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

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 Journey
Why 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 Hype
Why there's no "SAML for AI agents" and what enterprises actually need versus what the hype machine promises

[13:00] The Research-Plan-Implement Breakthrough
How 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 Today
When 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

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 background
• 02:00 – What Antithesis does and why it matters
• 06:00 – Real-world impact: Testing distributed systems (etcd, Kubernetes)
• 09:00 – Major outages & lessons learned (AWS, Knight Capital)
• 12:00 – The origins and philosophy behind Antithesis
• 16:00 – The future of reliability, testing, and AI in infrastructure
• 28:00 – Closing thoughts & where to learn more

Links:

• Learn more about Antithesis: https://antithesis.com
• Antithesis on YouTube: @AntithesisHQ

Join Tim from Essence VC and Ian Livingston from Keycard for the year-end 2025 recap of Infra Pod! In this special episode, Tim and Ian reflect on their favorite moments, hottest takes, and biggest lessons from a year of rapid change in infrastructure, AI, and agent technology.

They revisit standout episodes—like deep dives into browser automation, the evolving role of memory in LLMs, and the disruptive potential of agent sandboxes. The hosts discuss how companies are pivoting in the AI era, the importance of adapting quickly, and the surprising ways hardware choices are shaping the future of compute.

Looking ahead, Tim and Ian share bold predictions for 2026, debate the next big abstractions in infrastructure, and invite listeners to share their own hot takes and favorite episodes. Whether you’re an engineer, founder, or just passionate about the future of tech, this episode is packed with insights, energy, and a look at what’s next for the Infra Pod community.

In this episode of The Infra Pod, hosts Tim from Essence VC and co-host Ian Livingston (Keycard) interviewed Sammy Sdu, CEO of Eventual, a multimodal data processing platform. Sammy shares his journey from AI research and self-driving cars to founding Eventual, discusses the challenges of processing unstructured and multimodal data, and explores the future of data engineering, scalability, and the role of agents in modern data pipelines.

Timestamps:

• 02:47 — Data processing challenges & founding Eventual
• 09:40 — Real-world use cases & business impact
• 24:20 — The future of data engineering & tools
• 40:00 — Closing thoughts & where to learn more

In this episode of The Infra Pod, hosts Tim and Ian are joined by Anurag, CEO of Render, to discuss the journey of building a modern cloud platform from scratch. The conversation covers Anurag’s background at Stripe, the challenges of cloud infrastructure, the evolution of developer tools, the importance of abstraction and taste in product design, and the future of agent-driven development. The episode is packed with insights on scaling platforms, developer experience, and the shifting landscape of cloud computing.

Welcome to Episode 53 of The Infra Pod! Hosts Tim from Essence and Ian from Keycard are joined by special guest Alex Eagle, CEO and co-founder of Aspect Build. In this episode, Alex shares his journey from working on Angular at Google to founding a company around Bazel, Google's open-source build tool. The conversation dives deep into the challenges and motivations behind building developer infrastructure, the evolution of CI/CD systems, and the unique strengths and hurdles of adopting Bazel in organizations of all sizes.

The trio explores the future of software development, the impact of AI on coding and build systems, and the ongoing debate between monorepos and polyrepos. Alex also discusses Aspect's mission to make Bazel more accessible and the broader implications for developer productivity in an agentic, AI-driven world. Whether you're a platform engineer, open-source enthusiast, or just curious about the future of build tools, this episode is packed with insights and spicy predictions for the future of developer infrastructure.

• 00:00 – Introduction & Guest Background
  Tim and Ian introduce Alex Eagle, who shares his journey from Google to founding Aspect Build.

• 04:20 – Why Bazel?
  Alex explains the motivation behind focusing on Bazel, its challenges, and the analogy to municipal infrastructure.

• 10:55 – Bazel in the Real World
  Discussion on Bazel’s adoption, who should use it, and the hurdles organizations face.

• 21:06 – The Future: AI, Agents, and Build Systems
  Exploring how AI and agentic coding are changing developer infrastructure and Bazel’s evolving role.

• 43:01 – Closing & Takeaways
  Final thoughts, how to learn more about Aspect and Bazel, and episode wrap-up.

In this episode of the Infra Pod, hosts Tim (Essence VC) and Ian (CEO of Keycard) sat down with Lucas Thelosen, founder of Gravity and former head of product for data and AI at Google. Lucas shares his journey from leading teams at Google and Looker to launching Gravity, a company focused on bridging the gap between business users and data through generative AI.

The conversation dives deep into the challenges of data analysis in modern organizations, the evolution of AI-powered tools like Orion, and how generative AI is transforming the way companies leverage their data. Lucas discusses the importance of semantic layers, onboarding AI agents, and the future of data teams in a world where AI can automate complex analysis and reporting.