Everyone knows that we all need agriculture at least three times a day. ⠀ But how often do we think about the people who make those meals possible? ⠀ Two years ago, in 2024, I was in Rome, Italy 🇮🇹, attending the World Food Forum. ⠀ Today, on World Food Day, I look back at that experience with a question: ⠀ How can we turn our ideas, research, and global conversations into meaningful progress for farmers? ⠀ Joining agriculture has been an amazing experience for me. ⠀ It has opened doors, introduced me to people, and given me opportunities to contribute to something that touches every life. ⠀ Every day is an opportunity to learn. ⠀ From a farmer explaining a challenge. ⠀ From a young entrepreneur testing an idea. ⠀ From research that pushes me to ask better questions. ⠀ This journey continues to shape how I see agriculture and my responsibility within it. ⠀ I believe that advancing sustainable agricultural practices through innovation driven by youth, climate action, and digital integration will be key to addressing the critical issues that matter to farmers. ⠀ Making that vision practical requires listening. ⠀ Farmers need solutions that reflect their realities: changing weather, rising costs, limited resources, uncertain markets, and the pressure to sustain their livelihoods. ⠀ Technology should help them navigate those realities. ⠀ Sensors can support better irrigation decisions. ⠀ Digital platforms can connect producers with information and markets. ⠀ Artificial intelligence can help translate complex information into useful guidance. ⠀ But usefulness depends on context. ⠀ Can farmers afford the tool? ⠀ Can they understand its recommendations? ⠀ Does it work under local conditions? ⠀ Can they trust it enough to act? ⠀ These questions guide my interest in AI, farmer trust, and technology adoption. ⠀ Young people have a significant role in finding the answers. ⠀ Their creativity can strengthen how we produce, process, distribute, and communicate about food. ⠀ Turning that potential into lasting contributions requires access to skills, mentorship, finance, and opportunities to work directly with farming communities. ⠀ It also requires valuing the knowledge farmers already hold. ⠀ The most promising ideas can emerge when practical experience meets fresh thinking. ⠀ That is the kind of agricultural future I want to help build. ⠀ One where innovation supports livelihoods. ⠀ Where climate action is practical and accessible. ⠀ Where young people can build meaningful careers. ⠀ And where farmers help shape the technologies intended to serve them. ⠀ I am grateful for this journey and for every opportunity to keep learning, contributing, and growing alongside others. ⠀ Happy World Food Day!

This is how portable drying machines transform post-harvest practices.

Extension may become even more important in the age of AI. Not because farmers need someone to use technology for them. But because more information creates a greater need for trusted interpretation. Information abundance increases the value of judgment.

Did you know that some of the world’s new agronomists are AI agents? Imagine asking a system when to irrigate and having it check your soil readings, weather forecast, crop stage, and field history before recommending a next step. That is the promise of AI agents in agriculture. In this newsletter edition, “The World’s New Agronomists Are AI Agents,” I explore how these systems could help farmers turn agricultural information into practical decisions. I examine irrigation, planting recommendations, crop monitoring, and agricultural robotics, looking closely at what research has demonstrated and what still needs testing. I also explore the questions that will shape adoption: Can farmers trust the advice? Is it locally relevant and affordable? Who controls the data? Who takes responsibility when something goes wrong? The opportunity is substantial. Earning farmers’ confidence will require evidence from the conditions where they actually grow food. Which agricultural decision would you trust an AI agent to support? Read the full edition below. 👇 linkedin.com/pulse/worlds-ne… via @LinkedIn

How can you stand in a field like this and not smile? Although, looking at my orange hat and red shirt, I may have arrived dressed as a traffic light. Behind me are beautiful rows of vegetables. Behind those vegetables are decisions, patience, hard work, and someone hoping the weather will cooperate. A beautiful farm photograph makes growing food look easy. The weeds would like to disagree. Growing up around farming in Rwanda, and now studying agricultural systems in Nebraska, I appreciate how much thinking happens before food reaches our plates. When should we irrigate? How much moisture remains around the roots? Will the harvest justify the effort? These questions make agricultural research meaningful to me. Digital agriculture can connect soil moisture sensors, weather information, and farm records to support irrigation decisions. For me, integrated water management means considering rainfall, soil water storage, crop demand, and irrigation performance together. AI can help analyze those data. Nebraska researchers have tested AI models to estimate crop water use and water stress using sensor and weather information. But my research interests also include trust: can farmers understand the recommendations, assess their reliability, and use them confidently? Recommendations also need testing under local conditions. I want technology to help growers make informed decisions, conserve water, and protect their livelihoods. Also, vegetables are surprisingly patient selfie companions. No complaints, no blinking, and absolutely no requests to retake the photo. If you could grow just one crop in your backyard, what would it be, and why?

Can a conversation on a phone change how a farmer manages their crops? A new study by @MAliAouad, @Alpsungu , Niyazi Taneri, and @CanberkUcel tested AI agricultural advice with 1,935 rice farmers in India and the Philippines. Farmers reported improvements in some farming practices, particularly managing pests, weeds, and diseases. Their findings also raise important questions about the support farmers need to turn advice into action. In my newsletter, I share what I learned from their research and what it could mean for AI in agriculture. Credit to the research team and their supporting organizations, including @WhartonAIAI, @CambridgeJBS, @essec, MIT Generative AI Impact Consortium, MIT Sloan’s ASEAN fund, Wharton Global Initiative, and Wharton Tanoto Initiative. Check out my newsletter below , and read their full paper here: papers.ssrn.com/sol3/papers.… linkedin.com/pulse/can-ai-ad…

Three times every day, agriculture becomes personal. Breakfast. Lunch. Dinner. You may never visit a farm, but agriculture visits you every day.

We spent decades asking how to produce more food. Now agriculture faces a harder question: More food with less water. Less land. Fewer inputs. Lower emissions. The next revolution is not simply about producing more. It is about producing better.

A farmer can make the right decision and still lose money. Rain can stop. Prices can fall. Disease can arrive. Agriculture teaches something business schools sometimes forget: Good decisions reduce uncertainty. They do not eliminate it.

We invented machines that can steer themselves within centimeters. But many farmers still struggle to move data from one platform to another. Sometimes innovation moves faster than integration. And the farmer pays for the gap.

AI Has a Language Problem, and 3.4 Billion People Are Living With It

Agriculture is often described as traditional. Yet few industries have moved from animal power to autonomous machines within a few generations. Farmers have always adapted when innovation creates value.

Three meals a day make agriculture ordinary. That may be agriculture's greatest achievement. An enormously complicated system works so consistently that billions of people rarely have to think about it. Success can make essential systems invisible.

We keep asking what the farm of the future will look like. More robots? More sensors? More automation? More AI? Maybe the better question is: Will the farm of the future be profitable, resilient, sustainable, and worth passing to the next generation?

We have never had more tools for understanding farms. Satellites above them. Sensors inside them. Machines moving through them. Models analyzing them. Perhaps the next breakthrough is not another tool. It is learning how to connect what we already have.