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!

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 Kernel
1:30 Cash App's OpenAI experiment sparks the idea
3:56 Why browser infrastructure for AI agents?
6:36 Unikernels: 20ms startup vs 30+ seconds
15:02 Optimizing for variable web workloads
23:25 Future of agent-native software
32:05 Hot takes!

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 - Introduction
0:29 - Why start Morph and pivoting through YC
1:23 - The fast apply insight from Cursor
3:42 - How fast apply works and speculative decoding
6:09 - Use cases: when and where fast apply matters
8:19 - Why Cursor removed fast apply
9:22 - Morph's value prop beyond speed
11:58 - Subagent architecture and SDK approach
14:45 - Semantic search and code-specific tooling
19:52 - Building custom coding agents vs platforms
22:42 - Adoption inhibitors and the future of codegen
23:26 - Spicy take: Autonomous software and reliability