Heavybit Podcast Network: Master Feed. This is where you can subscribe to all episodes of all shows in the Heavybit Podcast Network.
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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 AI-native future.
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 powerful computing and scientific tools more broadly accessible.
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 multimodal workloads, open-source infrastructure, and the future of AI systems research.
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, Charity shares her perspective on responsible AI adoption, engineering in nondeterministic systems, and why production remains the ultimate source of truth.
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 debt, and the continuing importance of experienced engineers.
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 maintainers and healthy communities as it does on code.
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 encounter whale dictionaries, ancient scrolls, AI-written memos, autonomous tractors, and the dangerously comfortable “Yes Bubble.”
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 today's autonomous AI research.
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, and formal verification provide the confidence needed to safely harness AI-generated code.
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 the evolving security landscape for open source software.
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 discuss agentic systems, platform engineering, and even AI-powered kitchen appliances.
On this debut episode of Lab Notes, Amir Zohrenejad is joined by Ren Wang, a researcher and PhD student at UC Berkeley, to explore the state of physical AI and why robotics has progressed differently from large language models. They discuss data scarcity, world models, simulation, dexterity, and the challenges of building robots that can reliably operate in the real world.
On episode 39 of Open Source Ready, Brian Douglas and John McBride speak with Zach Smith, creator of Kplane, about rethinking Kubernetes for an AI-driven future. Zach explains how virtualized control planes could enable isolated cluster experiences at massive scale, while the conversation explores developer experience, AI tooling, and the possibility that future AI agents may each require their own cloud.
On episode 56 of Generationship, Rachel Chalmers sits down with Mark Brocato, founder of Mockaroo and creator of Fabricate, to explore the evolution of synthetic data in the age of AI. Mark shares how a simple internal QA tool grew into one of the most widely used synthetic data platforms and discusses how agentic AI is transforming software development, testing, and data generation.
On episode 13 of Data Renegades, CL Kao sits down with Josh Wills to explore how AI agents are reshaping software engineering, data science, and data infrastructure. They discuss verification, benchmarking, pre-training data pipelines, multimodal AI, and why understanding a problem may matter more than writing code. Josh also shares lessons learned from decades of building large-scale data systems and his journey from management back to hands-on engineering.
On episode 6 of Third Loop, Kim Harrison, Adam Zimman, James Governor, and Heidi Waterhouse sit down with Betty Junod. Together, they explore how agentic coding tools are enabling non-developers to build software for themselves, creating a world where the ideal customer profile might be just one person. They discuss personalization, Progressive Delivery, open source, and what happens when users become builders.
On episode 53 of The Kubelist Podcast, Marc Campbell and Benjie De Groot sit down with Anurag Goel. Anurag shares his journey from early employee at Stripe to founder and CEO of Render, one of the fastest-growing application platforms in cloud infrastructure. They discuss Kubernetes, platform engineering, bare metal, AI agents, and what the future of application deployment looks like.
On episode 91 of o11ycast, Ken Rimple and Jess Kerr sit down with Janaki Vivrekar. Janaki shares how Amplitude is building AI-powered analytics agents, why evaluation frameworks are becoming essential to AI product development, and how teams can use observability techniques to improve agent performance over time. The conversation explores eval-driven development, production feedback loops, and the challenges of helping AI systems reason about complex business data.
On episode 52 of The Kubelist Podcast, Marc Campbell and Benjie De Groot speak with Hugo Santos. They discuss the evolution of Namespace Labs, why traditional cloud infrastructure isn't always optimized for developer workflows, and what it takes to build a vertically integrated platform for builds, testing, and developer productivity. Hugo also shares lessons learned from nearly a decade at Google and years of startup building.
On episode 38 of Open Source Ready, Brian Douglas and John McBride speak with Graham Christensen, CEO of Determinate Systems, about the evolution of the Nix ecosystem and why more organizations are embracing reproducible infrastructure. They discuss secure package management, enterprise adoption challenges, open source business models, and how AI tooling is rapidly reshaping software engineering workflows.
On episode 12 of Data Renegades, CL Kao sits down with Maxime Beauchemin to explore what happens when software teams start working alongside armies of AI agents. Max shares the thinking behind Agor, his collaborative platform for orchestrating coding agents, and reflects on how AI is reshaping engineering, product, design, and data work. They also dive into the future of agentic workflows, technical collaboration, and what human roles may look like in the years ahead.
