Heavybit Podcasts

On episode 14 of Third Loop, the Progressive Delivery team sits down with Dr. Cat Hicks, psychologist and author of The Psychology of Software Teams. Cat unpacks the “Brains in Jars” mental model, the belief that engineers are interchangeable pure-cognition units, and explains why organizations that hold it struggle to use AI well. The conversation covers learning debt, overproduction pressure, an...

On episode 14 of Data Renegades, CL Kao speaks with Hannes Mühleisen, co-creator of DuckDB, about building databases that people actually want to use. Hannes explains how conversations with frustrated statisticians shaped DuckDB’s architecture and why useful software sometimes requires abandoning your own assumptions. They explore DuckLake, the Quack client-server protocol, and how a focus on huma...

On episode 6 of Lab Notes, Amir Zohrenejad speaks with James Evans about the surprising finding that reasoning models simulate a society rather than a single brain. They dig into sycophancy and why users trust AI less but perform better when it has a point of view, the Computational Life experiments that evolved self-replicating programs from a primordial soup of code, and James’s argument that di...

On episode 45 of Open Source Ready, Brian Douglas and John McBride speak with Dotta about Paperclip, an open-source platform for managing teams of AI agents. They explore what happens when agents produce more work than humans can review, why permissions need to extend beyond a separate computer, and how engineering judgment changes when writing code becomes easier.

On episode 13 of Third Loop, the Progressive Delivery team speaks with Jennifer Riggins about why faster code doesn’t automatically mean better software. They explore how AI exposes organizational bottlenecks, why psychological safety matters, and what Spotify’s growing feature set reveals about user value. Jennifer makes the case for smaller experiments, stronger feedback loops, and keeping peopl...

On episode 60 of Generationship, Rachel Chalmers speaks with Vasanth Mohan of SambaNova about when faster AI agents actually mean better work. They explore why token consumption and code volume are poor substitutes for business value, how inference latency interrupts productive workflows, and why engineering taste still matters. Sometimes the most valuable thing an engineer can produce is less cod...

On episode 44 of Open Source Ready, Brian Douglas and John McBride sit down with Mikyo King to explore why an agent can fail even when its model gets things right. They discuss observing the full agent workflow, using evaluations to uncover unexpected behavior, and testing whether skills actually improve results. Along the way, Mikyo shares how Arize approaches open source collaboration as coding...

On episode 12 of Third Loop, the Progressive Delivery team speaks with Steph Hippo, Platform Engineering Director at Honeycomb, about what happens when AI accelerates development beyond the pace humans can absorb. They explore safe defaults, evolving code reviews, and the feedback loops that help teams understand what they ship. Steph makes the case for reinvesting saved time in better decisions,...

On episode 59 of Generationship, Rachel Chalmers speaks with Emily Long and Alex Zenla, co-founders of Edera, about rethinking the foundations of cloud and AI security. They explain how an IoT side project became an approach to workload isolation built around Xen and Rust, and why AI agents are making stronger security boundaries increasingly urgent. Along the way, they discuss complementary leade...

In episode 5 of Lab Notes, Amir Zohrenejad speaks with Aoden Teo, co-founder and CEO of Miso Labs, about what it will take for voice AI to become truly humanlike. They explore the limitations of today's speech-to-text and text-to-speech pipelines, the promise of full-duplex speech models, and the technical challenges around audio tokenization, turn-taking, emotion, reasoning, and real-time in...

On episode 11 of Third Loop, the Progressive Delivery team sits down with Chad Fowler to explore regenerative software and what architecture looks like when AI makes code cheap enough to continually replace. They discuss Phoenix Architecture, Pace Layers, observability, architectural constraints, and why the system itself, rather than any individual implementation, may become the real asset in an...

On episode 58 of Generationship, Rachel Chalmers sits down with Anastasia Marchenkova. They explore what it will take to move quantum computing from promising hardware to useful, production-ready systems, including better orchestration across quantum, classical, and AI compute. Anastasia also discusses open-source infrastructure, the limits of AI automation, and her larger vision of making powerfu...

On episode 4 of Lab Notes, Amir Zohrenejad speaks with Junchen Jiang about why KVCache may be better understood as reusable, AI-native data rather than a temporary inference optimization. They explore how LMCache and CacheBlend can reduce redundant computation, move context across distributed inference systems, and help support increasingly complex AI agents. The conversation also covers multimoda...

On episode 10 of Third Loop, the Progressive Delivery team speaks with Honeycomb co-founder and CTO Charity Majors about observability, AI, and the changing economics of software development. They explore a future where code is increasingly disposable and regenerable while architecture, constraints, production behavior, and promises to users become the durable artifacts that matter. Along the way,...

On episode 12 of High Leverage, Joe Ruscio sits down with Dexter Horthy of HumanLayer. They explore the promise and limitations of autonomous coding, including why today’s models excel at bounded programming tasks but struggle to account for the long-term consequences of architectural decisions. The conversation covers dark software factories, code review bottlenecks, program design, technical deb...

In episode 54 of The Kubelist Podcast, Marc and Benjie sit down with David Crawshaw. David shares how a weekend WireGuard experiment became Tailscale, and how a series of unsuccessful developer-tool experiments eventually became exe.dev. The conversation offers a candid look at product discovery, technical failure, cloud economics, and building infrastructure for AI agents.

On episode 41 of Open Source Ready, Brian Douglas and John McBride sit down with Phil Estes. They explore why the definition of a container remains surprisingly fuzzy, how microVM-backed sandboxes could support the next generation of AI agents, and what AI-generated contributions mean for projects like containerd. Phil also explains why the future of open source depends as much on trusted maintain...

On episode 9 of Third Loop, the Progressive Delivery team explores the complicated relationship between AI, automation, and human creativity. Kim Harrison, Adam Zimman, and Heidi Waterhouse discuss AI’s ability to lower technical barriers and reduce toil, along with its tendency to strip away context, reinforce sameness, and confidently produce answers it does not understand. Along the way, they e...

On episode 3 of Lab Notes, Amir Zohrenejad sits down with Qizheng Zhang to explore one of the fastest-moving areas of AI research: recursive self-improvement. Together, they discuss Meta-Harness, context engineering, and why the future of AI may depend as much on the software surrounding models as the models themselves. The conversation also examines evaluation, agentic systems, and the limits of...

On episode 57 of Generationship, Rachel Chalmers sits down with Navneet Kaur, founder of FemTech India and TechThrive Ventures. Together they explore why women's health innovation must extend beyond Western markets, how AI is reshaping femtech, and what founders need to understand about trust, culture, and personalization when building global healthcare companies.

On episode 8 of Third Loop, the Progressive Delivery team sits down with Melinda Fekete to discuss FeatureOps, developer experience, and modern software delivery. The conversation covers feature flag lifecycles, runtime control, experimentation, chaos engineering, and why progressive delivery is becoming even more important in the age of AI-assisted development.

On episode 92 of o11ycast, Ray Myers joins Ken and Jess to explore how observability, reliability engineering, and formal software engineering practices are becoming even more important as AI coding agents take on larger roles in development. Rather than viewing AI as a replacement for established engineering disciplines, Ray argues that techniques like continuous delivery, testing, specifications...

On episode 2 of Lab Notes, Amir Zohrenejad sits down with Hanchen Li to explore the systems that make modern AI agents faster, more efficient, and better at learning from experience. They discuss KV Cache optimization, long-context inference, prompt learning, continual learning, and why better benchmarks may be just as important as larger models in advancing AI research.

On episode 40 of Open Source Ready, Brian Douglas and John McBride sit down with Orhun Parmaksiz to explore Ratty, his experimental GPU-rendered terminal emulator that combines traditional command-line workflows with interactive 3D graphics. They discuss the future of terminal user interfaces, how AI is accelerating developer tooling, and what recent supply chain attacks on Arch Linux reveal about...

On episode 7 of Third Loop, the Progressive Delivery team speaks with Nathen Harvey about the intersection of AI, DevOps, and user-centric software development. Together, they examine what DORA's research reveals about high-performing teams, why shipping faster doesn't automatically create more value, and how organizations can build stronger feedback loops with users. Along the way, they...