May 13, 2026 · 23m · a16z
The Founders Who Left Tesla to Rebuild America | a16z
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gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions
In this a16z panel, former Tesla leaders Turner Caldwell (Mariana Minerals) and Drew Baglino (Heron Power) explore how software, solid-state power electronics, and high-speed execution are essential to rebuilding America's critical mineral refining, power grid infrastructure, and industrial capacity for the AI era.
How this conversation actually went
Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. How this is scored →
The host as informed peer 2.6 Guest teaching 3.1 Guest disagreement 0.1 The host pushing back 0.6
speaking balance: gold is the host, purple is the guest (3 minute bins)
Sharpest disagreement ▶ 6:46 Turner rejects conventional policy focus on permitting alone
Turner forcefully argues that top-level policy fixes like permitting reform do not solve the fundamental execution slowness of building and ramping mineral capacity.
Hardest push from the host ▶ 10:22 Host presses guest on labor cost objections in US manufacturingThe host explicitly pushes back against optimistic timeline assumptions by bringing up industry arguments regarding domestic labor costs and talent shortages.
Biggest teaching moment ▶ 10:33 Drew breaks down actual COGS metrics in modern automated factoriesDrew corrects popular assumptions about labor cost barriers by explaining that automation reduces labor to under 5 to 10 percent of COGS, making co-located supply chains the true competitive driver.
The host holds their own ▶ 18:40 Host demonstrates deep topic research with exact company figuresThe host proves strong command of the guests' business plans by citing specific workforce expansion numbers across their respective Texas and Utah facilities.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | The host as informed peer | Guest teaching | Guest disagreement | The host pushing back | Why |
|---|---|---|---|---|---|---|
| Host Keynote: AI Dominance as a Physical Project | 3 | 1 | 0 | 0 | The host opens with an extended keynote framing AI dominance as an energy and physical infrastructure problem before introducing the guests. The host demonstrates thematic framing expertise but does not press or challenge the guests during their initial company overviews. | |
| Geopolitics, Supply Chains, and Outpacing Competition | 2 | 4 | 1 | 1 | The host prompts guests on geopolitical reliance and interjects briefly to clarify if being 'behind' means specifically relative to China. Turner schools the host on the realistic timelines of minerals development, pointing out the US is 50 years behind. | |
| Modernizing the Electrical Grid and Industrial Execution | 3 | 4 | 0 | 2 | The host brings up the common industry objection around US labor costs and shortages holding back manufacturing. Drew educates on modern automated factory economics, showing labor represents under 10 percent of COGS. | |
| Autonomy and Software Integration in Mineral Processing | 2 | 4 | 0 | 0 | The host sets up the distinction between extraction and processing of critical minerals. Turner schools on the necessity of reinforcement learning in refineries due to operator shortages and organizational cultural inertia. | |
| The Tesla Playbook for Rebuilding American Industry | 2 | 3 | 0 | 0 | The host asks comparative questions about how Tesla's operational playbook differs from traditional industrial conglomerates. Both guests share detailed internal perspective on startup urgency versus legacy corporate culture. | |
| Sourcing and Building an Industrial Workforce | 4 | 3 | 0 | 1 | The host demonstrates preparation by citing exact job creation figures (500 construction/factory jobs each) for both guests' upcoming builds. The guests explain how they cross-hire from adjacent industries like high-speed bottling and oil fields. | |
| Actionable Policy Asks for American Industrial Growth | 2 | 3 | 0 | 0 | The host solicits actionable policy recommendations to close the episode. Drew proposes a novel federal trust fund for grid infrastructure, providing policy insight while the host listically moderates. |
Statements from this episode (17)
Caldwell: US is 50 years behind on critical mineral supply
“The US is 50 years behind on critical mineral supply.”
Caldwell: Mariana Minerals uses reinforcement learning to automate mineral refineries
“We're making a big bet on autonomy and refineries, where we use reinforcement learning to actually remove humans from the loop in determining how refineries operate.”
Baglino: World's leading silicon carbide producer is US-based
“The world's leading producer of silicon carbide, which is a key power semiconductor, is based here in the U.S.”
Caldwell: Mariana Minerals aims to build 10 projects in the next decade
“We're building a lithium refinery in Texas with the goal of building 10 projects in the next 10 years.”
Baglino: Heron Power builds solid-state transformers to replace traditional grid materials
“At Heron Power, we're focused on building solid-state transformers to use silicon and software to replace steel, oil, and copper in power conversion at data centers, large-scale energy installations like solar and battery projects and others.”
Caldwell: Mineral facilities take up to 10 years to reach capacity
“Once you start building, it can take five years to get something built, and then it can take three or three to five years to get something actually operating at rate.”
Baglino: Tesla built the Lathrop Megafactory in 11 months
“I built the mega factory with my team. You know, my team was super awesome. Hello in Lathrop, California in 11 months. It was a JCPenney warehouse. 11 months later, the first product came off the line.”
Baglino: US-China factory labor differential is under 10% of COGS
“Yeah, I mean, these, today's factories are really automated. If you're building a new factory today, you know, in China or the U.S., the labor differential is less than 10% of cost of goods sold. It might even be less than five percent.”
Baglino: All 7,000 car parts are within 3 hours in China clusters
“If you look at, you know, China, they are so thoughtful about building these industrial areas, you know, everything that you could possibly need to build a car which has 7000 parts in it, you know, is within less than a three hours drive.”
Caldwell: US lacks labor pool required to operate critical mineral refineries
“And we don't have that labor pool here that has that embedded know-how that can walk up to a refinery and quickly get it operating on spec, and then also manage that variability.”
Caldwell: Operating teams, not technology, limit software penetration in industrial plants
“The gate to software penetration, really not the gate, what sets the rate of software penetration and technology penetration into these plants and into these mines ultimately is the operating teams.”
Caldwell: Co-locating plant operators with software engineers beats forward-deployed models
“Sitting the software engineers right next to the operating teams, but Not in like a forward deploy engineer type way where everyone has the same incentives is what's going to yield the best results when it comes to trying to optimize these assets.”
Caldwell: Legacy mining companies abandon autonomous tech projects after short failures
“And I think what we see, at least in, in, in the minerals industry, is, like, folks will give it a shot for a year. You know, people have tried to do autonomy and mining for a long time. And generally a lot of companies will just end up, you know, they'll fail…”
Baglino: Existential urgency drove Tesla's peak team performance
“Many times in Tesla's history, You know, the company's future success, really, like, whether or not the paycheck will clear, you know, was bet on the team within the company executing well. And that is a very, like, focusing reality. And it drives people to do…”
Caldwell: Mining industry faces 35 years of labor pool attrition
“It's the, you know, for the mining industry, we're in a similar position where we're kind of, we've had 35 years of just meaningful attrition in the labor pool.”
Caldwell: Industrial refining algorithms match consumer tech software models
“And the software space you know, a lot of the underlying optimization algorithms that we're writing for our plants, they look very, very similar to the optimization algorithms that are in dog walking apps and Uber ride optimization underwriting loans ad optimi…”