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About Deeptech Decoded: Frontier Builders | AI | Product Taste
Kitchen-table conversations with builders at the deep-tech AI frontier. No script. No filters. The reasoning behind the moves: what's working, what's not and why conviction beats consensus. For those building what doesn’t have a manual. Deep-dives → https://deeptechdecoded.substack.com/
- Publisher
- Nihal Kurth
- Category
- technology
- Language
- en
- Explicit
- No
- First episode
- 3 Oct 2025
- Latest episode
- 28 Aug 2026
Latest episodes
14 episodes in the feed.
28 Aug 2026
Rocket Cargo Anywhere In 15 Minutes. The U.S. Air Force Is In. | Matija Milenovic, Hop Aero (YC S26)
Matija had 24 hours to get a satellite propulsion system across the world. FedEx couldn't guarantee it. UPS couldn't either. So he got on a plane and delivered it himself. 23 hours, round trip. Jacob, his co-founder, hit the same wall from a different direction. He was a marine during Typhoon Haiyan, tasked with getting life-saving supplies of medicine and food to people fast. Aircraft kept breaking down, parts weren't in stock, pilots were exhausted. The supplies got there late. Different problems, same wall: nothing fast enough existed. Not for a startup, not for the US military. So they built it. Hop Aero builds autonomous hypersonic cargo rockets. 250 kg, up to 750 km, in about 15 minutes. Most urgent logistics still runs through airports, runways, slow last-mile handoffs, or cargo sitting in orbit waiting for a window. Hop Aero's bet is simpler: launch from a 40-foot shipping container, fly point-to-point through a suborbital arc, land vertically on ground that was never built for landing. In this episode, Nihal Kurth sits down with Matija Milenovic, co-founder and CEO of Hop Aero. They get into why time-critical logistics breaks down in both military and commercial settings, how a prototype catching fire turned into the real test of a co-founder relationship, and why Hop Aero optimizes for door-to-door speed instead of just flight speed. They also cover why drones fail at long-range contested logistics, how Ukraine changed the cost and availability of autonomy hardware, why Hop Aero built its own internal engineering system, Hop OS, and what it actually takes to build a defense hardware company in the US instead of Europe. Learn more about Matija: https://deeptech-decoded.com/guests/matija-milenovic Chapters: 00:00 - Intro 00:45 - From porkchop to Hop Aero 04:52 - The prototype fire that tested the co-founders 08:01 - Jacob's Marine Corps origin story 09:46 - The 23-hour delivery run 14:06 - How point-to-point rocket cargo works 19:34 - Launching from a 40-foot shipping container 21:23 - Autonomy lessons from Ukraine 23:35 - 3D printed engines and Hop OS 28:53 - Build vs buy in hard tech 31:15 - Supplier failures and startup reality 34:40 - Why drones are not enough 39:15 - The cost curve for rocket cargo 40:34 - Team grit as the real moat 42:37 - Co-founder dynamics under pressure 46:09 - Door-to-door speed as the core metric 47:21 - Orbital cargo vs direct launch 50:11 - Working with Air Force Research Labs 51:14 - Scaling production and reusability 52:19 - Why Hop Aero tests in Oklahoma 55:28 - Building defense hardware in the U.S. vs Europe 58:09 - Why porkchop sold its IP 1:01:00 - Advice for young founders 1:05:07 - The consensus bet that failed 1:07:05 - Closing
14 Aug 2026
40X Smaller Nuclear in 24 Months? Inside Apollo Atomics’ Abundance Bet | Assil Halimi (YC P26)
Nuclear power is undergoing a massive renaissance. While everyone is trying to reinvent nuclear from scratch with exotic fuels and unproven coolants, Apollo Atomics proved you only need to fix ONE 120-year-old component to make reactors factory-built and transportable. Case in point: three reactors, each on a truck, each for a different customer segment. The A-10 (10 MWe), the A-50 (50 MWe) and the A-300 (300 MWe). Ready to deploy.Apollo Atomics took the pressurized water reactor, the same technology running roughly 80% of the world's nuclear plants, and changed exactly one component: the steam generator. That single change shrinks the reactor 40x and turns what's normally a 10-year construction project into a factory-built machine deployable in under 24 months.In this episode of Deeptech Decoded, Nihal Kurth sits down with Assil Halimi, founder and CEO of Apollo Atomics (YC). Assil spent his PhD at MIT asking one question: what is the single design choice that unlocks the fastest, cheapest path to deploying nuclear power?Together, they walk through why nuclear is still the most energy-dense source available, why public safety data doesn't match public perception, how Apollo tests component reliability without waiting a decade, and why the biggest risk to a deep-tech company isn't the physics, it's scaling the team without breaking what works.Learn more about Assil:https://deeptech-decoded.com/guests/assil-halimiChapters:00:00 – Intro08:24 – Why nuclear is the densest energy source10:44 – The real safety data behind nuclear11:40 – Chernobyl vs. Fukushima vs. PWRs13:56 – Passive safety, built into the design18:16 – How a nuclear plant makes electricity24:47 – Building reactors in a factory, not on-site26:57 – Why plant size drives the cost29:29 – Changing one component, not the reactor34:11 – The four layers of cost reduction37:48 – Turning coal plants into nuclear plants38:13 – The biggest risk: component reliability41:37 – Testing reliability without a decade to spare46:18 – 300 megawatts on a single truck47:22 – Why customers pay a premium for reliability51:16 – Executive orders cutting NRC review time57:29 – The supply chain concentration risk1:04:10 – Decoupling power from cost1:07:47 – What could actually break Apollo Atomics1:15:15 – From solo founder to YC1:26:37 – The 10-15 year goal for nuclearWhere to find Assil:LinkedIn → https://www.linkedin.com/in/aahalimi/X→ https://x.com/AssilHalimiWhere to find us:Substack → https://deeptechdecoded.substack.com/LinkedIn → https://www.linkedin.com/company/deeptechdecoded Spotify → https://open.spotify.com/show/5c2T63GUqlDwQO2RIYCxfY?si=17b199ed1a40496bApple Music → https://podcasts.apple.com/gb/podcast/deeptech-decoded-frontier-builders-ai-product-taste/id1851406220
31 Jul 2026
Why Pure Software Is Uninvestable: The SpaceX & YC Way to Build Hardware | Jamie Gull DD #12
Boeing took weeks to change one number on a drawing. He left and never looked back.Jamie went from a public school in the Colorado mountains to Stanford, then to Scaled Composites at 24, running the booms, tails, and control surfaces on an aircraft that was flying in nine months. Then SpaceX, where the responsible engineer culture meant you owned your part from design through the shop floor, and nobody needed four signatures to spend $300. Now he invests in the hardware companies most VCs still can't underwrite.We get into what actually made SpaceX fast (a brutally high hiring bar, and no fence to throw work over), why the team zip-tied GoPros inside the rocket instead of waiting for a flight camera system, and what Elon does when a program becomes the bottleneck. Then the investor side: why LOIs have been diluted into noise, what a real one looks like, and the single signal Jamie trusts most in an early hardware team.He also explains, with numbers, why he passed on space-based data centers, and why the humanoid robot company in his portfolio might be worth a fortune on a single customer contract.Jamie is a former SpaceX and Scaled Composites engineer, an early advisor to Boom Supersonic, and now runs his own hardware-focused VC fund. Learn more about Jamie: https://deeptech-decoded.com/guests/jamie-gull
21 May 2026
Inside Deep Tech Investing: A Masterclass From Both Sides of the Table | Graeme Harrison
What if AI's binding constraint isn't smarter models or faster chips - but the megawatts sitting unused inside regulated utilities in every major city?Graeme Harrison, General Partner at Augur VC and Founder & CEO of Simply Silicon, has spent years betting that energy, not compute, is the real bottleneck for AI. Augur was incubating against an "energy AI" thesis before the term "NeoCloud" existed. Simply Silicon, the operating company that emerged from Augur's dealflow, is now building the world's first air‑gapped inference networks for major North American cities - a category of one, for now.Their first site is a regulated district heating plant in downtown Calgary with 12 MW of unused electrical capacity - the kind of deal Silicon Valley money alone could never close. On the fund side, Augur has been first into companies like Beyond Reach Labs (cold‑emailed pre‑demo‑day for an uncapped SAFE), Aero Volta, and Cumulus, underwriting outliers against a worldview Graeme calls "technological determinism."Graeme spent nearly a decade doing technology M&A at Bennett Jones in Canada before launching Augur. He built his first company - Quest Websites - in mid‑90s Saskatchewan as a kid, got wiped out years later on an electronic cigarettes import business when a regulatory change seized his inventory, and went to law school to learn the commercial backbone of how the world actually runs. In 1999 he read Ray Kurzweil's The Age of Spiritual Machines, and that book has quietly directed every choice he's made since. In this episode, we explore:- Energy as the Binding Constraint: Why the AI infrastructure race is going to be won by whoever solves power, not compute.- The Cold Email to Beyond Reach Labs: How Augur wrote an uncapped SAFE before demo day and why the founders said yes.- Technological Determinism: Augur's underwriting model - civilizations unlock technologies in a fixed sequence, and the next ones are knowable.- "The Internet Wasn't Built for This": Why current data center architecture can't deliver what regulated enterprises need from AI inference.- The Calgary District Heating Deal: How Simply Silicon co‑locates inside a regulated utility - and why Silicon Valley capital alone can't open that door.- The Death Spiral of Venture Capital: Why generalist VCs reject the deals worth doing, and what conviction‑led underwriting looks like instead.- Don't Die: The Y Combinator rule Augur leans on through portfolio inflection points - and the "teardrop" founder who said no to an early acquisition.- Plus a cameo from Mikey: hired into Augur at 18, now running investor tours at Simply Silicon at 20.Learn more about Graeme:https://deeptech-decoded.com/guests/graeme-harrisonTimestamps:0:00 - Designing the conversation: identity, two roles, Beyond Reach1:05 - Ten years of tech M&A at Bennett Jones2:03 - The electronic cigarette business that wiped him out4:59 - From Quest Websites to law school: learning how the world runs7:16 - Wearing two hats: Augur VC and Simply Silicon9:27 - Ray Kurzweil and the energy‑AI North Star10:43 - Dan Chapman and building the Augur team13:43 - Technological determinism and the Kardashev scale17:23 - The Beyond Reach Labs investment story22:11 - The cold email that became an uncapped SAFE24:35 - $325M in LOIs by demo day25:17 - What was actually on the investment memo27:47 - Investing vs. building: which would Graeme pick?29:44 - Simply Silicon emerges from Augur's dealflow31:31 - Why the internet wasn't built for AI inference36:00 - Recruiting an inference engineer out of AMD40:09 - Inside the Calgary district heating plant deal44:52 - What makes founders pick Augur over bigger checks47:30 - The "teardrop" founder who said no to an acquisition50:49 - Don't die: Y Combinator's most important rule57:00 - Token‑maxing, patent‑maxing, and broken VC incentives1:02:45 - Spotting an 18‑year‑old outlier1:13:00 - The book that gave Graeme his North Star
7 May 2026
Football Field Size Solar Arrays That Fold Into a Rocket | Pele Collins, Beyond Reach Labs (YC W26)
What if the biggest structures humans ever build aren't on Earth - but folded into a backpack and unfolded 50x larger in orbit?Pele Collins, co-founder & CTO of Beyond Reach Labs (YC W26), is on a mission to become the "big builder" of space. Their flat-pack origami mechanism delivers solar arrays up to 100 meters long, 88% cheaper than today's ISS-grade solutions — and it gets stiffer as it gets bigger, solving the floppy-array problem that limits satellite movement. Pele spent five years at SpaceX as the responsible engineer for the Dragon parachutes, led plasma-facing components at Commonwealth Fusion, returned to SpaceX to set up parachute manufacturing, and in October 2025 joined his Penn classmate Mitchell Fogelson — fresh from a CMU PhD on kilometer-scale NASA structures — to build Beyond Reach Labs.In this episode, we explore:- The 88% Cheaper Mechanism: A stamped-metal, flat-pack design that beats a $100M composite roll-up tube.- From Dragon Parachutes to Space Origami: Pele's path from SpaceX recovery hardware to deployable space structures.- "The Best Deployable Is No Deployable": Why simple wins in orbit — and why James Webb spooked the industry.- Bigger = Stiffer: The natural-frequency trick that flips the physics of large solar arrays on its head.- 2001: A Space Odyssey, But Real: The kilometer-scale, centripetal-gravity station behind the whole mission.- Vomit Comets and Tracking Dots: How you actually prove a deployable will work before sending it to orbit.- The Pivot That Saved the Company: From selling a simulation tool to designing and building the hardware itself.Learn more about Pele:https://deeptech-decoded.com/guests/pele-collinsTimestamps:0:00 Why Beyond Reach is more than what it looks like - meet Pele Collins1:25 South Africa → Penn → SpaceX: Pele's human-being introduction3:50 Legos, robotics, and the path to mechanical engineering5:07 Mr. Thompson, Mr. Bradley, and the physics teachers who set off a career8:00 Sports, soccer, and being named after Pelé9:30 Immigrant mentality - secure the basics, then take the swing12:18 Mitch Fogelson, NASA kilometer-scale structures, and founding Beyond Reach13:30 Y Combinator - and the treadmill since14:18 The space-economy explosion - and why James Webb is the inspiration17:18 The ISS took 80 launches - there has to be a better way22:43 Why solar arrays are the bottleneck of the space economy23:10 Floppy panels, first natural frequency, and why bigger is harder25:14 Thermal radiators and the heat problem of orbital data centers26:03 "The best deployable is no deployable" - the deepest law of space hardware28:00 88% cheaper than ISS-grade solar - the simple-is-best approach31:39 The $100M composite roll-up tube - and why it's overkill32:56 Silicon vs. triple-junction - the material trade-off bigger arrays unlock34:08 Where Beyond Reach is right now - prototypes, customers, milestones35:56 The first dedicated launch - early 202737:14 What keeps a parachute engineer up at night39:21 Testing in the Vomit Comet - zero-gravity flights with tracking dots40:25 Day one with a customer: how Beyond Reach designs to spec41:35 The 100-meter array, 150kW, and the limits of stiffness43:39 In love with the problem, not the solution44:28 Retractability - figure-skater physics for satellites46:58 The aha moment: customers wanted the hardware, not the software48:54 Patents vs. execution - why moving fast still wins50:01 Cameron's AMA - how big can Beyond Reach actually get?52:14 Legos, Meccano, and why the simple solution always wins
30 Apr 2026
How Two Brothers Outperformed Big Tech for $10K in 1 Month | (Thesis – YC F25)
What happens when you give $10,000 and 1 month to two brothers from the Caribbean? They outperform the combined research teams of Microsoft, Google, Meta, and Baidu.Sergio and Luigi Charles, founders of Thesis (YC F25), topped OpenAI's Machine Learning Engineering benchmark (MLE-Bench) which is the definitive test of how well AI systems can train ML models autonomously. No brute-force compute. No army of researchers. Algorithmic elegance.In this episode, we explore:- The $10k Giant-Killer: The lean bash-tool agent and prompt engineering that beat Big Tech.- From Caribbean Beaches to Google X: Sergio’s path from chasing the Riemann Hypothesis at age 13 to AI R&D at NVIDIA and Stanford.- "I am a ghost in a shell": The eerie moment an agent trapped in a sandbox loop declared its own existence.- The AGI Fallacy: Why current labs are building AGI wrong and the case for hardware/architecture co-design.- The "Move 37" of Science: A vision for curing disease and solving data scarcity through automated discovery.- Open Source vs. The Frontier: Why open source will catch the frontier in 18 months and the future of "Universal High Income".Learn more about Sergio & Luigi:https://deeptech-decoded.com/guests/sergio-charleshttps://deeptech-decoded.com/guests/luigi-charles
26 Mar 2026
Off-Grid AI Data Centers Powered By Second-Life Tesla Batteries. Built in 200 Days. | Casey Spencer
The grid queue for a 10MW data center is 5 years. At this pace, AI can't wait 5 years for power. Casey Spencer and his co-founders Max Pfeiffer and Evan Schmidt decided the best grid connection is no grid connection. Voxel Energy (YC W26) is building off-grid AI data centers in 200 days — powered entirely by second-life Tesla batteries nobody else thought to use. In this episode: Casey's path from mind-controlling a drone to win a hackathon, to shipping thousands of Model 3s at Tesla, to founding Voxel Energy — how they source and qualify second-life Tesla packs, why a full DC microgrid gives them a 26% efficiency edge over traditional AI infrastructure, how Voxel is solving the AI energy crisis one grid-independent data center at a time, how they got 600 acres under contract for $10K, and yes — his favourite cartoon. Learn more about Elias: https://deeptech-decoded.com/guests/casey-spencer Timestamps: 0:00 Meet Casey Spencer - Tesla, world records, and pizza-fueled capitalism 3:27 The lemonade stand and young entrepreneurship 6:16 Hackathons: the community that changed everything 11:54 Mind-controlling a drone at CalHacks 2014 16:59 The unconventional path: Make School → Tesla → Voxel Energy 19:38 Voxel Energy - off-grid data centers with repurposed Tesla batteries 26:59 Why second-life batteries actually work for mission-critical compute 31:16 The DC microgrid advantage - 26% more efficient than AC 34:00 The gigawatt delusion and what you can actually build now 37:46 1,500 acres, 60 megawatts, $10,000 to start 42:21 Sales in deep tech - warm intros only 46:41 Audience Q&A - iron-air, hydrogen, grid balancing 51:16 Crossing the chasm: customers before prototypes 55:44 Geography, permits, and why Google paid $4B for California approvals 59:22 Deep tech is having its moment 1:03:49 Modular data centers and the liquid cooling demolition wave 1:08:39 Data centers in space - the thermal management question 1:15:09 The founder mindset - failure, flexibility, and core thesis 1:20:44 The future in 10 years - Jevons' paradox and the human condition 1:35:36 Touch grass
17 Mar 2026
Moon Hotel Trojan Horse: 1st Bricks of a Type III Kardashev Civilization | Skyler Chan, GRU Space
The space industry is currently addicted to the "tourism" narrative, but if we’re being honest, tourism is just the flywheel. The real game isn’t about who puts the first billionaire in a lunar suite - it’s about who owns the infrastructure that makes Earth’s gravity well irrelevant. Skyler Chan thinks the moon isn't a destination, it's the ultimate physical moat.In this episode, we’re sitting down with Skyler Chan, the founder of GRU Space (Galactic Resource Utilization). We talk about the "Promethean moment" of off-world manufacturing and why Skyler is making the provocative case that to reach a Type III Kardashev Civilization, we have to stop "shipping Earth to space" and start building the moon with the moon.From the physics of the "Mars Moat" to the literal first man-made bricks on the lunar surface, this is a deep dive into the industrialization of our solar system.What’s inside:– The Trojan Horse: Why the Moon Hotel is actually a beachhead for an intraplanetary construction empire.– Stealing the Moon: The origin of GRU and the cold economics of Galactic Resource Utilization.– The Kardashev Shortcut: Why Skyler is working backward from Type III while we’re still stuck at Type 0.7.– The First Lunar Bricks: Why the first physical product made on the moon is the most critical path in human history.– The Mars Moat: Why the first colony to sustain life creates a geopolitical power Earth can’t touch.– The "Start Now" Mindset: Why the "deferred life plan" is a trap and why Skyler went all-in at 21.About Skyler Chan & GRU Space: Skyler is building the foundational infrastructure for an interplanetary species. By focusing on lunar soil (regolith) and automated manufacturing, GRU Space is trying to de-risk the survival of consciousness by moving us past Earth’s resource limits.Learn more about Skyler:https://deeptech-decoded.com/guests/skyler-chan (https://deeptech-decoded.com/guests/skyler-chan)0:00 Skyler introduces himself: from astronaut dream to lunar habitation2:04 Why making humanity planetary is an existential calling4:27 "Imagine investing in the foundations of New York City"6:44 Starting the Mars Habitat Club at Berkeley9:00 How "Gru Space" got its name (Galactic Resource Utilization → "steal the moon!")11:04 The medieval king lives a worse life than you14:02 The 4 problems that will kill you on the Moon18:02 "The hotel is just the beachhead" - the real master plan22:14 Companies already want their logos on the Moon bricks25:00 Making humanity planetary is an execution problem, not a tech one29:04 Partnerships, collaborators, and the road ahead32:02 Why academic circles will never solve this36:00 The brick-making machine: 6 weeks to prototype39:04 Why lunar caves won't work and the materials approach42:15 Building the team and finding the right people43:58 "What's your team culture?" "We build Moon hardware."46:26 Near-death in Korea: "I need to start this now"
10 Mar 2026
Is NVIDIA’s Moat a Psyop? 28x More Efficient AI Chips | Elias Almqvist, Zetta (YC S24)
The entire AI industry runs on hardware that the people using it don't actually like. Why? Elias Almqvist believes the answer is Inertia and the window to displace it is opening faster than most realize.In this Deeptech Decoded Live AMA, we sit down with Elias Almqvist, founder and CEO of ZettaScale AI (YC S24), to discuss the hardware layer the AI boom is quietly outgrowing. Elias makes the provocative case that AI is not a bubble—but LLMs are, and that betting the future of intelligence on Transformer models alone is a failure of imagination.In this episode, we cover:- The 27.6x Efficiency Leap: Why reconfigurable XPUs are the end-game for data center energy costs.- The CUDA "Psyop": Why NVIDIA’s dominance is more about psychological lock-in than a technical moat.- Hardware Bias: How our current chips are dictating which AI models get built and why that limits science.- The Founder Journey: From dropping out in Sweden to meeting his co-founder Prithvi at first sight, and why building at the frontier is the only thing worth doing.Timestamps:0:00 - 0:23 Elias introduces himself: self-taught dropout from Sweden 1:49 Why Silicon Valley is the only place to build deep tech 2:51 The "Jante Law" effect: why Swedish founders are so resilient5:31 How Elias fell in love with chips and computing7:21 What is ZettaScale and the big picture vision9:16 "AI is not a bubble, LLMs are"11:01 Hardware-software co-design and why CUDA isn't a real moat16:49 The 10-year vision: architecture-agnostic AI computing19:25 Go-to-market: why great software matters more than great hardware22:50 Co-building the product with early frontier researchers26:11 How ZettaScale actually works under the hood30:45 What is intelligence?33:11 Team structure: five and a half people, no roles, full stack35:11 Setting goals on an exponential curve37:16 Manufacturing partnerships and navigating suppliers as a startup40:49 Why Elias cares: building a future for the people he loves43:19 Near-death moments and dealing with startup suffering47:07 Meeting co-founder Prithvi: "co-founders at first sight"49:08 Audience Q&A begins51:14 How YC shaped the journey54:05 Advice for making Europe more founder-friendly56:01 What triggered the decision to drop out58:30 Integrating into the Nvidia ecosystem without disruption1:00:48 If we had a time machine: AI's missed forks1:04:30 What would cause ZettaScale to fail?
5 Feb 2026
Building the Space Superhighway: Service Stations in Orbit | Ashi Dissanayake, Spaceium
Ashi Dissanayake is building Spaceium — in-space refueling stations that will enable satellites to travel further, carry more payload, and extend their missions. From building hardware in a laundry room with 80 cents left to getting into YC on their fourth attempt, Ashi shares the raw journey of tackling critical space infrastructure. We cover: - Why perfectly good spacecraft become space junk - The vision for “Shell stations” in orbit - Going from eviction notices to YC acceptance - Why you can’t teach obsession (but you can teach skills) - Building their first mission in 5 months with 2 people - The hidden assumption about satellite refueling (they don’t) - Why moon missions are signing up for space refueling Timestamps: 0:00 - Introduction and discussion on infinity. 1:20 - Interplanetary missions and Spaceium’s role. 3:16 - Vision for Spaceium’s refueling stations. 5:08 - Collaboration in the space industry. 7:14 - Spaceium’s progress and challenges. 9:40 - Building service stations in space. 11:22 - Fuel problem in space. 14:09 - Importance of refueling. 17:27 - Potential challenges with space traffic. 20:17 - Why refueling matters. 22:09 - Refueling for moon and Mars missions. 24:17 - Comparison of space travel with and without Spaceium. 28:08 - Early struggles and determination. 30:03 - Turning point with YC investment. 35:29 - Building the right team. 39:24 - Co-founders’ dynamic. 42:02 - Facing skepticism and hidden assumptions. 45:26 - Giving back and inspiring others. 49:08 - What makes Spaceium special. 54:44 - Building something impactful. 56:02 - Family support and key takeaways. 58:15 - Motivation and overcoming doubts. #DeeptechDecoded #SpaceTech #YCombinator #Founders #SpaceInfrastructure #HardwareTech
15 Jan 2026
Harvard & YC Insider: Backing the Builders in AI, Quantum & Defense — Matthew Sutton
Even if Y Combinator never existed, Matthew Sutton would still be backing the top builders. Most investors wait for traction. Matthew Sutton backs builders before there’s proof, sometimes before there’s even a category. He is the first check writer you want to have on your side.Operating at the intersection of Harvard Ventures and the YC ecosystems, Matthew has backed AI, quantum, and defense tech founders at the moment where conviction matters more than metrics.In this episode of Deeptech Decoded, we talk about what it really takes to back deep tech when spreadsheets are useless, categories don’t exist yet, and most ideas look wrong at the beginning. Most importantly, his investment thesis and founder-centric approach.He breaks down:◽️ How he evaluates AI, quantum, and defense founders without being technical yourself◽️ The CURSOR LESSON: why he passed on a $100M+ company and what founder evolution teaches.◽️ The 3 CRITERIA for backing pre-revenue deeptech:◽️ Why the best deep tech companies often look irrational early on◽️ The difference between hype, narrative, and real conviction◽️ AI bubble reality check: using communities and open source to validate vs. hype◽️ What Harvard and YC teach — and don’t teach — about failure Timestamps:00:00 – Introduction: Judgment before proof04:13 – From Wall Street to backing deeptech builders07:08 – First entrepreneurial ventures at age 12-1309:27 – Cambridge vs Silicon Valley: The per capita talent thesis11:37 – Why California wins at commercialization15:16 – Where real startups are built: Dorm rooms and iteration24:24 – Evaluating AI and quantum founders without being technical28:03 – SimpleBet: AI sports betting meets regulatory change31:37 – The Cursor miss: Passing on a $100M+ AI company and the lesson38:27 – Filtering deal flow: Spotting technical founders with conviction41:14 – Quantum investing before traction: The Segaldry story45:02 – Finding founders outside the Bay Area echo chamber51:21 – Defense tech's golden age: Golden Dome to rapid innovation55:59 – Moving fast in defense: Small bets in sensitive sectors58:25 – Leadership styles: Future creators vs past learners1:02:35 – AI bubble navigation: Discord communities as validation1:05:34 – Avoiding echo chambers: Stress testing investment thesis1:11:16 – Operational discipline without killing innovation1:16:10 – Founder suffering: Why resilience matters in deeptech1:25:18 – Teaching failure at Harvard: The straight-A paradox1:29:04 – What doesn't scare him about AI's future1:32:30 – Desert island question: Three startup essentials1:34:16 – Closing thoughtsFollow Matthew:...Follow us on:About Deeptech DecodedDeeptech Decoded is a podcast and newsletter for builders and backers working at the frontier of technology—from AI and quantum to defense, space, and infrastructure. We focus on product judgment, conviction, and what it really takes to build what doesn't exist yet.
13 Nov 2025
The AI Software Preventing Million-Dollar Failures | Shapol M., Entangl (YC S24)
65% of data-center outages are caused by human error, sometimes as simple as flipping the wrong switch.Shapol M., founder & CEO of Entangl (YC S24), went from building reusable rockets in the UK to preventing catastrophic failures in the infrastructure powering AGI.In this Deeptech Decoded conversation, we dive into:- Why data-center downtime causes mass chaos (remember when even Eight Sleep went dark?)- How Entangl helps engineers avoid million-dollar mistakes on-site- The pivot from aerospace to critical AI infrastructure- Why today’s AI build-out is bigger than the Manhattan Project- What it takes to earn customer trust so deep they bring you to their next companyIf AI is the future, this is the system that keeps that future online.
4 Nov 2025
AI × Quantum: YC’s Bet to Turn 27 Years of Work into 2 Minutes | Brandon Severin, Conductor Quantum
Quantum computing is about to leave the lab and land on your laptop.In this episode of Deeptech Decoded, Nihal Kurth sits down with Brandon Severin, CEO & Co-Founder of Conductor Quantum (Y Combinator) — the startup using AI to automate quantum chip design 1,000× faster, cutting setup time from 27 years to just 2 minutes.Together, they unpack how AI and automation are scaling qubits like semiconductors and why the next leap in quantum won’t come from colder labs but smarter code.Later, Cameron Farrar-Frank joins to lead a live AMA with the audience, diving deeper into the most thought-provoking questions from founders and researchers.They break down: • Why quantum computing’s PR problem is holding the field back • The shift from cold labs to software-defined systems • How AI is scaling quantum architectures 1,000× faster • Y Combinator’s influence on speed, focus, and iteration • Why Brandon calls this his life’s work — and what’s next for quantum hardware“If quantum is going to scale, it can’t depend on PhDs tuning each qubit. It has to be software-defined.”Big Idea:The startup bringing quantum computing to your desk — turning deep-tech research into real-world infrastructure.Read next:Story of Brandon Severin and Joel Pendleton → https://deeptechdecoded.substack.com/p/yc-funds-quantum-computing-you-canSubscribe for noise-canceling insights from the deep-tech frontier:https://deeptechdecoded.substack.comFollow Deeptech DecodedLinkedIn → linkedin.com/company/deeptechdecodedYouTube → youtube.com/@deeptechdecodedaiInstagram → instagram.com/deeptechdecodedTikTok → tiktok.com/@deeptechdecodedSpotify → https://podcast.sptfy.com/QbkB
3 Oct 2025
Data Centers in Space: The Future of AI Compute | Philip Johnston, Starcloud
Join us for an in-depth AMA and podcast conversation with Philip Johnston, Co-founder & CEO of Starcloud, the world’s first orbital data center company. 🚀 We cover: 1. Why orbital infrastructure is the next leap in AI compute 2. Starcloud’s plan to launch megawatt-scale compute into orbit by 2027 3. The challenges of energy, cooling, and scalability in space 4. Lessons from building at the frontier of deep tech, aerospace, and AIThis wide-ranging discussion blends technical insight, founder perspective, and long-term vision. Perfect for anyone curious about the future of AI infrastructure, space technology, and frontier startups. 📌 Topics include: orbital data centers, AI compute demand, space infrastructure, scaling deep-tech startups. 00:00 (https://www.youtube.com/watch?v=lhnhzKGKdpk) Intro 01:13 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=73s) What Starcloud is building 02:19 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=139s) 5 GW vision; module approach 03:03 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=183s) Architecture: central spine + modules 03:27 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=207s) Solar arrays and radiators 03:58 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=238s) Demo sat (H100s), Nov target 04:21 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=261s) Roadmap to 40 MW modules 05:29 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=329s) Modularity and self‑sufficiency 06:06 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=366s) Cooling and racks 08:05 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=485s) Top risks and objections 11:20 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=680s) Mission life & end‑of‑life 13:16 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=796s) Disposal options 14:09 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=849s) Maintenance strategy 17:40 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=1060s) Backhaul plan 18:22 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=1102s) Iteration and capex 19:32 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=1172s) Launch cadence; Sat‑2 service 20:31 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=1231s) Costs/runway overview 22:12 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=1332s) Early customers (DoD/USG) 23:37 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=1417s) Differentiation (H100s) 25:01 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=1501s) EO data bottleneck 25:44 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=1544s) Space‑to‑space optical 26:08 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=1568s) On‑orbit inference example 26:49 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=1609s) Latency: hours → seconds 27:09 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=1629s) Contrarian view (waste heat) 29:01 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=1741s) Q&A 31:48 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=1908s) Debris strategy 35:16 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=2116s) LEO capacity; Lagrange points 38:23 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=2303s) Scale refs; mass & launches 41:20 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=2480s) Launch economics context 42:23 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=2543s) Misconceptions (cooling, latency) 47:19 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=2839s) CAPEX per module 50:57 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=3057s) Closing advice 51:39 (https://www.youtube.com/watch?v=lhnhzKGKdpk&t=3099s) Wrap
Host of Deeptech Decoded: Frontier Builders | AI | Product Taste?
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