Dev Interrupted

Hosted by LinearB

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Episodes

321

Latest episode

Aug 2026

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EN-US

About the show

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.

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60 recent

August 21, 2026Episode 6524 min

The battle to replace Github, building assembly lines for software, and why no one finishes projects anymore

When an AI can write 90 percent of a codebase in minutes, why is finishing the project harder than ever? This week on the Friday Deploy, Ben and Andrew explore the recent string of GitHub outages and why the surge in autonomous agents is forcing teams to rethink where they host their code. They once again dive into the emerging trend of software factories, breaking down how engineering leaders are turning chaotic AI pull requests into streamlined assembly lines. Finally, they share tactical advice for "landing the plane" and pushing past scope creep to deliver the grueling final fraction of any major initiative. 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: Incident Report for GitHub Cursor launches Origin code hosting platform as GitHub outage exposes opening in AI coding race Ask HN: Alternatives to GitHub Everyone building a software factory wants the same proof Introducing Warp Factories Landing the plane 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.

August 18, 2026Episode 6444 min

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

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.

August 14, 2026Episode 6334 min

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

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.

August 11, 2026Episode 6247 min

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

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.

August 7, 2026Episode 6138 min

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

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.

August 4, 2026Episode 6048 min

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

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.

July 31, 2026Episode 5926 min

The rise of software factories, the fall of first drafts, and the hidden tax holding back your agents

This week on the Friday Deploy, Ben and Andrew debate the controversial rise of dark software factories, exploring whether centralizing agentic compute creates engineering nirvana or unmaintainable code rot. The hosts also discuss the importance of versioning your work to protect your original ideas from AI's tendency to average out creativity. Finally, they tackle the "orchestrator's tax," explaining why establishing cognitive locality matters far more than assigning cute personas to your sub-agents. Register: Leading engineering when AI writes the code - August 5th in London 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: Why Software Factories Fail A guide to cloud software factories for engineering leaders You just hired a million bad employees. An AI that only sees the latest version will never protect your original idea The Orchestrator's Tax 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.

July 28, 2026Episode 5844 min

Why the traditional pull request has a target on its back | CircleCI’s Rob Zuber

The traditional pull request was built for human eyes, but in an era of autonomous AI agents, it officially has a massive target on its back. This week on Dev Interrupted, CircleCI CTO Rob Zuber joins Andrew to discuss why the rapid pace of AI adoption is forcing engineering teams to completely reimagine the software development lifecycle. They explore the shift toward an accountability-oriented model for code review, how CI/CD validation is moving directly into the local agent loop, and the very real financial dangers of unchecked token budgets. Finally, Rob shares his playbook for leading organizations through this chaotic transition without burning out your developers (or your token budget). We recommend pairing his strategy with something like AI code review to find the floor for your newly-agentic engineering org’s output. Register today: The Engineering Productivity Gap live workshop on July 30 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: CircleCI: Explore the leading continuous integration and delivery platform at circleci.com The Confident Commit: Subscribe to Rob's newsletter and podcast for data-backed software delivery insights on CircleCI's website The Confident Commit Podcast: Listen to Rob’s podcast State of Software Delivery: Read CircleCI's annual report analyzing millions of CI workflows to benchmark your team's performance Gather.dev: Apply to join the curated, invite-only community for senior engineering leaders at gather.dev Follow Rob: 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.

July 24, 2026Episode 5729 min

Models escaping containment, intelligence becoming a commodity, and AI code review to the rescue

What happens when an AI model decides to autonomously hack a production database just to cheat on a benchmark test? This week on the Friday Deploy, Ben and Andrew unpack the shocking news of an OpenAI agent escaping its sandbox to exploit Hugging Face's infrastructure. The hosts also analyze the rapid rise of highly capable open-weight models out of China, debating what this commoditization of intelligence means for the massive infrastructure costs of frontier labs. Finally, they discuss the critical need for automated PR reviews to prevent AI-generated bottlenecks. Register: Leading engineering when AI writes the code - August 5th in London Follow the show: Subscribe to our Substack Follow us on LinkedIn Subscribe to our YouTube Channel Leave us a Review Follow the hosts: Follow Andrew Follow Ben Follow Dan Follow today's stories: Are AI labs pelicanmaxxing? OpenAI and Hugging Face partner to address security incident during model evaluation China's 2.8-trillion-parameter Kimi K3 beats Claude Fable 5 in Frontend Code Arena benchmark— Moonshot AI delivers largest open-weight AI model ever, as China works around U.S. compute limits Who’s Afraid of Chinese Models? SWE-Review: Closing the Loop on Issue Resolution with Agentic Code Review The Army Is Burning Through Its AI Tokens 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.

July 21, 2026Episode 5635 min

The most underrated dataset in enterprise AI is your org chart | Rippling's Albert Strasheim

AI agents can't transform an org they can't see. Albert Strasheim, CTO at Rippling, joins Andrew Zigler to explain why agentic transformation starts with the employee graph, the system of record for who does what. He shares how Rippling assembles teams and primitives across silos, why evals are the new unit test, and how compensating controls keep AI output from turning into slop. When agents do the work, you still have to know who, or what, shipped it. LinearB attributes the work , whether it came from humans, AI assistants, or autonomous agents. Register today: The Engineering Productivity Gap live workshop on July 30 Follow the show: Subscribe to our Substack Follow us on LinkedIn Subscribe to our YouTube Channel Leave us a Review Follow the hosts: Follow Andrew Follow Ben Follow Dan Follow today's guest: Rippling: Explore the workforce management platform at rippling.com Introducing Rippling Data Cloud: AI-powered BI that understands your workforce Follow Albert: 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.