4 Steps For Rapid Growth In The AI Age

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Inside a L’Oréal factory, high-value botanical ingredients for fragrances and cosmetics no longer depend on distant weather, vulnerable global logistics or multi-month demand forecasts. L’Oréal is deploying AI-controlled, closed-loop “BioPods” developed and operated by Interstellar Lab. (Disclosure: I am an investor in Interstellar Lab.)

Interstellar grows high-value plants on-site under precise conditions, producing ingredients the beauty giant requires, where and when it needs them. As demand increases, the company installs more pods.

Founder Barbara Belvisi says BioPods grew from Interstellar’s work with NASA: “We wanted to figure out how to grow food on Mars. That remains our long-term mission. Meanwhile, we’ve built a great business here on Earth.”

Call this Edge Scaling: deploying small, complete, AI-enabled operating nodes at precise points of demand. In the AI Age—where monitoring, interpretation, even decisions, can be made nearly anywhere—the new question for strategic scaling of manufacturing becomes:

What is the Minimum Complete System we can deploy profitably at the point of demand?

In the AI Age, companies can win by placing intelligent, networked, complete operating systems closer to customers, continuously improving each node and the network’s overall performance.

Scale Ain’t What It Used To Be

For over two centuries, the dominant manufacturing growth playbook was to build big factories, standardize output and distribute across distance. Leaders were required to forecast demand months or years in advance, raise capital to build massive facilities and hope the market would absorb the capacity.

Industrial Age scaling harbors a systemic risk: it forces leaders to make irreversible, capital-intensive bets ahead of verified demand. If the forecast is wrong, owners are left with underperforming assets, overcapacity and sometimes insolvency. Pandemic bottlenecks, wars, climate shocks and geopolitical tension exposed the fragility of global supply chains.

Digital technologies reward a different logic. By pushing intelligence, agility and production closer to the edge—a multi-decade trend called Proximity—companies can scale more in synch with verified demand.

Lisa Morales-Hellebo, founder of venture firm REFASHIOND Ventures, observes, “We’ve been betting on Edge Scaling before you named it.” With over 70 manufacturing and supply chain-focused companies in their portfolio, she reasons, “Companies winning in the AI Age are deploying smarter, smaller productive systems exactly where customers require the output. The benefits are profound: less waste, lower logistics costs, faster iteration, greater resilience, and the ability to serve customers in ways unreachable by centralized production.”

The Minimum Complete System

Edge Scaling begins with the Minimum Complete System, or MCS: the smallest operating unit that can deliver profitable, high-quality customer outcomes.

An MCS is not a pilot version of a future larger facility. It is a complete node of a scalable network, containing the technology, data architecture, processes, safety and quality standards and inputs required to serve demand. With a proven MCS, scaling becomes less speculative. The company can install new nodes where customers have signaled need.

Consider Haddy, an advanced manufacturing company using AI-driven, robotic microfactories to produce large-format objects like boat hulls, architectural elements, concrete molds and furniture via additive and subtractive manufacturing. At its flagship 30,000 square-foot facility in downtown St. Petersburg, Florida, founder Jay Rogers and the Haddy team have proven their microfactory model. Opened in 2025, the facility is already operating near capacity. (Disclosure: I am an investor in Haddy.)

Nine industrial scale robots with both additive (3D printing) and subtractive manufacturing tools work with a team of highly-skilled production technicians–great new jobs in St. Pete. AI constantly experiments in response to each new customer requirement, expanding what’s possible. When robot-technician teams learn what works–and what doesn’t–the system instantly sends the insights to Haddy’s entire fleet.

Haddy’s second microfactory is under development in Los Angeles in partnership with Disney, which has contracted for 50% of the new plant’s capacity. Three more microfactories are in development stage across the US and overseas.

Because each microfactory shares identical digital architecture, design files can move instantly between facilities closer to end-use locations, reducing freight costs, transit times and carbon emissions. As Rogers explains, “Each microfactory is within an eight-hour range of tens of millions of consumers. We produce what our customers require for their customers: wherever, whenever, in whatever volume.”

One Scaling Logic, Many Sectors

The strategic logic applies across sectors.

Food production: Chicago-based FARMZERO builds small controlled-environment farms within vacant commercial office space in urban centers like Chicago’s Loop. They started by proving profitability of a 1,000 square foot indoor farm. The company only adds capacity when local customers, such as hospital systems, sign contracts.

Energy: Boom Energy’s hydrogen fuel cells enable hyperscalers like CoreWeave and Oracle to locate electricity generation on-site, scalable to power demands. Need more power? Add more fuel cells. Similar developments are underway in nuclear power with Small Modular Reactors and enhanced geothermal technologies from companies such as Fervo Energy.

Edge Scaling does not replace centralized high-scale manufacturing. If you require millions of bushels of soybeans, grow them on mega farms in Iowa or Brazil. If you need fresh produce for hospital nutrition, grow it near demand.

The future is center and edge.

Edge Scaling is best suited where responsiveness, customization, resilience or freshness create meaningful value. Centralized high-scale manufacturing retains advantages for standardized products with stable demand, long runs and low sensitivity to distance.

The Edge Scaling Playbook

To capitalize on this shift, manufacturers must master four moves:

1. Define the Minimum Complete System. Determine the smallest operating unit that can deliver profitable, high-quality customer outcomes. Specify what must remain consistent across every node, such as core functionality, data architecture, quality and cybersecurity.

2. Prove the model. Prove that your MCS can successfully serve customers and make money.

3. Replicate only with verified demand. Sign contracts for at least part of the capacity of a new node, then build capacity.

4. Learn locally, upgrade globally. Each node should collect data and conduct ongoing analytics to help every other node improve. The network becomes more valuable as the system collects proprietary production data and insights.

The Road to Mars

Edge Scaling matters wherever traditional supply chains encounter friction: excess inventory, rigid logistics, long lead times, fragile sourcing or insufficient customization. Disney partnered with Haddy because traditional manufacturing could take months to deliver custom pieces for theme parks and Broadway shows. Haddy delivered them in days, with greater flexibility and almost no waste.

If Belvisi and her space-race colleagues are right, our descendants will eventually Edge Scale on Mars. For now, urgent opportunities await here on Earth.

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