Beyond Tech Special Edition | Newsletters

The United States has record agricultural productivity and a thriving AI and cryptocurrency sector so far 47 AD Americans They still struggle to access food reliably, including 1 in 5 children. Food, trucks and stores are there. The missing pieces are information, coordination and sustainable financing.

Launch of the “Zero Hunger” token $EAT — how Wade (Wyoming decentralized exchange) Impact tokens and coins are shaping the emerging new combination of American food systems and charitable giving in 2026.

Farm to cloud – How artificial intelligence is reshaping the American food chain. Quiet spread of Artificial intelligence decision engines Since the new food stack’s nervous system is powered by USDA 2025-26 Artificial Intelligence Strategy and Agricultural technology financing.

Web 3 for dinner – How Blockchain Became Quiet Infrastructure in Food Aid, Programmable Food Entitlements, On-Chain Reporting, and Food Chain Transparency.

AI and agricultural technology funding forecasts – How AI has become the defining growth engine com.agrifoodtech In 2026. Investors will shift their focus to AI-heavy tools that promise true efficiency, flexibility, and margin improvement across the food value chain.

With the holiday season in full swing and 2026 ushering in, this edition targets builders, founders and public sector leaders by asking a simple question:

The currency that feeds people: inside WadeEAT symbol for $

Most currencies are found in bank accounts. Bitcoin burns electricity and turns it into hash and heat. $EAT is designed to do something even more powerful: it turns transaction fees into meals and is the first of its kind CauseCoin.

release December 10, 2025 On Coinbase’s underlying blockchain, eat $Our goal is to eliminate hunger by guiding A 0.25%-1.25% Impact Fee For reasons to relieve hunger when trading. $DOGE.X ( ▼ 6.55%) ) An average of $2 billion in daily volume. If just 0.50% of that went to causes like the ASPCA, it would exceed the ASPCA’s current annual donation volume in less than two months and nearly 10 times that over the course of a year.

On the network, each trade receives fees divided between them Making an impact (25%), shareholder rewards (25%), WYDE liquidity and marketing (25%), infrastructure (25% + small protocol allocation). Verified 501(c)(3) Partners like Feed America, No child is hungryRegional food banks are waiting to receive programmatic funding.

Wade works under Wyoming Donna Legal framework of the DAO. The article, Donna Guide 2025 Posted yesterday explaining the DUNA framework, including configuration requirements and tax options. DUNA is an innovative way to display Legal recognition For decentralized LLCs, choose either corporate or nonprofit structures such as 501(c)(3) or 501(c)(4).

For traders, the $EAT offer is simple:

“Accept $EAT and every checkout in your store automatically feeds a person today, with an auditable impact on your ESG dashboards.”

For a sector that spends $12 trillion annually on food globallyAn interesting thought experiment: if so 5% Of this spending eventually passes through the bars of $EAT, resulting in 3 billion dollars In annual impact fees can fund approx 2.4 billion meals a year At non-profit prices. This is enough to close the current global hunger gap on an ongoing basis, simply by channeling a portion of natural food trade through a different monetary primitive.

release December 10, 2025 On Coinbase’s underlying blockchain, the eat $ The code aims to provide a stable funding source for charities that provide real food to people who can’t afford it in the United States.

The most interesting food tech this winter isn’t a new delivery app. It is the quiet spread of Artificial intelligence decision engines From fields to warehouses to community stores.

On the production side, the United States Agricultural technology financing In 2025 it is leaning towards Heavy AI tools: Computer vision that detects crop stress, robots that automate weeding, and analytics that improve irrigation in climate-stressed regions like California’s Central Valley. the USDA 2025-26 Artificial Intelligence Strategy It explicitly relies on machine learning to predict productivity, monitor pests, and respond to disasters.

These models now trickle down the chain:

• Processing plants and warehouses Deploy AI-powered cameras to detect contamination and defects faster than human inspectors.

• Kitchens, cafeterias and workplace canteens Use sensors to track what’s cooked, served, and what’s thrown away, with dashboards that suggest menu changes, portion sizes, and donation opportunities in near real-time.

The layers on top are Routing and demand forecasting engines That treats food like cloud power. Instead of CPU cycles, they reallocate milk and production pallets, directing trucks away from saturated neighborhoods and toward “cold areas” on the map. If done correctly, the system looks like… “AWS for calories”: A shared digital infrastructure that knows where it is located, who needs it, and how to connect the two with minimal waste.

The holiday period is an annual stress test. Demand for food banks rises at the end of the year as storms and disrupted work schedules hit vulnerable families, while retailers risk over-demanding. AI-enhanced forecasting that integrates historical patterns, real-time point-of-sale data, and local signals can make the difference Extra turkeys in litter boxes and Extra dinners in community refrigerators.

For founders and city IT managers, 2026 is shaping up as the year that “Public Sector AI for Food” moves from experimental to core chipsets.

Crypto’s reputation problem was based on memes and speculation. The most interesting story of 2026 is how Blockchain technology has become the quiet plumbing for food aid and benefits.

United Nations World Food Programme Building blocks The project remains one of the most important real-world deployments. In refugee camps, families receive digital “credits” instead of paper vouchers; Purchases at participating stores are recorded on a permissioned blockchain network, which improves traceability and reduces intermediaries and foreign exchange leakage. Beneficiaries know that their entitlements are recorded correctly, that retailers get paid faster, and that donors see where the money is going.

Latest efforts such as Food for crises They are experimenting Charity on the chain Stack, aiming up to 1 billion dollars In hybrid assets and scoring flows down to the project level so institutional donors can read impact from dashboards instead of legacy PDF files.

the $EAT ecosystem These patterns extend to retail and trading behavior in the United States:

• all Eating trade $ On the methods of WYDE Impact Exchange 25% of dynamic fees Directly to verified 501(c)(3) nonprofits.

• Fee distribution and accrual are fully transparent, with charitable allocations unlocking as the token’s market value grows $10 million to $100 million.

Looking forward to 2026, the potential user experience is “Web 2.5”. Users tap cards or scan QR codes; Under the hood, blockchains deal with auditability and programmable logic. He thinks Immediate emergency food credits For disaster-affected households, which can be redeemed at regular retailers, settlement is done via a transparent ledger. or Symbolic surplus Food pallets that are nearing expiration appear as claimable digital assets that NGOs can channel to local programmes.

The limitations are real: KYC/AML rulesState-to-state money transfer law, and the volatility of cryptocurrencies, all shape what’s possible. But for policy makers and protocol designers, the design brief is clear:

Less casino, more “GitHub for grants and groceries.”

After a tough few years for venture capital in the agri-foodtech space, 2024 has seen a slight rebound — and 2025 appears to be accelerating a clear shift in the types of companies grabbing investor dollars. According to AgFunder Global Agri-Food Technology Investment Report 2025funding for agri-food technology in the United States grew by 14% in 2024 – Bucking the general downturn and signaling renewed investor interest.

Crucially, much of this renewed interest is in leveraging tools and companies Artificial intelligence (AI), machine learning, robotics, or data-driven agricultural engineeringInstead of “classical” agricultural technology – such as appliance tractors or conventional inputs. In other words: there is a clear trend towards “digital + smart” agriculture.

Macro pressures and economic constraints It made investors more selective. Startups need it now Strong unit economics, scalability, and defensible differentiation – AI delivers this through data, software and automation.

The global market for artificial intelligence in agriculture is expanding rapidly. Projections indicate a significant CAGR over the next decade for AI-powered agriculture tools (sensors, predictive analytics, precision agriculture).

The real-world demand – for farmer labor relief, improved yields, and sustainable use of resources – aligns precisely with what AI can offer: smarter decision support, more efficient inputs, and better risk management.

short: AI-based agricultural technology addresses exactly those structural challenges (climate variability, labor shortages, input cost volatility) where “old school” agricultural technology often struggles.

Redirecting AI first offers big advantages – but it also comes with its own set of risks:

+ Pros: Better scalability; Software-based margins; High defensibility via data and algorithms; Ability to deliver value per acre even at large scale.
+Cons: High upfront development cost; Farms must adopt new courses of action; Requires data infrastructure; Success depends on adoption across varying farm types (size, yield, geographic areas).

Risk of selection bias: With investors focusing on “digital and agile” startups, Pure biological or hardware only Agritech may struggle to obtain capital – even if it offers environmental or sustainable benefits.

In other words: the winners may be the ones who collect Artificial Intelligence/Automation + Biological or Conventional Agricultural Engineering – Digital delivery + real-world agricultural impact.

More “hybrid” startups. – Combining AI, data analytics and biology/nutrition to manage soil and crops (not just robots or markets).

Organizational drive and sustainability – As climate pressures rise, regulators and buyers may prefer systems that provide environmental benefits through precision, putting AI-based systems in an advantageous position.

Farmers’ dependence/resilience – We’ll be watching which of these first AI innovations gain real-world traction at scale, and how much they actually impact productivity, input costs, and environmental footprint.

Continued investor focus – Fewer and bigger bets on startups that show realistic paths to scale and unit economics – Early-stage non-AI biocompanies may have to work harder to obtain funding.