Industrial Base Hackathons: An Underwriting Layer for Reindustrialization

How visibility, aggregation, and coordination become leverage.

Anhthu Nguyen

Jan 15, 2026

The Capitol to the Heart of the Industrial Base

DC marble floors to Detroit hard steel in 24 hours.

From policymakers and primes to machinists and manufacturers.

At the top of the supply chain:
“We don’t have capacity.”

On the ground:
“We do. Just no time to market it.”

I made many similar trips across cities in America over the past few months.

One week, I was in factories with founders.

The next, in high-rises with private equity firms and family offices.

Those startups were building the first domestic alternatives for materials in energy, defense, and transportation.

Materials that are still 60–90% imported today.

At least until China’s last round of export restrictions.

Yet they were struggling to secure funding, even as demand far outpaced supply.

Meanwhile, many of the investors in those rooms either believed America’s innovation had peaked—or were searching for the next Anduril without real access to where that innovation is actually forming.

Both camps often ask where to deploy capital next.

That’s when I realized the problem isn’t capacity.

It’s the absence of a shared view of reality.

And coordination.

An Idea

What I’ve found since is that progress is often much simpler than it sounds.

Sometimes it’s as straightforward as introducing five drone startups struggling to find testing sites within a year to two facilities already certified to support drone testing operators.

It could be connecting two think tank leaders working independently toward the same financing policy.

Other times, it’s listening to a munitions manufacturer explain the constraints of producing key components—then carrying that perspective into the next call with government actors, who pause and admit they’ve never considered the problem from the builder’s point of view.

These moments add up.

They make clear that accelerating reindustrialization requires moving faster than traditional programs allow—and directing capital with far more precision than we do today.

So I floated an idea.

“What if we had hackathons, not for code, but for rebuilding America's industrial base?
What if we convened tiger teams of industry, academia, trade associations, investors, and government across the country to hammer out the real bottlenecks we keep hearing about—across regulation, procurement, workforce, technology, policy, and capital?
Even if all we did was leave each session with a precise list of problems and solutions to hand directly to government, industry, and investors, we could start fixing them immediately.
And if those teams tied back to a central source, we could build on one another’s progress—sharing solutions, compounding insight, and avoiding the trap of solving the same problems in silos.

That idea drew significant inbound.

So a national series was built around it.

Industrial Base Hackathons

A mechanism for accelerating reindustrialization by identifying and resolving bottlenecks to collapse timelines across America’s industrial base.

And behind it, there is a larger plan.

Hackathons as the Underwriting Layer

America is not short of ideas or capital.

What we lack is the infrastructure to see which businesses and innovations are most impactful, to form and route capital into the industrial base at scale.

Without that visibility, trillions of dollars either stall inside bureaucracy or flow blindly to the wrong places.

And to win the energy and AI race—which is now a global race for power—we have to reindustrialize at speed.

So I wrote a plan for that.

It is demand–supply chain management funding infrastructure that makes industrial businesses and startups bankable—using industrial base treasury bonds and mobilizing private credit to route trillions of dollars directly into the heart of America’s industrial base: innovative startups and small and mid-sized industrial businesses foundational to our most critical supply chains.

The problem is that no one knows where those true chokepoints are.

So that plan calls for these next steps toward identifying that.

Key Milestones & Timeline

Assemble a $1 trillion purchase-order-book – 6–9 months
Stand up new Office of Strategic Capital (OSC) units and qualification infrastructure – 6–9 months
Deploy data & analytics layer for purchase order verification and real-time underwriting – 6–12 months
Launch guarantees and credit insurance programs – 6–12 months (faster if leveraging existing authorities)
Secure congressional approval for capital channels, OSC structures, and bond issuance – 12–16 months

Industrial Base Hackathons execute the foundation of the first three steps.

They function as the underwriting layer—qualifying where capital should go, policy must change, and resources can practically move the industrial base in the real world.

On December 10, 2025, Ad Astra Group co-hosted our first Industrial Base Hackathon in Austin, Texas with Oracle, Texas Nuclear Alliance, and Exodys Energy.

The First Industrial Base Hackathon

The day started rough.

We kept the pilot small by design.

A hybrid format to test team dynamics.

That decision came with consequences.

Tech broke. Remote participants missed entire discussions.

People stared at their bottleneck lists. Then at each other.

A few slipped out the door.

By midday—deflated and irritated that there wasn’t cell signal in the bathroom to text my friends crying emojis—I was genuinely questioning whether Industrial Base Hackathons were the right mechanism at all.

Then we forced a shift.

More facilitation. More surgical questions.

Instead of asking teams to “solve the problem,” we pushed them to identify where the system actually breaks, the exact point where a process stalls, a handoff fails, or an incentive misaligns.

That’s when everything changed.

As the work dropped from abstraction to process-level constraints, conversations sharpened. Assumptions were challenged. Debates got heated—in the best way.

Teams stopped talking about how the industrial base should work and started mapping how it actually works.

In those details, leverage points emerged—the kind that, if addressed, collapse timelines instead of extending them.

By the end of the session, the answer was clear.

The model works.

What sealed it wasn’t my internal exhale.

It was the feedback, from long-time operators and newcomers across industry and government, saying the same thing:

“This was useful. And we need more of it.”

And that was before they saw the patterns that emerged.

Two Unexpected Key Findings

The usual suspects showed up across all teams: capital access, workforce shortages and regulation challenges.

As we dug deeper, it became evident that those were only symptoms of the deeper issues at hand.

What emerged was a cascading failure of shared visibility—reappearing within industries, across domains, and again inside individual programs.

Finding #1: Visibility Gaps are the Bottleneck

Across the room, teams kept running into the same constraint: they couldn’t see the full picture and they didn’t know many who could.

Three visibility gaps surfaced: opaque supply-chain dependencies, narrative distortions around nuclear deployment, and the absence of a shared workforce baseline.

1. Opaque Supply Chains and Dependencies

Unmanned Aircraft Systems Team

A former Anduril and Lockheed Martin operator:

“The next step in trying to get our arms around this really opaque problem of supply chain is we don’t know our dependencies on our adversaries. There are very well-known ones, like rare earth minerals, steel, and other ones we all know, but it’s not just raw materials. It’s also technologies, like manufacturing technologies, different processes that they know how to do that we don’t. Or services, different things, like heat treating, types of lithography, other technologies that we need to get to the bottom of, and ascertain a list or an article that publicizes that. America’s supply chain weak points.”

Why this matters:
The bottleneck isn’t just sourcing, it is unmapped capability dependencies buried deep in the supply chain.

2. Nuclear Narrative and Deployment Visibility Gaps

Energy/Rare Minerals and Materials Team

A Texas nuclear ecosystem leader connected across industry and policy:

“There’s plenty of activity happening upstream. I would say this is almost a narrative violation on we are lacking rare earth minerals, materials, and uranium. The reason I say it’s a narrative violation is because a lot of those things are underneath our feet. We can find them in North America, if not exactly the U.S, Canada, and also in Texas alone. Texas specifically for uranium. We have massive reserves of uranium that can be mined. But, now, downstream of the supply chain: where and what is really, breaking all of this apart? Stalling or the wall that we’re hitting? It’s somewhere between the OEMs right before they actually deploy.”

Why this matters:
Misplaced narratives obscure where friction actually occurs—leading capital and policy to target the wrong part of the system.

3. Workforce Baseline Data and Information Distribution Gaps

Workforce Team

An academic-industry leader who led a comprehensive nuclear workforce mapping effort approved at the state level:

“…if you even just want a quantitative assessment of what the market needs for one specific industry that’s emerging, like nuclear, good luck right now.”
“We keep talking about centralization, everything all over the country and everywhere else, it’s just… nobody’s talking to each other, so you need to find a way that, that information gets out to as many people as possible.”
“And frankly, we don’t have a known reality baseline of what the problems are, really, and how we would integrate them between each other. Which is why the bottleneck is so hard to communicate for all of them. But that also is a pathway, then, for a solution, right?”

Why this matters:
Without a shared baseline, workforce planning becomes guesswork, redundant and coordination breaks down before it starts.

The Pattern

Across teams, industries, and domains, the same pattern emerged:

The bottleneck of all major bottlenecks is the absence of shared, actionable visibility.

Not surprisingly, the second pattern that surfaced across every group was the same response: a need to create that visibility—systematically, at scale.

Finding #2: Aggregation Changes Behavior

By the end of the day, teams weren’t just sharing solutions.
They were independently converging on the same structural move: aggregation.

Across domains, the proposed solutions took the same shape, pulling fragmented demand, supply, capabilities, or data into a shared, visible layer.

Unmanned Aircraft Systems
- Demand/Component Aggregation: Aggregate demand for common UAS components—batteries, radios, ESCs, motors, flight controllers—via a brokerage or startup model.
- Supply Chain & Supplier Database: Make opaque dependencies explicit by cataloging suppliers and weak points, informing bulk purchases and targeted capital to fill gaps.
- Shared Infrastructure / Makerspaces: Create a brokerage for access to 3D printers, electronic materials, makerspaces, and university facilities.
Workforce
- Workforce & Training Aggregation: Establish a center of gravity that pulls together fragmented community colleges, universities, and training programs to scale high-quality local capacity.
Munitions Manufacturing
- Precursor & Chemical Database: Aggregate precursor and chemical demand across government programs into a shared database, paired with supplier visibility.

We’ve long intuited that aggregating fragmented information doesn’t just improve analysis—it changes how stakeholders understand the ecosystem.

And that shift in understanding alters behavior.

When information is aggregated, investors can ask better questions, agencies escalate faster, and operators stop duplicating work—because context emerges and relationships between pieces become visible.

Aggregation → Visibility → Narrative → Coordination

One team’s work made this especially clear.

Deep Dive Case Study: Munitions (Proof)

War games conducted by the Center for Strategic & International Studies, cited that if we went to war with China today, the U.S. would run out of core munitions, in only seven days.

So we made munitions manufacturing for drones one of the bottlenecks we looked at. This group surfaced a practical constraint—one that turned out not to be rare minerals, funding, or even manufacturing capacity.

At least not in the way most people assume.

A simple question:

“Where are we seeing the longest lead times?”

A Y-combinator linked explosives startup co-founder answered immediately:

“Precursors.”

A memory crossed my mind from months earlier, when a friend at the Naval Nuclear Lab voiced frustration about America’s severe shortage of essential chemical “core builders.”

Then a leading munitions steel producer echoed that same challenge. So did the downstream component manufacturer.

“Does this fall under rare minerals and materials?”

These precursors are not mined materials. They are chemically synthesized or biologically produced intermediates, often made by a handful of specialized domestic suppliers using tightly controlled processes. Losing capacity for them can take years to rebuild, requiring deep process knowledge, specialized equipment, and significant capital.

But the near-term solution here wasn’t new facilities.

The team pointed out that alternative domestic precursors already exist with greater availability. Yet, requests to qualify and use these substitutes routinely get rejected or ignored across different government programs. The same substitution proposals are often submitted repeatedly by different suppliers for similar systems, only to go through redundant evaluation cycles in separate channels.

Another team member, formerly at Tesla and now with visibility across hundreds of precision manufacturers in America, affirmed the same experience.

The problem was that precursors require deep process-level expertise—expertise that often doesn’t exist at the individual program level.

So how could we expect each program to effectively evaluate alternative materials?

“How many precursor request types are we talking? Thousands or millions?”

Tens of thousands. And when we dug deeper, the number of avenues could be hundreds or thousands.

That scale is unmanageable for humans.

But it’s exactly the kind of problem data systems are designed to handle.

What we uncovered was that these requests were arriving through systematically identifiable avenues from individual program offices to centralized defense agencies responsible for logistics, contracting, and compliance.

All of these avenues could be pooled into a central data repository at a level overarching all service branches. At a level that could be properly staffed with the right talent focused solely on general precursor evaluations, streamlining visibility and coordination. This repository could be further strengthened by integrating the Department of War’s supplier database, tracking records from the office of Imports, pulling in industry groups, consortia, academic labs, crowdsourcing from industry with incentives, etc.

“Would this work?” I asked hopefully.

“Yeah actually, this would make a big difference and save a lot of time across programs and suppliers.”

A single day in one room surfaced a mechanism that could potentially cut weeks, months, or even years off critical timelines—simply by reorganizing information and expertise that already exist.

But the most important takeaway?

This munitions example illustrates a broader pattern likely repeating across other supply chains. Long-lead precursors and specialized intermediates sit far upstream, yet they remain poorly mapped, under-financed, and uncoordinated. Making their dependencies visible can shift narratives, unlock existing regulatory flexibility, and redirect capital and policy to where it matters most.

Imagine applying the same aggregation and evaluation infrastructure not just to precursors, but to rare minerals, specialty materials, components, and processes across the industrial base.

Can We Talk More About Precursors?

There are likely many “precursors” in our ecosystem.

We have a precursor sequencing narrative problem.

Across innovation and production lines that keep our everyday lives running, long-lead-time precursors are a chokepoint. The diagram below illustrates how these precursors underpin downstream materials, components, and finished systems that many stages of the industrial base depend on.

New precursor facilities often carry lead times of 10–15 years and are just as important as minerals and materials in shaping supply-chain resilience. Yet they are frequently misunderstood or overlooked—treated as downstream inputs or assumed to be synonymous with minerals and materials.

I also made that assumption.

In reality, precursors are defined by unique tooling, chemistry, process knowledge, and sequencing constraints.

Sometimes, simply making these dependencies visible is enough to change a conversation and direction.

We recognize what we can surface allows others to shape.

The data we collect feeds into a knowledge graph that creates a shared mental model aligning industry, capital, and government.

Why Hackathons?

Different parts of the system surface different truths.

A factory savant who ran Tesla’s general assembly might argue that bulk access to hydraulics and servo valves is the fastest way to unlock production across defense and manufacturing. An executive at a global industrial automation company may insist the real constraint is composites. While a government technology liaison could be focused entirely on logistics.

And they’re likely all right.

The challenge isn’t choosing which perspective matters. It’s understanding which constraints, when addressed, unblock the most downstream paths.

Even when government actors ask which banking regulations to adjust or which supply-chain risks deserve priority, the honest answer is often the same: it’s hard to know. There are simply too many variables to assess in isolation.

When operators, industry leaders, and government actors are convened across sectors and domains—old and new, public and private—patterns begin to surface. Recurring failure points that consistently slow America’s supply chains.

That is why we convene hackathons.

We are building the underwriting infrastructure that sources, qualifies, and de-risks the industrial businesses that—when properly capitalized—can expand capacity and collapse timelines across America’s industrial base.

From Insight to Execution

But what good are insights if they are not operationalized into reality?

What we’re seeing from just one hackathon:

A consultant advising defense tech startups shared that a munitions testing range—closely aligned with what our munitions manufacturing group proposed (more details in our full report)—is already underway in Texas due to demand, confirming the team independently arrived at a real-world bottleneck already moving toward resolution.
One attendee shared a state-approved nuclear workforce plan she had personally mapped. We are now in early conversations about conducting a Texas-focused case study and tying in our friends in New York and California close to similar state level efforts there, exploring what it would look like to work on this together.

At the same time, accelerators, coalitions and investors were asking for more than analysis. They were requesting investable ideas and founders—from multigenerational family offices to private equity firms telling us, directly, to bring them the deals.

The hackathons provide a structured way to answer those questions with real-world contextualized data.

This points to conversion beyond just insight.

A Supply Chain Ecosystem Knowledge Graph

As any good story shows, insights travel further through visualization.

We build programs and entire businesses around plans and schedules.

Why is rebuilding America’s industrial base much different?

Hackathons aggregate people and create data.

Data that must be converted to a shared map or knowledge graph—creating a durable source of truth that reduces redundancy, compounds over time, and enables a shared view for sustained, coordinated action.

This will begin to take more shape as our hackathons progress.