Dev Interrupted

Software itself is fundamentally changing. We explore the transition to agentic orchestration, vibe coding, and AI-native development, grounding the conversation in the principles that have always defined great engineering. On Tuesdays, we interview the founders, architects, and builders of the world’s most impactful tech to uncover the timeless engineering principles and strategies shaping the next era of development. And on Fridays, we drop an end-of-week roundup of the biggest news in AI and software, and what it actually means for your career, your craft, and your life as a developer. Subscribe to stay ahead of the next era of code.

Dev Interrupted is a technology podcast hosted by LinearB, with 320 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.

LinearB hosts Dev Interrupted, a technology show with 320 episodes published.

Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.

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  Episode #64

  Agent, skill, or MCP? Which to use and when to use them | AWS’ Clare Liguori

  Aug 18, 202644 minS6

  Every engineering team wants to build its own custom AI agent, but what if all your organization needs is a standardized skill or a stateless MCP server? This week on Dev Interrupted, Andrew sits down with AWS Senior Principal Engineer Clare Liguori to untangle the ecosystem of modern agentic architecture. They work through how a team decides which AI building blocks to own, and how to get that reach without inheriting a maintenance burden. Clare shares her perspective on the simplified MCP 7.28 spec and why stripping away heavy custom scaffolding is how enterprise AI scales. That same shift is what makes MCP a gamechanger for LinearB customers, bringing your SDLC context layer, git, project management, and software delivery, into any agentic surface. What could your agents achieve if they can query your SDLC ? Get the guide: The AI engineering productivity gap - how elite teams pull ahead in 2026 Register: Dev Interrupted Presents: The Software Factory Roundtable Follow the show: Subscribe to our Substack Follow us on LinkedIn Subscribe to our YouTube Channel Follow the hosts: Follow Andrew Follow Ben Follow Dan Follow today's guest: Strands Agents SDK: Explore the open-source framework for building model-driven agents at strandsagents.com MCP 7.28): Dive into the new stateless specification at modelcontextprotocol.io Follow Clare: LinkedIn | X OFFERS Start Free Trial: Get started with LinearB's AI productivity platform for free. Book a Demo: Learn how you can ship faster, improve DevEx, and lead with confidence in the AI era. LEARN ABOUT LINEARB AI Code Reviews: Automate reviews to catch bugs, security risks, and performance issues before they hit production. AI & Productivity Insights: Go beyond DORA with AI-powered recommendations and dashboards to measure and improve performance. AI-Powered Workflow Automations: Use AI-generated PR descriptions, smart routing, and other automations to reduce developer toil. MCP Server: Interact with your engineering data using natural language to build custom reports and get answers on the fly.

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  Episode #63

  Telling your agent “no” is a moat now, rearward deployed engineers, and harnessing the context for your SDLC

  Aug 14, 202634 minS6

  This week on the Friday Deploy, Ben and Andrew explore Uber's strategy of "rearward deploying" engineers to spread agentic AI workflows into departments like legal and marketing. They also dive into Anthropic making Claude Code's Auto Mode the default, Meta's new on-device Muse Glimmer model, and Tim O'Reilly's case for an open source AI ecosystem. Finally, they break down context engineering for the SDLC and examine new research showing why generalized agent skills outperform personalized ones. Register: Dev Interrupted Presents: The Software Factory Roundtable Follow the show: Subscribe to our Substack Follow us on LinkedIn Subscribe to our YouTube Channel Follow the hosts: Follow Andrew Follow Ben Follow Dan Follow today's stories: After starting the tokenmaxxing panic, Uber's CTO is back with a very different AI story Auto mode is now the default in Claude Code for Pro, Max, and Team plans Introducing Muse Glimmer: An Open Agentic Model That Runs on Your Device Why Open Source Matters for AI Your SDLC is your context engineering Do personalized skills help coding agents? An empirical study of developer interaction histories OFFERS Start Free Trial: Get started with LinearB's AI productivity platform for free. Book a Demo: Learn how you can ship faster, improve DevEx, and lead with confidence in the AI era. LEARN ABOUT LINEARB AI Code Reviews: Automate reviews to catch bugs, security risks, and performance issues before they hit production. AI & Productivity Insights: Go beyond DORA with AI-powered recommendations and dashboards to measure and improve performance. AI-Powered Workflow Automations: Use AI-generated PR descriptions, smart routing, and other automations to reduce developer toil. MCP Server: Interact with your engineering data using natural language to build custom reports and get answers on the fly.

  ListenShow Notes
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  Episode #62

  The playbook to close your team’s AI productivity gap | LinearB’s Yishai Beeri

  Aug 11, 202647 minS6

  This week, LinearB CTO Yishai Beeri joins the show to unpack fresh mid-year benchmark data revealing a widening productivity gap between elite engineering teams and the rest of the industry. The conversation explores why tracking pure AI adoption is a trap, detailing how leaders must shift focus to measuring true leverage through metrics like PR yield rate and cost per PR. Finally, they break down why fully autonomous agentic workflows are currently bottlenecking at the review stage and how to establish human ownership to prove real ROI to your finance team. Get the guide: The AI engineering productivity gap - how elite teams pull ahead in 2026 Register: Dev Interrupted Presents: The Software Factory Roundtable Follow the show: Subscribe to our Substack Follow us on LinkedIn Subscribe to our YouTube Channel Follow the hosts: Follow Andrew Follow Ben Follow Dan Follow today's guest: The AI Productivity Gap Report: Read the full report and explore the 2026 data from 2.7 million PRs LinearB: Learn how to measure AI leverage and optimize your engineering workflows at linearb.io Connect with Yishai: LinkedIn OFFERS Start Free Trial: Get started with LinearB's AI productivity platform for free. Book a Demo: Learn how you can ship faster, improve DevEx, and lead with confidence in the AI era. LEARN ABOUT LINEARB AI Code Reviews: Automate reviews to catch bugs, security risks, and performance issues before they hit production. AI & Productivity Insights: Go beyond DORA with AI-powered recommendations and dashboards to measure and improve performance. AI-Powered Workflow Automations: Use AI-generated PR descriptions, smart routing, and other automations to reduce developer toil. MCP Server: Interact with your engineering data using natural language to build custom reports and get answers on the fly.

  ListenShow Notes
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  Episode #61

  Model welfare, building a civilization for agents, and the CI/CD landrush

  Aug 7, 202639 minS6

  This week on the Friday Deploy, Ben and Andrew break down Steve Yegge's radical approach to orchestrating agentic civilizations and pushing code straight to main without traditional CI/CD. The conversation also highlights the art of constructing effective AI harnesses by balancing context complexity with cognitive locality and the Socratic method. Finally, they dive into the math community's existential crisis as AI accelerates the frontier of knowledge far beyond the speed of human peer review. Register: Dev Interrupted Presents: The Software Factory Roundtable Follow the show: Subscribe to our Substack Follow us on LinkedIn Subscribe to our YouTube Channel Follow the hosts: Follow Andrew Follow Ben Follow Dan Follow today's stories: Microsoft Tells Engineers ‘Tokenmaxxing Is Not What We Are Optimizing For’ The Shape of Things to Come The Shape of Things to Come - Part 2: Model Welfare for Agentic Engineers How AI helped Socrates to help me actually understand myself The Month AI Conquered Math: The Full Story How to Build an Effective Agent Harness Making AI Visible, Not Vanished: How AI Policies Reshape Developer Experience on GitHub OFFERS Start Free Trial: Get started with LinearB's AI productivity platform for free. Book a Demo: Learn how you can ship faster, improve DevEx, and lead with confidence in the AI era. LEARN ABOUT LINEARB AI Code Reviews: Automate reviews to catch bugs, security risks, and performance issues before they hit production. AI & Productivity Insights: Go beyond DORA with AI-powered recommendations and dashboards to measure and improve performance. AI-Powered Workflow Automations: Use AI-generated PR descriptions, smart routing, and other automations to reduce developer toil. MCP Server: Interact with your engineering data using natural language to build custom reports and get answers on the fly.

  ListenShow Notes
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  Episode #60

  Why AI gains are unevenly distributed in your engineering team | Asana’s Arnab Bose

  Aug 4, 202649 minS6

  Why are 75% of knowledge workers using AI, yet only 5% of companies seeing meaningful productivity gains? This week on Dev Interrupted, Asana Chief Product Officer Arnab Bose explains why scaling enterprise AI means shifting from isolated chatbots to fully integrated agentic work management. He breaks down how Asana is turning AI from a tool into a transparent digital teammate with shared memory, full audit trails, and role-based access controls. The conversation closes on Asana's acquisition of Stack AI, the upcoming Command product for R&D teams, and which metrics prove AI ROI . Get the guide: The AI engineering productivity gap - how elite teams pull ahead in 2026 Follow the show: Subscribe to our Substack Follow us on LinkedIn Subscribe to our YouTube Channel Follow the hosts: Follow Andrew Follow Ben Follow Dan Follow today's guest: Asana: Explore the work management platform and learn more about Agentic Work Management at asana.com Stack AI: Read about Asana's acquisition of the no-code AI workflow automation platform on the Asana Blog Connect with Arnab: LinkedIn OFFERS Start Free Trial: Get started with LinearB's AI productivity platform for free. Book a Demo: Learn how you can ship faster, improve DevEx, and lead with confidence in the AI era. LEARN ABOUT LINEARB AI Code Reviews: Automate reviews to catch bugs, security risks, and performance issues before they hit production. AI & Productivity Insights: Go beyond DORA with AI-powered recommendations and dashboards to measure and improve performance. AI-Powered Workflow Automations: Use AI-generated PR descriptions, smart routing, and other automations to reduce developer toil. MCP Server: Interact with your engineering data using natural language to build custom reports and get answers on the fly.

  ListenShow Notes

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