Integration is a dirty word in defense. The consultancy model that solved it for decades no longer works when you're dealing with hundreds of systems from dozens of vendors across land, sea, and airspace, all needing to work together within milliseconds.In this episode of High Bit, Brett Gibson talks with Zane Mountcastle, cofounder and CEO of Picogrid, about how they built the hardware and software infrastructure layer that makes hundreds of defense systems work together.Zane gets into what it actually looks like to deploy in the field, from detecting a quadcopter 50 feet off the ground, operating in GPS-denied environments with decades-old hardware and adversaries trying to trick your sensors.Speed became their biggest differentiator. Their average integration time is measured in hours, and what used to take six to twelve months gets done over a weekend.He also explains why trust is the biggest moat in defense, and how AI is now core to how they build, including training a model on every system they've ever connected so a first pass integration happens in seconds.Chapters:(00:00) "Integration is a dirty word"(00:19) What Picogrid builds(01:08) How Zane ended up working with the Pentagon(03:11) The Last Supper: how defense consolidated(05:01) Why hundreds of new defense vendors made integration worse(07:22) Why the consultancy model no longer works(09:41) Why speed is their biggest differentiator(11:53) Each system has a language(15:49) Four types of location data to find and track a drone(19:54) Why Picogrid will never build a drone or sensor(22:16) The military loves to buy widgets(30:38) Trust is the biggest moat in defense(34:20) Calibrating in the field: the camera that finds the sun(37:36) First team in, last team out(45:37) How AI is now part of everything they build(47:00) $45M from Bessemer and what comes nextFollow Zane and Picogrid:X: @zanemountcastle / @PicogridLinkedIn:linkedin.com/in/zanemountcastlelinkedin.com/company/picogridFollow Brett and Initialized:X: @brettdg / @InitializedLinkedIn:linkedin.com/in/brettdgibsonlinkedin.com/company/initialized-capital

The internet was built without identity at the protocol level. Now AI makes it nearly impossible to know who or what you're interacting with online. Alien is a decentralized unique identity platform built on the principle of one human, one account — no government required, no central authority, just a cryptographically verifiable way to prove you're human and link that identity to the AI agents acting on your behalf. Mainnet is live now.In this episode of High Bit, Brett Gibson talks with Kirill Avery, founder and CEO of Alien, about why identity has always been the missing layer of the internet, how Alien combines biometrics, social graphs, and verifiable credentials into a single trust framework, and why the company built its own blockchain rather than deploy on Ethereum or Solana. Kirill also explains why 50 countries already have CBDCs and why building an alternative is the only real answer, what it looks like when one agent manages a thousand agents each managing a thousand more, and why proving you're human online will always be probabilistic — never absolute.Chapters:(00:00) Are you human? Why the answer is always probabilistic(00:19) What Alien is and why unique identity matters(01:08) Kirill's background: VK, bots, and the identity problem(03:11) Why the internet was built without an identity layer(05:01) How AI made the identity problem urgent(06:24) Why Alien needed its own blockchain(07:22) CBDCs, centralized identity, and why an alternative is necessary(10:30) Consensus mechanisms as voting machines and Bitcoin's honesty problem(12:15) How Alien ensures one person, one account(16:04) Biometrics, birthdates, and social graphs as layered verification(19:54) The Alien coin and how value accrues to participants(22:39) Why early adopter concentration is a design flaw(27:42) Agent hierarchies and why human-linked agent identity matters(30:06) How Alien uses AI internally to build with a smaller team(35:15) What's next: Mainnet phases, Alien coin, and Solana integrationFollow Kirill and Alien for more:X:@kirillzzy@alienorgLinkedIn:linkedin.com/in/kirillzzylinkedin.com/company/alienorgFollow Brett and Initialized:X: @brettdg / @InitializedLinkedIn:linkedin.com/in/brettdgibsonlinkedin.com/company/initialized-capital

Azura built a unified application for trading across multiple blockchains from one interface. You can trade tokens across Solana, Ethereum, Base, Arbitrum, Blast, and more without jumping between wallets, bridges, and apps. Try it: app.azura.xyzIn this episode of High Bit, Initialized managing partner Brett Gibson talks with Jackson Denka, founder and CEO of Azura, about building an onchain trading platform that aims to feel more like a traditional brokerage while staying self-custodial. They dig into why crypto trading is still fragmented — and what Azura is doing about it.Jackson explains why DeFi is powerful but still hard to use, what it takes to unify DEXs and bridges into a single trading experience, and why cross-chain execution is such a difficult technical problem. They also discuss why he believes value in crypto will accrue at the application layer, why Azura built more of its stack in-house, and what it would take for crypto to disappear into the backend.Chapters:(00:00) One venue for every asset(00:46) What Azura builds(01:07) Jackson’s origin story(03:13) Why DeFi is hard to use(05:39) Why the app layer wins(09:23) Why onchain is next(13:05) One app across chains(15:45) Why this is so hard(17:12) Cross-chain execution(21:12) Hiring in DeFi(22:36) App revenue and DEX growth(25:44) Removing gas and networks(27:01) Self-custody, simpler UX(30:07) Building the stack in-house(33:13) How Azura uses LLMs(39:52) What’s next for AzuraFollow Jackson and Azura:X@jacksondenka@AzuraTradeLinkedInhttps://www.linkedin.com/in/jacksondenka/https://www.linkedin.com/company/azuraxyz/

Code can be generated faster than ever. But getting that code to actually look good is a different problem entirely.In this episode of High Bit, Initialized managing partner Brett Gibson sits down with Daniel Bulhosa Solórzano, cofounder and CTO of Variant, about what it takes to build AI that gets design right, not just code that runs.Daniel started thinking about this problem in 2017 at Weebly, when the models weren't close to ready. After a stint in self-driving, he came back to it. Variant generates UI that's visually designed, not just technically correct, and shows you multiple options at once so you can find what you actually want instead of having to describe it upfront.Topics include:- Why AI struggles with visual quality even when the code works- The difference between precision and recall in design generation- Why showing people options beats asking them to describe what they want- Why people will always want to stay in the loop on design- How the role of designers changes as AI handles more of the execution(00:00) What design AI could eventually do(00:44) What Variant builds(01:25) How Daniel got here: Weebly, self-driving, and an unsolved problem(03:20) Why visual code generation is hard(04:10) Precision vs. recall and why design is different(06:55) What good design actually means(09:04) Landing page vs. dashboard: how context shapes design choices(11:31) What can be described vs. what has to be labeled(13:10) Casting a wide net for what good design looks like(15:25) Building the product around an imperfect model(17:04) Why people react to designs faster than they can describe them(19:29) Why people won't give up design to AI(23:40) What AI does to the design learning curve(25:06) Designers as design managers for agents(37:42) The 50%/80% horizon and what it means for engineering teamsFollow Daniel and Variant:Daniel Bulhosa SolórzanoX: https://x.com/bulhosaLinkedIn: https://www.linkedin.com/in/dbulhosa/VariantWebsite: https://variant.com/X: https://x.com/variantuiLinkedIn: https://www.linkedin.com/company/variantui/posts/?feedView=allHigh BitWatch more episodes: https://www.youtube.com/@InitializedCapitalFollow on Spotify: https://open.spotify.com/show/36gTYrH1wlYzTZwLQywbIf

Code can be written faster than ever. But getting that code safely into production is where many engineering teams lose time.As organizations grow, CI failures, flaky tests, and conflicting pull requests start to compound.In this episode of High Bit, Initialized managing partner Brett Gibson sits down with Eli Schleifer, founder and CEO of Trunk, to talk about the systems that keep CI green and allow engineering teams to land code reliably as organizations grow.Before starting Trunk, Eli built developer infrastructure at Microsoft, started a company that was acquired by Google, and later worked with hundreds of engineers at Uber ATG. At Google he saw how powerful internal developer tooling could be. At Uber he saw engineers spend days trying to land code because those systems did not exist. That gap led him to start Trunk.Eli explains why engineering productivity slows once dozens or hundreds of engineers share the same repository, how flaky tests quietly waste engineering time, and how merge queues prevent broken builds and conflicting pull requests.Topics include:Why CI becomes the bottleneck as engineering teams growHow merge queues keep builds reliableWhy flaky tests waste engineering timeThe build vs buy decision for developer toolingHow coding tools are increasing pull request volumeHow engineering workflows are changing(00:00) AI fixing flaky tests(00:40) What Trunk builds(02:13) When CI becomes the bottleneck(02:33) Eli’s background: Microsoft, Google, Uber(04:29) Why dev tools must solve real pain(05:09) The merge queue problem(09:25) Build vs buy for developer tooling(14:22) How merge queues handle large codebases(18:58) How coding tools increase PR volume(21:53) Flaky tests and engineering productivity(25:24) Using CI and test history to debug failures(27:37) How engineers prune the search space(33:23) Engineers as conductors of automated systems(37:49) What’s next for TrunkFollow Eli and Trunk:Eli SchleiferX: https://x.com/elischleiferLinkedIn: https://www.linkedin.com/in/elischleifer/TrunkWebsite: [https://trunk.io](https://trunk.io/)X: https://x.com/trunkioLinkedIn: https://www.linkedin.com/company/trunk-io/High BitHosted by Brett Gibson, managing partner, Initializedhttps://open.spotify.com/show/36gTYrH1wlYzTZwLQywbIf

AI models keep getting better, but most AI systems still fail in production. Why?In this episode of High Bit, Brett Gibson sits down with Ghita Houir Alami, cofounder and CEO of ZeroEntropy, to break down the real bottleneck holding AI agents back: retrieval.Ghita explains why embeddings alone can’t reliably surface the right information, why tools like Slack search feel so frustrating, and how rerankers add a critical second pass that dramatically improves accuracy. She walks through ZeroEntropy’s approach to training rerankers using pairwise comparisons and Elo-style scoring, and why this method generalizes across domains like code, finance, and biology.The conversation goes deep into:Why AI agents fail even when the data exists.How reranking fixes poor ordering from vector search.Why “accuracy” now includes helpful context, not just correct answers.What actually changes when retrieval becomes trustworthy enough to remove humans from the loop.If you’re building AI agents, search systems, customer support bots, or internal knowledge tools, this episode explains what’s breaking today, and what has to change for AI to work reliably at scale.(00:00) What changes when retrieval works(00:39) What ZeroEntropy builds(01:42) Why retrieval became the real problem(03:12) Why search fails (Slack included)(05:11) Why embeddings fall short(07:11) Rerankers: the missing layer(10:11) Why rerankers matter most(12:44) Pairwise ranking vs scoring(13:52) Elo scoring for documents(16:33) Fast rerankers via distillation(18:07) Why old training methods break(21:29) Retrieval for AI agents(24:20) Recency, memory, personalization(32:06) What reliable retrieval unlocks(33:42) What’s next for ZeroEntropyFollow Ghita and ZeroEntropy for more:X@ghita__ha@ZeroEntropy_AILinkedInhttps://www.linkedin.com/in/ghita-houir-alami/https://www.linkedin.com/company/zeroentropy-inc

Electrification isn’t easy—and most people don’t see the chaos beneath the solar panels, batteries, EV chargers, and heat pumps going onto the grid. Coperniq cofounder and CTO Max Kazakov breaks down the hidden workflows behind distributed energy: legacy tools installers still rely on, hardware that doesn’t want to integrate, and why the next generation of “utilities” will look nothing like the last.Coperniq is the workflow platform for contractors and energy companies to move from post-its and spreadsheets to a system that sells, permits, installs, and maintains distributed energy assets over decades.Max also shares what it takes to build vertical SaaS for the physical world: curbside Figma demos during COVID, rebuilding their mobile app for 120°F rooftops with no cell service, designing a workflow engine that matches real-world permitting and interconnection, integrating a wild west of OEM hardware, and how AI is already reshaping their product and engineering culture.Content:(00:00) The Invisible Glue of the New Grid(01:05) The Second Electrification Wave(02:51) Cofounder Origins: Russia, Yemen, Berkeley(06:12) Humans + Hardware Coordination Challenge(08:10) Anti-MVP: Mini ERP on Day One(11:56) Curbside Figma Demos during COVID(14:47) Field Reality: 120° Rooftops, Zero Cell Service(20:03) Stateful Workflows (Permits, Interconnection, Construction)(24:56) Integrating OEM Hardware (Hitting Walls)(28:41) The Dongle Question: Do we need software afterall?(31:25) Rebuilding the Mobile App for an Offline-First World(36:40) Hire Tinkerers, Not Pedigrees(43:00) How AI Is Reshaping CoperniqSubscribe to High Bit for more conversations with technical founders building the future.Follow @Coperniq_AI for more.

Robots built like humans.On High Bit, Dhanush Radhakrishnan, cofounder & CEO of Clone, explains how they’re letting biology set the blueprint for musculoskeletal, super-intelligent androids — synthetic humans straight out of sci-fi.Powered by artificial muscles instead of motors and attached to anatomically accurate skeletons, Clone is building robots designed for human-level motion, durability, and full-body control.Dhanush explains the early engineering choices that helped them move fast, their data strategy (motion capture, teleoperation, egocentric video), and his excitement about a future untethered biped.Hosted by Brett Gibson, managing partner at Initialized.Content:(00:00) From Fragile to Durable(00:37) Musculoskeletal Androids(02:03) Why Artificial Muscles(04:10) Starting Clone in Poland(06:29) Removing Early Sensors(10:14) The Durability Challenge(14:10) Anatomy as Blueprint(16:22) Building Custom Valves(18:17) Hand to Full Body(24:40) Prototyping with Pneumatics(29:26) Delaying Tactile Skin(32:39) Data: MOCAP + Teleop(45:20) Toward an Untethered BipedSubscribe to High Bit for more conversations with technical founders building the future.

In this episode, Brett Gibson talks with Lucas Young, cofounder and CEO of Deepnight about how they’re building AI-powered night vision that helps the military, law enforcement, and first responders see in near-total darkness. Deepnight combines AI with commodity digital sensors — the same kind used in smartphones — to replace expensive analog night-vision hardware that costs over $30,000 per unit and hasn’t kept pace with modern imaging technology.Lucas explains how night vision has worked since World War II, why analog image intensifiers hit a ceiling, how smartphone photography paved the way for this breakthrough, and what it takes to bring military-grade low-light imaging into the field.Chapters(00:00) Why Night Vision Is Still Mostly Analog(00:39) Deepnight’s Breakthrough: AI That Sees in the Dark(01:44) How Their AI Reconstructs *Real* Scenes(03:58) Lucas’s Path: Google Pixel → YC Founder(05:26) Why Modern Cameras Rely on Software(09:12) The Rise of AI-Enhanced Photography(11:45) The Insight: AI Could Beat $30K Night-Vision Goggles(13:03) How Traditional Night-Vision Tubes Work(14:10) Starting Deepnight Without Knowing If It Would Work(15:11) Early Prototypes: Offline → Real-Time Night Vision(16:15) The Physics Challenge: Seeing in Moonless Starlight(19:12) Running This on Smartphone-Class Chips(22:27) Building a Custom Neural Network for Night Vision(28:43) Can Cheap $50 Sensors Match Military Gear?(48:06) What’s Next: Real Soldiers Using AI Night VisionSubscribe to High Bit for more conversations with technical founders building what’s next, hosted by Brett Gibson of Initialized Capital.

Brett Gibson sits down with cofounders Max Prilutskiy (CEO) and Veronica Prilutskaya (CPO) of Lingo.dev to talk about making every product multilingual—so teams “just keep shipping” and don’t have to worry about localization and translations at scale. Lingo.dev helps product teams develop multilingual user interfaces, uses LLMs to produce perfect translations, and automates localization end to end.Chapters:(00:00) The Future of Coding and “Vibe Coding”(00:50) What Lingo.dev Does (01:24) Built at a Hackathon(04:59) From Google Translate to LLMs - for more context(06:20) “Perfect Translation” - objective AI precision + subjective brand tone + cultural nuance(11:13) Automating Translations with Pull Requests(13:41) The New Compiler - making apps multilingual without refactoring(17:42) How “Vibe Coding” Changed Software Development(19:10) Write Once, Click Save, See It in Any Language(37:29) AI Impact: “The Future of Coding” in PracticeSubscribe to High Bit for more conversations with technical founders building what’s next, hosted by Brett Gibson of Initialized Capital.Follow Lingo.dev, Max and Veronica on X for more:https://x.com/lingodotdevhttps://x.com/MaxPrilutskiyhttps://x.com/vrcprl