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