
Gradient Dissent: Conversations on AI
Hosted by Lukas Biewald
Written by a model from the transcript; not yet reviewed.
This episode of Gradient Dissent features Drew Baglino, former senior executive at Tesla and founder of Heron Power, discussing his career building electric vehicles, energy storage systems, and the future of the electrical grid. Baglino shares behind-the-scenes stories of working closely with Elon Musk, explaining how extreme constraints and the separation of ego from engineering work drove innovation and massive scale at Tesla. The conversation shifts to the grid, power electronics, and the rising demand for electricity driven by AI data centers, which Baglino argues can ultimately make power cheaper and more stable.
Listeners will gain a rare insider perspective on the engineering philosophy that built Tesla, alongside a clear, accessible explanation of electrical infrastructure and solid-state transformers. Baglino breaks down complex material science topics like wide-bandgap semiconductors and explains why data centers are actually desirable utility customers. The discussion offers a refreshing, technically grounded look at the energy transition, moving past common media narratives to examine the real physics and economics of power generation.
The episode opens with a brief technical explanation of data centers, followed by the host introducing himself and the guest, Drew Baglino, and outlining the conversation’s focus on energy and AI.
Baglino recounts his Stanford days, early connections with Elon Musk, and his transition from a think‑tank to Tesla’s embedded DSP and powertrain teams.
Baglino describes a pivotal meeting where Elon set an impossible battery cell target, forcing the team to innovate in motor efficiency and cell density.
He explains the importance of separating personal ego from product work, the role of strong leadership, and how this culture shaped Tesla’s rapid iteration and problem‑solving.
Baglino shifts focus to Tesla’s autonomous driving ambitions, the transition to energy solutions like Powerwall, and the broader vision of electrification.
Discussion of rising AI workloads and the resulting increase in data center power consumption.
Exploration of why California’s retail rates are high yet average household bills remain moderate.
Explanation of how utility business models and a lack of load growth have led to a calcified supply chain.
Analysis of California’s net‑metering policy and its impact on utility revenue and consumer rates.
Introduction to wide‑band‑gap materials and how they enable faster, more efficient power electronics.
Overview of Heron’s product that reduces transformer volume by 100× using power electronics.
Description of how high‑frequency transformers shrink size and improve grid flexibility.
First Interaction with Elon Muskstory
Baglino recounts his first meeting with Elon Musk when proposing battery cell counts for the Model S, where Musk arbitrarily demanded a lower number that forced the team to innovate.
Checking Your Ego at Doorinsight
Explaining why engineers burn out, Baglino argues that separating ego from work is essential for accepting feedback and rapid iteration.
The Reality of Production Hellstory
Baglino shares the famous story of removing a problematic desiccant installation robot during Model 3 production hell, illustrating how questioning every part drives efficiency.
Solid-State Versus Mechanical Switchgearinsight
Baglino explains how wide-bandgap semiconductors allow the electrical grid to switch high voltages instantly without heavy mechanical switches.
Scaling Down Power Transformersdata
By converting power at hundreds of kilohertz instead of 60 hertz, Heron Power's solid-state transformer shrinks the component size by a factor of 100.
Data Centers as Grid Assetsinsight
Contrary to popular belief, Baglino explains why data centers are ideal utility customers that can actually drive down electricity costs through high, steady usage.
“You take a gigawatt of power and you convert it into 700 megawatts of heat.”
“We can reduce the loss from grid to chip by about a factor of two.”
“I think that's actually probably one of the hardest things for engineers, especially in high‑paced companies to do, is to accept that what they just spent the last three months on might get torched, and for really good reason.”
“The data centers are the best customers.”
“Because the efficiency of compute kept improving dramatically.”
“The denominator got a lot smaller or didn't grow.”
“The power of power electronics.”
Can today's power grid handle the explosive growth of AI data centers? Tesla Alum Drew Baglino https://www.linkedin.com/in/baglino/, now founder & CEO of Heron Power https://www.linkedin.com/company/heron-power-electronics/, doesn't think so. In this episode, he joins Lukas Biewald https://www.linkedin.com/in/lbiewald/?skipRedirect=true to talk about why scaling compute requires a fundamental overhaul of grid-to-chip infrastructure, not just bigger power plants. They cover how Heron Power raised $140M to cut power losses in half, shrink massive oil-filled transformers by 100x, and unlock 35MW of extra compute for every gigawatt data center, and what that means for the future of AI energy efficiency. Connect with us here: Drew Baglino https://www.linkedin.com/in/baglino/Heron Power https://www.linkedin.com/company/heron-power-electronics/Lukas Biewald https://www.linkedin.com/in/lbiewald/?skipRedirect=trueWeights and Biases https://www.linkedin.com/company/wandb/posts/?feedView=all
16,202 words · 2 speakers
Speaker names marked are inferred from speaking time and the show’s known hosts — they are not voice-verified.
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