Antony Yousefian is a partner at The First Thirty which backs early-stage entrepreneurs leveraging technology to enhance human and planetary health.
The views expressed in this article are the author’s own and do not necessarily represent those of AgFunderNews.
When I first ventured into ag and foodtech in 2015, I believed we were on the cusp of a revolution. I was mistaken. though. We were far from ready.
Back then, we lacked the technology to truly engage with nature’s complexity. We had fragments—sensors, rudimentary machine learning, enhanced genetics—but no cohesive framework to unite them.
Fast forward to the last 18 months, and the pace of change isn’t just accelerating, it’s compounding. The convergence of artificial intelligence, plummeting computing costs, and ubiquitous connectivity have ignited an inflection point that demands attention. These aren’t incremental improvements; they represent a fundamental shift in how we harness biological systems.
Between 2015 and 2022, progress was gradual, almost tentative. Now, it’s surging. Foundation AI models are decoding biology’s intricate relationships. Computing costs are dropping by 70% annually, and connectivity is becoming near-free and universal.
Meanwhile, our century-old food systems—industrial, standardized, and inflexible—are faltering under mounting pressures:
- Major food companies report slowing growth and compressed margins.
- Global healthcare systems strain under the burden of diet-related diseases.
- Climate pressures expose the vulnerabilities of conventional agriculture.
- Consumers demand transparency and nutrition that commodity systems struggle to deliver.
At The First Thirty, we’re no strangers to the skepticism surrounding agtech. After all, returns in this space have often been underwhelming, to say the least. Yet, what’s unfolding now is not a repeat of past cycles but a moment that is distinct and investable. Allow me to explain why.
What held us back: the old barriers
The fundamental flaw in our initial wave of agricultural technology wasn’t just a lack of tools, it was a mismatch of approach. We applied linear, industrial logic to exponential, biological systems, and four critical barriers kept us stalled:
- The complexity trap: We tried to simplify biology’s richness—its monocultures, uniform inputs, basic nutrition—to fit our limited capabilities. Nature thrives on diversity, and we couldn’t accommodate it.
- The intelligence gap: Early AI could identify simple patterns but failed to grasp the intricate feedback loops such as weather influencing soil, microbes driving nutrient uptake, and food impacting health.
- The cost barrier: Even when we understood the complexity, the economics didn’t align. Spending £100,000 ($127,000) on compute to save £50,000 ($64,000) in inputs was a non-starter that no board would have approved.
- The data void: Rural connectivity was unreliable and expensive. Sensors were cumbersome and costly. The biological world remained largely inaccessible to digital insight.
Those constraints are no longer relevant. Technology is advancing exponentially, propelled by new enablers opening possibilities that were unimaginable even just three years ago.
Computing power: decoding life’s complexity
Analyzing biological systems once carried a prohibitive price tag: millions to explore soil microbes or nutrient dynamics.
That’s changed dramatically, with AI training costs falling 70% annually, according to ARK Invest, and NVIDIA’s H100 chip delivering 30x better AI performance per watt than its predecessor.
Meanwhile, cloud platforms like AWS, Google Cloud, and Azure have democratized access, offering this power for mere pounds per hour rather than millions upfront. A computation costing £100,000 in 2020 now runs for under £1,000, or around $1,200.
All of this unlocks the ability to:
- Map entire microbiomes and their influence on human health
- Simulate how growing conditions enhance nutritional outcomes
- Trace real-time connections between soil vitality and human wellness
AI: From simple rules to biological understanding
Early AI was a blunt tool, effective for narrow tasks but blind to broader context.
Today’s foundation models, trained on vast datasets, function like a team of expert researchers, synthesizing connections across weather patterns, soil health, plant genetics, and microbial activity. Claude 3 can process complex scientific papers overnight, drawing insights that once took months. Google’s Gemini Ultra integrates text, images, and data to decode multifaceted systems. Even smaller models, like DeepSeek, demonstrate that precision can outshine scale in specialized domains.
This isn’t mere automation—it’s a leap in biological comprehension.
Connectivity: the biological internet
Recall the days of driving to a field with a USB stick to gather data? That’s history.
Starlink has slashed rural internet costs to £100 ($127) per month, delivering speeds exceeding 100Mbps. AST SpaceMobile is poised to transform every mobile phone into a satellite receiver, eliminating signal dead zones without specialized equipment. Innovations like Wiliot’s battery-free, ambient-energy chips track temperature, humidity, and chemical changes at microscopic scale. In 2015, connecting a single sensor cost £50 monthly.
Today, thousands can be linked for the same price. Soon, millions will cost pennies, creating a dense, real-time network of biological data.
The opportunity ahead: a new era for food and biology
This isn’t about better machinery or higher yields—it’s a reimagining of our relationship with nature, driven by technology. Three seismic shifts define this moment:
- Decoding complexity: We’re moving beyond data collection to true understanding—like shifting from grainy pixels to 8K resolution, revealing the full symphony of biological interactions.
- Flipped economics: For the first time, working with nature’s complexity—optimizing and understanding it—is more cost-effective than resisting it. The tools now cost less than the inefficiencies they address.
- Value migration: Economic value is transitioning from commodity crops to precision nutrition, synthetic inputs to biological solutions, reactive healthcare to preventative food-as-medicine.
Echoes of the ‘90s internet boom
All of this mirrors the internet’s ascent in the 1990s. Skeptics dismissed dial-up and rudimentary browsers as novelties until infrastructure—broadband, Netscape—unlocked explosive potential. E-commerce and social media surged, creating trillion-pound giants almost overnight.
Agritech is at its own Netscape moment: AI serves as the browser, decoding biological complexity, while computing costs, down 1000x, make it economically viable to process nature’s data. The internet accelerated from “email’s a fad” to “every company’s a tech company” in a blink. Biology’s digital revolution is outpacing even that trajectory.
Take the global food system, valued at £8 trillion ($10 million) annually, and healthcare, another £8 trillion market driven by diet-related challenges. These aren’t separate anymore; they’re converging, fueled by tech that links soil health to human wellness. At TFT, we see this fusion as a £16 trillion opportunity—not just adding markets, but creating new value through precision nutrition, regenerative agriculture, and preventative health solutions. Early movers will forge empires; those who hesitate will be left scrambling.
Why now? The clock’s ticking
This isn’t a fleeting trend, it’s the dawn of a transformative alliance between technology and nature, one that regenerates ecosystems, enhances human health, and unlocks unprecedented economic value. The £16 trillion fusion of food and healthcare is accelerating faster than even the most optimistic forecasts predicted.
For investors, this is a defining moment. Those who act now won’t merely participate, they’ll shape the future of food and health for the next century. Delay, and you’ll be catching up to a train already in motion. At The First Thirty, we’re committed to backing the disruptors driving this revolution—because the opportunity is here, and the window is narrow. The time to invest is now.
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