High Bit

Initialized Capital

Welcome to High Bit, a podcast hosted by Initialized Capital managing partner Brett Gibson about the art of technical problem-solving. A high bit is the most significant part of the binary representation of a number. In programming language, it is commonly referred to as the most important thing you need to understand about a problem. Brett speaks to guests about just that. In each episode, they’ll break down a gnarly engineering problem and you'll hear how the builder’s ingenuity and inventiveness led to a successful outcome.

  1. Variant: What It Takes to Get AI-Generated Design Right

    25. MÄRZ

    Variant: What It Takes to Get AI-Generated Design Right

    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 teams Follow Daniel and Variant: Daniel Bulhosa Solórzano X: https://x.com/bulhosa LinkedIn: https://www.linkedin.com/in/dbulhosa/ Variant Website: https://variant.com/ X: https://x.com/variantui LinkedIn: https://www.linkedin.com/company/variantui/posts/?feedView=all High Bit Watch more episodes: https://www.youtube.com/@InitializedCapital Follow on Spotify: https://open.spotify.com/show/36gTYrH1wlYzTZwLQywbIf

    46 Min.
  2. Trunk: Fixing CI at Scale (Merge Queues, Flaky Tests, and Shipping Code)

    10. MÄRZ

    Trunk: Fixing CI at Scale (Merge Queues, Flaky Tests, and Shipping Code)

    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 Trunk Follow Eli and Trunk: Eli Schleifer X: https://x.com/elischleifer LinkedIn: https://www.linkedin.com/in/elischleifer/ Trunk Website: [https://trunk.io](https://trunk.io/) X: https://x.com/trunkio LinkedIn: https://www.linkedin.com/company/trunk-io/ High Bit Hosted by Brett Gibson, managing partner, Initialized https://open.spotify.com/show/36gTYrH1wlYzTZwLQywbIf

    39 Min.
  3. ZeroEntropy: The Hidden Bottleneck in AI. Retrieval, Not Models

    30. JAN.

    ZeroEntropy: The Hidden Bottleneck in AI. Retrieval, Not Models

    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 ZeroEntropy Follow Ghita and ZeroEntropy for more:X@ghita__ha@ZeroEntropy_AILinkedInhttps://www.linkedin.com/in/ghita-houir-alami/https://www.linkedin.com/company/zeroentropy-inc

    35 Min.
  4. Coperniq: Building the Workflow Glue Behind the New Electric Grid

    16.12.2025

    Coperniq: Building the Workflow Glue Behind the New Electric Grid

    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 Coperniq Subscribe to High Bit for more conversations with technical founders building the future. Follow @Coperniq_AI for more.

    58 Min.
  5. Deepnight: AI Night Vision That Beats $30K Goggles

    01.12.2025

    Deepnight: AI Night Vision That Beats $30K Goggles

    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 Vision Subscribe to High Bit for more conversations with technical founders building what’s next, hosted by Brett Gibson of Initialized Capital.

    49 Min.
  6. Orbital Operations: Rewriting Orbital Physics for Space Mobility

    16.10.2025

    Orbital Operations: Rewriting Orbital Physics for Space Mobility

    Orbital Operations is building high-thrust, cryogenic spacecraft designed to move freely in orbit—reshaping how we think about mobility, defense, and logistics in space. Cofounder & CEO Benjamin Schleuniger joins Initialized Managing Partner Brett Gibson on High Bit to talk about the next generation of spacecraft that will move, refuel, and think for themselves: Why satellites need to move — the rise of in-space mobilityHow cryogenic propulsion unlocks long-duration missionsThe refrigeration-cycle tech enabling propellant storage in orbitMilitary and logistics use cases driving demandRefueling with water to extend mission lifeThe third age of space mobility and what it enablesHow AI and autonomy will power future spacecraft Chapters (00:00) Intro (01:10) What Orbital Operations is building and why it matters (01:26) Ben’s path: NASA → SpaceX → Relativity (02:17) Why satellites need to move now (04:30) Basics of propulsion and why mobility is limited in space (05:55) Satellites vs rockets: propellant tradeoffs (08:30) Choosing cryogenic propellants and rethinking storage (10:15) The refrigeration-cycle system that makes it possible (17:00) Thermal management and engineering challenges in orbit (22:30) Military and logistics use cases for in-space mobility (25:40) Refueling with water and the future of orbital logistics (27:50) Engineering vs. business challenges of building in space (30:50) Scaling missions and the path to commercial viability (33:30) The third age of space mobility and what comes next (35:20) AI tools in aerospace and autonomy in orbit Subscribe to High Bit for more conversations with technical founders building what’s next, hosted by Brett Gibson of Initialized Capital. Follow Orbital Operations and Benjamin Schleuniger on X for more: @OrbitalOps_ @BenSchleuniger

    38 Min.

Info

Welcome to High Bit, a podcast hosted by Initialized Capital managing partner Brett Gibson about the art of technical problem-solving. A high bit is the most significant part of the binary representation of a number. In programming language, it is commonly referred to as the most important thing you need to understand about a problem. Brett speaks to guests about just that. In each episode, they’ll break down a gnarly engineering problem and you'll hear how the builder’s ingenuity and inventiveness led to a successful outcome.