibrated to different farmer literacy and context levels
- Synthesise agricultural research literature into practical field recommendations using AI
- Design an M&E framework for extension programmes and track impact using AI-assisted analysis
- Diagnostic
- How AI-ready are you as an agronomist or extension worker?
- Chapter 1
- AI in Agronomy and Extension Right Now
- Chapter 2
- Your Agricultural AI Toolkit
- Chapter 3
- Soil and Crop Diagnosis
- Chapter 4
- Precision Recommendations and Input Planning
- Chapter 5
- Extension Materials and Farmer Communication
- Chapter 6
- Research Translation and Evidence Synthesis
- Chapter 7
- Farm Advisory Reports and Programme Documentation
- Chapter 8
- Working with Agricultural Data Safely
- Chapter 9
- Monitoring, Evaluation, and Programme Impact
- Chapter 10
- Your 90-Day AI Adoption Plan
- Back matter
- Skill Summary · Recommended Next Reads · Glossary · Tool Reference
Built by an AI engineering firm for agronomists and extension workers who know the gap between evidence and impact — and are determined to close it.
