Big Ideas in App Architecture

Cockroach Lab’s Big Ideas in App Architecture is a podcast for architects and engineers building modern data-intensive applications and systems. In every weekly episode, an innovator joins the show to share useful insights from their experiences building reliable, scalable, maintainable systems. Welcome to Big Ideas in App Architecture!

Big Ideas in App Architecture is a business podcast hosted by Unknown Host, with 70 episodes on record and a Required Pod Score of 80.

Unknown Host hosts Big Ideas in App Architecture, a business show with 70 episodes published.

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  Big Ideas in App Architecture

  Introducing Cockroach Continuum | A Big Ideas in App Architecture Exclusive

  Sep 16, 202636 min

  This episode marks a big moment for Cockroach Labs, a refreshed brand and the introduction of Cockroach Continuum! David Joy sits down with Tara Jana (TJ), who joined Cockroach Labs earlier this year and has been deep in the work behind everything you're about to hear. TJ has spent 21 years at the intersection of deep technology and storytelling, starting as an engineer, moving through solution architecture and field engineering at Microsoft, then taking products like Amazon CodeGuru and Kendra to market before landing at Cockroach Labs. The two begin by unpacking what's shifting across the database industry as AI agents multiply faster than any team can manage and why the companies with a data foundation built to absorb that growth will scale successfully. That shift sets the stage for Cockroach Continuum, The Agentic Database Cloud. TJ breaks down what Continuum delivers and walks us through the foundation underneath it: database virtualization, elastic infrastructure through Plenum, and agent-assisted operations through Aegis. We also get into the economics of it all, including consumption-based pricing that means paying for what you use, not what you provision for peak demand. Learn more about Cockroach Labs: cockroachlabs.com Learn more about TJ: [LinkedIn]

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  Big Ideas in App Architecture

  The Everything Trap: Building AI Software That Lasts with Sam Hilsman

  Jul 22, 202648 min

  Generating working software with AI has never been easier, but every shortcut a team takes today is a debt it pays back later. In this episode, David talks with Sam Hilsman, co-founder and CEO of CloudFruit , a studio that builds ERPs, analytics platforms, and custom products — including a custom ERP for a Chicago fabrication studio. Drawing on a path that runs from philosophy and healthcare administration into technical leadership, Sam makes the case that speed is the most underpriced risk in AI-assisted building. Sam unpacks his "Everything Trap" thesis: every decision incurs "change debt," so teams should build "icebergs, not ice sheets" — going narrow and deep, tightly scoping, testing relentlessly, and resisting feature bloat. He traces how his own AI use evolved from simple writing tasks to daily coding, and why he now works primarily in Claude Code alongside tools like Playwright for QA and Remotion for video. He shares hard-won lessons from an early venture (HiiBo) around context management and pivoting, the unsolved problem of authentication for agents, and where real moats, governance, and ethical guardrails still need to come from as agents scale.

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  Big Ideas in App Architecture

  Why Inference Engineering Is the Next Big Role in AI with Philip Kiely

  Jun 17, 202652 min

  ​Most teams moving AI into production quickly discover that generating an output is the easy part; running it reliably, efficiently, and at scale is a discipline of its own.In this episode, David talks with Philip Kiely, engineer at Baseten and author of Inference Engineering , a free guide to building and operating AI inference systems. Philip argues that every company will soon need a dedicated team to own inference, and draws on his work at Baseten to explain why it demands fluency across GPU optimization, distributed systems, model correctness, and developer experience all at once. He walks through how agentic workloads are reshaping inference demands, which open-weight models are worth watching, and key optimization techniques including KV cache reuse, quantization, and speculative decoding. Grab your copy of Inference Engineering here: https://www.baseten.co/inference-engineering/

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  Big Ideas in App Architecture

  Distributed Systems, Linkerd, and the Cost of Network Calls with William Morgan from Buoyant

  May 20, 202646 minS0

  <b>In Kubernetes environments, concerns like retries, security, observability, and traffic control often end up scattered across application code, leading to duplicated logic, inconsistent behavior, and systems that are harder to operate and debug. </b><b>The service mesh was designed to solve exactly that.</b><br /><b></b><br /><b>In this episode, David talks with William Morgan, co-founder and CEO of Buoyant, about the origins of the service mesh and the role Linkerd plays today. Linkerd is an open source, CNCF-graduated service mesh for Kubernetes, built in Rust, that provides security, observability, and reliability. </b><br /><b></b><br...

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  Big Ideas in App Architecture

  Making Software as Durable as Data with Peter Kraft from DBOS

  Apr 15, 202644 minS0

  <b>Most workflow and orchestration tools rely on external systems and fragile state management, making it hard for applications, especially AI agents to recover from failures or long running interruptions.</b><br /><b></b><br /><b>In this episode, David talks with Peter Kraft, co-founder of DBOS, about a new approach to durable execution. DBOS is a lightweight, database-backed library that checkpoints program state so applications can resume after crashes, upgrades, or API failures. Originating from Stanford research with Matei Zaharia and Michael Stonebraker, the idea is to make software as durable as data by storing application state in the...

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