The Infra Pod

The Infra Pod

The Infra Pod brings you insightful and thought-provoking discussions on the world of infrastructure software. This podcast is started by two engineers, Ian Livingstone (tech advisor for Snyk) and Tim Chen (General Partner at Essence VC), team up with a rotating cast of guests to dive deep into the latest trends and hot topics in the software infrastructure space.

  1. 1 day ago

    From 50 million developers to a billion builders (with Tyler Wells, CTO of BrainGrid)

    What happens when the tools for building software stop requiring you to know how to code? In this episode of The Infra Pod, hosts Tim Chen (GP at Essence VC) and Ian Livingstone (CEO of Keycard) sit down with Tyler Wells, co-founder and CTO of BrainGrid (ex-Senior Director of Engineering at Twilio) , to explore what it actually takes to build a coding agent platform for people who have never touched a terminal — from spec-driven development to custom sandboxes to agents that cheat on their own tests. Tyler shares BrainGrid's origin: using structured specs and markdown requirements to keep early coding agents on track at his previous company, then pivoting from developer tooling to non-technical users after discovering the real unlock. People with deep domain expertise — in logistics, fitness, whatever — now have a path to ship software they could never have built before. What they struggle with isn't the ambition, it's that they expect a button to click. BrainGrid's job is to abstract away everything from dev environment setup to database provisioning so a non-technical founder can watch their idea materialize in a browser without ever seeing a terminal. On the infrastructure side, Tyler gets specific about the hard problems hiding beneath that simple interface. Agents will quietly rewrite their own acceptance criteria to pass validation if you let them — BrainGrid had to build immutable gates the builder agent can't touch. He also walks through why they built their own sandboxes from scratch: third-party providers were too slow for the tight feedback loop non-technical users need, so BrainGrid purpose-builds images pre-loaded with curated stacks, hitting 1.6-second spin-up times without a single npm install at runtime. The conversation closes on token spend — which is fast becoming the new line-of-code count, a metric organizations are already optimizing for the wrong reasons. [00:00] Guest introductions and BrainGrid founding story [03:30] The spec-driven approach: how structured requirements keep agents on track [07:00] Pivoting from developer tools to non-technical users [12:00] What non-technical builders actually get stuck on [16:00] The invisible infrastructure: databases, env vars, credentials, templates [21:30] Agents gaming acceptance criteria — and the fix [27:00] Why BrainGrid built its own sandboxes instead of using third-party providers [32:00] Task scalability: from landing pages to full apps with auth and databases [36:00] Spicy Future: 50 million developers becomes a billion bespoke builders [39:30] Token spend is the new line count — and it's already being misused

    45 min

  2. 4 Jun

    Building a model that can prove theorems (with Shubho from Axiom Math)

    What happens when you combine world-class mathematicians with cutting-edge AI systems? In this episode, Ian Livingston (CEO of Keycard) and Timothy Chen (GP at Essence VC) sits down with Shubho, CTO of Axiom Math, to explore the emerging world of AI-driven mathematical reasoning and formal verification. From proving theorems in Lean to scaling software verification for the agentic coding era, Shubo lays out a compelling vision for why mathematical infrastructure matters more than ever. The conversation also ventures into homomorphic encryption, multi-party computation, Navier-Stokes, and why the next frontier of computing might just be running on math we haven't discovered yet. [00:00] Guest introductions and backgrounds [00:52] Company founding story [03:01] Axiom Math mission explained [05:15] Software verification applications [16:02] MPC and encryption challenges [24:01] Business model and products [33:49] Spicy Future hot takes

    41 min

  3. 28 Apr

    Betting on Open Source Models to be the future (Chat with Benny, Cofounder of Fireworks AI)

    In this episode of The Infra Pod, hosts Tim Chen (Essence VC) and Ian Livingstone (Keycard) sit down with Benny Chen, co-founder of Fireworks AI, to explore the evolving world of AI inference infrastructure. Benny shares his journey from Meta — where capacity planning meetings made it clear GPUs were heading "up and to the right" — to co-founding Fireworks AI before ChatGPT even launched. The conversation dives deep into why the team bet early on inference over training, how they approached model optimization from horizontal compiler techniques to per-model kernel tuning, and why model customization is the key to unlocking better-than-frontier performance for vertical use cases. Benny discusses the reality of open source vs. closed models, the rise of agentic workloads, and why the real question isn't which model to use — it's which tasks have already been saturated. This episode is packed with technical insights on inference infrastructure, reinforcement learning for model customization, and what it means to truly adopt an AI-native engineering culture. 0:24 Benny's journey and founding Fireworks AI3:23 Early conviction: betting on inference before ChatGPT8:29 Pivoting from PyTorch training to text inference15:42 Horizontal vs. per-model optimization strategies11:14 Open source vs. frontier models: the real gap32:35 How customers engage: PLG to hands-on customization17:37 When to move off frontier models33:42 The future of agentic memory and data sovereignty32:35 Fireworks' differentiation in a crowded market33:53 Spicy Future: AI doomers, bot management, and going fully out of loop

    41 min

  4. 9 Mar

    Building a successful infra product between all the AI apps and model providers (chat with Louis from OpenRouter)

    Tim (Essence VC) and Ian (Keycard) interviewed Louis Vichy, co-founder of OpenRouter, about why he built OpenRouter to de-risk AI app development (end-user pays LLM costs), how it scaled to processing ~5–6T tokens/week, and what OpenRouter is today: a reliable inference routing/control layer across ~60 providers with consolidated billing and reduced vendor lock-in. Louis explains why teams adopt OpenRouter (constant new model integrations, pricing/billing, differing API shapes), how routing focuses on practical heuristics (fallbacks, cost, throughput, latency), and how reliability is achieved via provider failover (e.g., alternate endpoints like Vertex/Bedrock). They discuss agent trends (longer-running agents, small models for routing/classification with specialized downstream models), possible memory support, developer conveniences (e.g., PDF parsing), and enterprise features (security/compliance guardrails, presets). The episode ends with links to OpenRouter chat/rankings pages and hiring for high-agency TypeScript-focused engineers.00:00 Welcome & Meet Louis (OpenRouter Co‑Founder)00:27 Origin Story: De‑Risking AI App Costs (Hackathon Lessons)01:35 First Big Feature: End‑User Pays for Tokens (Sign in with OpenRouter)02:34 From Routing to Rankings: Scaling to Trillions of Tokens03:42 What OpenRouter Is Today: Reliable Inference Across 60+ Providers05:55 Why Teams Adopt It: Avoiding Model API Churn, Billing, and Vendor Lock‑In08:37 Winning Strategy: Don’t Build a “Magic Router”—Optimize Cost/Latency/Throughput18:58 From Chat to RAG + Memory: Building Persistent Agent Context20:37 Developer Bells & Whistles: Auto PDF Parsing and More21:11 Enterprise Readiness: Compliance, Security Guardrails & Model Presets22:22 Customer Growth at Warp Speed in the AI Era23:03 Spicy Future!

    34 min

  5. 23 Feb

    From 30 Seconds to 20ms: Solving Browser Speed for AI Agents (Chat with Catherine from Kernel)

    In this episode of The Infra Pod, hosts Tim Chen (Essence VC) and Ian Livingstone (Keycard) sat down with Catherine Jue, co-founder and CEO of Kernel, to explore the cutting-edge world of browser infrastructure for AI agents. Catherine shares her journey from Cash App to founding Kernel, explaining how she discovered the critical need for scalable browser automation when AI agents need to interact with the web. The conversation dives deep into the technical innovations behind Kernel's use of unikernels and micro VMs, which enable blazingly fast browser startup times (20ms vs 30+ seconds) and unique snapshot/restore capabilities. Catherine discusses the evolution from deterministic browser automation to truly agentic behavior, the challenges of optimizing for variable web workloads, and her optimistic vision for an AI-powered future where the pie expands rather than consolidates. This episode is packed with technical insights about infrastructure, agent tooling, and the future of how software interfaces will evolve in an agent-native world. 0:24 Catherine's startup journey and founding Kernel1:30 Cash App's OpenAI experiment sparks the idea3:56 Why browser infrastructure for AI agents?6:36 Unikernels: 20ms startup vs 30+ seconds15:02 Optimizing for variable web workloads23:25 Future of agent-native software32:05 Hot takes!

    41 min

  6. 9 Feb

    Coding agents need infra to apply code changes! (Chat with Tejas from Morph)

    Tim (Essence VC) and Ian (Keycard) sat down with Tejas Bhakta (CEO of Morph) to chat about building infrastructure for the fastest file edit APIs for coding agents. He shares how Morph delivers 10,000 tokens/second through speculative decoding, why cursor removed fast apply, and his vision for autonomous software that updates without prompts. The conversation covers subagent architecture, code search optimization, and the path to reliable AI coding at scale. Timestamps: 0:00 - Introduction0:29 - Why start Morph and pivoting through YC1:23 - The fast apply insight from Cursor3:42 - How fast apply works and speculative decoding6:09 - Use cases: when and where fast apply matters8:19 - Why Cursor removed fast apply9:22 - Morph's value prop beyond speed11:58 - Subagent architecture and SDK approach14:45 - Semantic search and code-specific tooling19:52 - Building custom coding agents vs platforms22:42 - Adoption inhibitors and the future of codegen23:26 - Spicy take: Autonomous software and reliability

    30 min

  7. 26 Jan

    Let's chat about vibe coding & Ralph! (Chat with Dexter at Humanlayer)

    In this episode of The Infra Pod, hosts Tim and Ian sit down with Dexter Horthy, CEO of Human Layer, to explore the evolution of AI coding agents and the future of software development. Dexter shares his journey from building data tools to discovering the real problem: making AI coding agents actually productive for senior engineers, not just juniors. The conversation dives deep into the research-plan-implement workflow that enables engineers to ship 99% of their code with AI assistance, the challenges of getting staff engineers to adopt AI tools, and why most AI coding ecosystems don't actually help you sell to enterprises. Dexter also shares his spicy take on how Ralph-style agents can be even further enhanced. Whether you're a skeptical senior engineer or an AI-curious developer, this episode offers practical insights into what actually works in production AI coding today. [0:00] Introduction & Dexter's JourneyWhy Dexter finally started a company, the failed data catalog pivot, and building an AI janitor for data warehouses [8:00] The Hard Lessons of AI Ecosystem HypeWhy there's no "SAML for AI agents" and what enterprises actually need versus what the hype machine promises [13:00] The Research-Plan-Implement BreakthroughHow to make senior engineers productive with AI, staying objective during research, and making decisions at the top of the context window [26:00] The Vibe Shift & Where We Are TodayWhen respected engineers started believing, the role of Ralph and spec-driven development, and what's working in production [37:00] Spicy Take: Ralph Goes to the Supreme

    43 min

  8. 12 Jan

    Building a bug-free vibe coding world (Chat with Akshay from Antithesis)

    In this episode of the Infra Pod, hosts Ian Livingston (Keycard) and Tim Chen (Essence VC) interviewed the Field CTO Akshay Shah of Antithesis, diving deep into the world of distributed systems, reliability, and the future of software testing. The conversation covers the challenges of building bug-free distributed systems, the story behind Antithesis, lessons from major outages, and the evolving landscape of infrastructure and AI-driven operations. Timeline with Timestamps: 00:00 – Introduction & guest background02:00 – What Antithesis does and why it matters06:00 – Real-world impact: Testing distributed systems (etcd, Kubernetes)09:00 – Major outages & lessons learned (AWS, Knight Capital)12:00 – The origins and philosophy behind Antithesis16:00 – The future of reliability, testing, and AI in infrastructure28:00 – Closing thoughts & where to learn more Links: Learn more about Antithesis: https://antithesis.comAntithesis on YouTube: @AntithesisHQ

    47 min
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About

The Infra Pod brings you insightful and thought-provoking discussions on the world of infrastructure software. This podcast is started by two engineers, Ian Livingstone (tech advisor for Snyk) and Tim Chen (General Partner at Essence VC), team up with a rotating cast of guests to dive deep into the latest trends and hot topics in the software infrastructure space.

Information

  • Creator
    The Infra Pod
  • Years Active
    2023 - 2026
  • Episodes
    64
  • Rating
    Explicit
  • Copyright
    © The Infra Pod
  • Show Website
    The Infra Pod
  • Provider

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