Dev Interrupted

LinearB

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.

Play

Open in

35 episodes
Avg 39 min
English

Episodes 35

Newest Oldest Longest

All20 Unplayed20 In progress0 Played0

Counted on this page — what you have heard stays on this device, so it is not something the list can be paged by.

S6 · E77
Tuesday · 46 min
Multiplayer AI will revolutionize the way we work | OpenClaw Foundation’s Vincent Koc
Agents made each engineer faster, but the handoffs between them still run through copy and paste. OpenClaw Foundation chief architect Vincent Koc ran into that friction on his own team, and their answer was to move the engineering work of building OpenClaw inside OpenClaw itself. This week on Dev Interrupted, he joins Andrew to walk through the multiplayer setup behind OpenClaw 2.0, where teammates and their agents can jump into each other’s sessions on shared servers and pick up work when someone goes to sleep. Vincent explains how tools like Git Crawl keep their agents aware of everything happening across the repo, and why the piece that’s still missing is the why behind a decision. Save your seat: What your software factory is doing to your engineers Join us at AGNTCon + MCPCon on Oct 22 & 23 in San Jose. Use code MEDIA25 for 25% off your ticket. 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: OpenClaw Foundation: openclaw.org The foundation behind OpenClaw, which Vincent serves as chief architect. OpenClaw: openclaw.ai The open source personal AI assistant at the center of the conversation. OpenClaw 2.0, Accidentally: openclaw.ai/blog/openclaw-2-accidentally The release post for OpenClaw 2.0 and its multiplayer features. OpenClaw on GitHub: github.com/openclaw The org’s open source repos, all under MIT. OpenClaw security: openclaw.ai/security The project’s security page, which Vincent points to for the full record of reported vulnerabilities. Git Crawl: github.com/openclaw/gitcrawl The team’s GitHub issue and pull request crawler that keeps their agents aware of work across the repo. Crabbox: github.com/openclaw/crabbox The testing infrastructure the team built when nothing out there fit. Tideglass: github.com/vincentkoc/tideglass Vincent’s side project for inferring intent and preference profiles for agents. Beads: github.com/steveyegge/beads Steve Yegge’s git-backed issue tracker for coding agents. Wikinomics: dontapscott.com/books/wikinomics The book on mass collaboration that Vincent keeps coming back to. Connect with Vincent: 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.
S6 · E76
October 13 · 45 min
Building the software factory from the spec up | LinearB's Ariel Illouz & Ofer Affias
LinearB's software factory spends more time on the spec than on the code. VP of Engineering Ariel Illouz spent the last year moving his team of about 30 engineers from vibe coding to spec-driven development, starting with a single spec-writing skill and a rule that every story above three story points gets a spec. This week on Dev Interrupted, he and returning guest Ofer Affias, LinearB's senior director of product, join Andrew to walk through a project Ariel puts at six months without AI that shipped in roughly four weeks, at least two of them spent on specs. Ofer explains why proving the impact meant measuring AI adopters as separate cohorts. They close the conversation on where the software factory goes next, as agents take over more of the loops humans run today. Save your seat: What your software factory is doing to your engineers Join us at AGNTCon + MCPCon on Oct 22 & 23 in San Jose. Use code MEDIA25 for 25% off your ticket. 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: LinearB Metrics Builder: The custom metrics builder Ariel's team built spec-first, a project he puts at six months without AI. LinearB AI benchmarks: The AI engineering productivity gap: how elite teams pull ahead in 2026. Connect with Ariel: LinkedIn Connect with Ofer: 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.
S6 · E75
October 6 · 48 min
A neutral home for MCP, A2A, goose, and more | AAIF co-founder Manik Surtani
MCP was already a hit before it had a neutral home. Then Manik Surtani helped launch the Agentic AI Foundation, and MCP's SDK downloads grew fivefold to over a billion. This week on Dev Interrupted, he joins Andrew to share why he expects the same kind of growth for A2A and the foundation's other newest projects, and why these protocols belong together in a neutral place. Manik also shares the unique reasons behind A2A’s rapid adoption in China’s mobile app ecosystem. They close the conversation on why open source projects like Goose now want your ideas instead of your pull requests, and the neverending roadshow making it all possible out in the community right now. Save your seat: What your software factory is doing to your engineers Join us at AGNTCon + MCPCon on Oct 22 & 23 in San Jose. Use code MEDIA25 for 25% off your ticket. 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: Agentic AI Foundation (AAIF): The foundation's home for working groups, blogs, events and news https://aaif.io The Daily Agentic AI Newsletter: The AAIF's news and views, published on LinkedIn. A2A: The agent-to-agent protocol that grew out of Google and recently joined the AAIF https://a2a-protocol.org A2A joins AAIF: The foundation's announcement Model Context Protocol (MCP): One of the AAIF's founding projects https://modelcontextprotocol.io goose: The open source agent Manik oversaw at Block, now an AAIF project https://block.github.io/goose AGENTS.md: The AAIF's third founding project https://agents.md agentgateway: An open gateway for agentic AI traffic, including token spend tracking https://agentgateway.dev Agent Router: The related AAIF project Manik mentions alongside agentgateway https://theagentrouter.ai AGNTCY: The Cisco-backed agent stack whose ACP spec gave way to A2A https://agntcy.org Connect with Manik: LinkedIn | X Manik's Substack: Manik's writing on open source and AI. https://maniksurtani.substack.com 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.
S6 · E74
September 29 · 27 min
Why AI made code review the new bottleneck, and the metric that spotted it | Newsela's Dee Wilcox
You can't automate a planning process that only some of your teams follow. This week on Dev Interrupted, Newsela CTO Dee Wilcox joins Dan Lines, LinearB's COO and co-founder in our AI Enablement interview series. She shows how Newsela brought dev cycle time down from four days to closer to two, and why she treats code review time as a measure of how long engineers wait for feedback. They close the conversation on proving AI ROI to the board, where Dan makes the case for cost per effective PR, a metric that only counts the PRs that ship without causing incidents or needing rework. Save your seat: What your software factory is doing to your engineers 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: Learn more about Newsela: https://newsela.com Accelerate Everyone: Dee's Substack on engineering leadership https://accelerateeveryone.substack.com Connect with Dee: 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.
S6 · E73
September 22 · 55 min
Securing tomorrow’s git forge, so we can reimagine everything else | Entire's Thomas Dohmke & Apiiro's Idan Plotnik
Before anyone reimagines the software lifecycle for agents, someone has to secure the place all that code lands. Entire CEO Thomas Dohmke, formerly CEO of GitHub, and Apiiro co-founder and CEO Idan Plotnik see the same problem from opposite ends of the pipeline: agents now write, review, test and deploy the code, and nobody reads it. This week on Dev Interrupted, they join Andrew to argue that the fix is context, injected before the prompt through hooks and captured afterward as session logs committed next to the code. Idan puts numbers on the perfect storm of agents shipping more code as Mythos scans surface 10x the vulnerabilities, while Thomas makes the case that code is the what and the session log is the why. They close the conversation on why every pull request needs a business owner, not just a code owner. Save your seat: Sustaining engineering health through your AI transformation 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: Entire: https://entire.io/ Entire CLI (open source): https://github.com/entireio/cli Apiiro: https://apiiro.com/ Apiiro Guardian Agent: https://apiiro.com/blog/introducing-apiiro-guardian-agent/ JPMorgan's Patchmageddon report: https://privatebank.jpmorgan.com/nam/en/insights/latest-and-featured/eotm/patchmageddon Connect with Thomas: LinkedIn | Twitter/X Connect with Idan: 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.
S6 · E72
September 15 · 45 min
Treat your data pipelines like code, because your agents already do | MotherDuck's Jordan Tigani
Your data warehouse still thinks a human is on the other end of the query. That's a problem MotherDuck CEO and co-founder Jordan Tigani knows from the inside, having spent years as a founding engineer on Google BigQuery. This week on Dev Interrupted, he joins Andrew to make the case that one warehouse per agent beats the distributed systems he used to work on. He lays out Watertown, his riff on Steve Yegge's Gastown that recasts the data engineer as the manager of a fleet of agents, and walks through how MotherDuck's Flights, Dives, and just-launched Guides keep pipelines, visualizations, and business context as code reviewed in GitHub. Get the guide: Your software factory needs a context layer 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: MotherDuck: The DuckDB-powered data warehouse built for small data and agents at motherduck.com Water-Town: Read Jordan's take on the agent swarm data stack, his riff on Gastown, at motherduck.com/blog Flights: Learn how MotherDuck turns data ingest into scheduled Python scripts your agents can write at motherduck.com/blog Dives: See how MotherDuck replaced its BI tool with LLM-written TypeScript visualizations at motherduck.com/blog Guides: Read the docs on MotherDuck's new Markdown context layer for agents at motherduck.com/docs MotherDuck Blog: Keep up with all things MotherDuck at motherduck.com/blog MotherDuck Community: Join the community Slack at community.motherduck.com Connect with Jordan: 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.
S6 · E71
September 11 · 36 min
The factory gets darker, Meta migrates to Slack, and throwing 10,000 PhDs at math problems
This week on the Friday Deploy, Andrew is joined by Dev Interrupted's producer Adam Noble to size up OpenAI's declaration that the AGI era has arrived, the Navier-Stokes race that has the math world crying foul, and why Meta is ditching its own messaging stack for Slack. They also dissect the bizarre saga of OpenAI's sandboxed agents leaving whispered notes for their future selves, and the "super dark factory." Finally, they celebrate Kiro Pro going free for over a million college students and tease a terminal-first upcoming news segment. 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 stories: The Era of AGI A Bad Day For Humans, a Worse Day For Humanity Meta is switching to Slack because it says it's better for AI agents Agency and Agents The Superdark Factory Spec-Driven Development for Agentic Software Engineering: Harnessing Human-Agent Teamwork Inside Dev Interrupted’s agentic newsroom and what it reveals about the future of tech media Kiro Pro for students: kiro.dev/students 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.
S6 · E70
September 8 · 44 min
Your agents are starving! Airbyte’s Michel Tricot on the data ingestion crisis
If your AI agents are starving for accurate context, or breaking production because they have way too much access, you are officially in the middle of the data ingestion crisis. This week, Airbyte CEO and co-founder Michel Tricot unpacks the massive data access and context sprawl challenges that are crippling AI workflows in production. He and Andrew dive into the critical need for strict data permissions, automated entity resolution, and why the transition to agentic workflows perfectly mirrors the paradigm-shifting migration from bare-metal servers to the cloud. Finally, Michel explains why obsessing over short-term AI ROI is a massive mistake, revealing how Airbyte measures true success with their internal automation project, Hydra. Get the guide: Your software factory needs a context layer 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: Airbyte: Explore the open-source data integration platform powering AI context at airbyte.com Agent Blueprint: Read Michel Tricot's newsletter on building agentic data infrastructure on Substack Connect with Michel: 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.
S6 · E69
September 4 · 33 min
NVIDIA acquires Hugging Face, OpenClaw 2.0 goes multiplayer, and the Linux kernel fights back against AI scrapers
This week on the Friday Deploy, Ben and Andrew unpack Nvidia's massive acquisition of Hugging Face and what it means for the future of localized models. They also explore the multiplayer updates in OpenClaw 2.0, how relentless AI scraper bots are overwhelming kernel.org, and how engineering leaders can continuously balance safe infrastructure investments against volatile technology bets. Finally, they discuss why a strong engineering culture remains the ultimate productivity hack and how autonomous agents will only amplify existing organizational dysfunction. 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 stories: NVIDIA to Acquire Hugging Face Teaching Everyone to Fish for Tokens OpenClaw 2.0, Accidentally Creepy crawlies Reject Change, Sometimes Good Culture is the Biggest Productivity Hack, Not AI 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.
S6 · E68
September 1 · 58 min
Why software factories fail without humans | HumanLayer, Warp & LinearB
In this special episode, Andrew hosts HumanLayer CEO Dexter Horthy, Warp Head of Product Engineering Aloke Desai, and LinearB COO Dan Lines. They debate why human ownership of pull requests remains nonnegotiable and how to implement "night vision" observability across automated workflows. The panel also explores why incident management is the final frontier for AI and how to get your team excited about building the factory instead of fighting it. Get the guide: Your software factory needs a context layer 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: 1Password: Explore the enterprise password and identity platform at 1password.com 1Password for Developers: Dive into the new developer tooling, credential brokering, and secure AI workflows at 1password.dev Oracle Red Bull Racing: Read more about the F1 team's systems engineering at redbullracing.com Connect with Nancy: 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.
S6 · E67
August 28 · 36 min
Build fences not sandboxes, earn the currency of trust, and share the cognitive burden of agents across engineers
This week on the Friday Deploy, Ben and Andrew evaluate the strange arrival of Ox Alpha and debate the security risks of black-box AI tools. They also explore why engineering trust is more critical than ever, revisit the controversial lines of code metric in the age of AI generation, and explain why autonomous agents need structured fences rather than restrictive sandboxes. Finally, they break down the multi-agent graph architectures powering modern software factories and share actionable advice for reaching staff engineer status by driving cross-team AI adoption. 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 stories: Ox alpha Fundamentals of Trust in Engineering Conceptual integrity and counting lines of code Graph Engineering: The Complete Guide to Building Multi-Agent AI Systems Fences, not Sandboxes How to Grow From Senior to Staff Engineer in the AI Era 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.
S6 · E66
August 25 · 47 min
Can agents keep a secret? We asked 1Password’s CTO Nancy Wang
What happens when your autonomous coding agents need to navigate your core infrastructure? Do you hand them the keys and hope for the best? (gulp!) This week on Dev Interrupted, 1Password CTO Nancy Wang teaches the golden path for agentic security: just-in-time secrets that grants AI "access without custody." She also shares her CTO playbook for measuring true agentic ROI beyond raw PR volume, explains why 1Password has officially replaced traditional coding interviews with agent builder tests, and confesses she’s shipping PRs again with her own fleet of agents between meetings. Like many CTOs we’ve had on the show, Nancy reminds us that code is cheap now, and review is what’s expensive now. We get into tactics for addressing that bottleneck. 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: 1Password: Explore the enterprise password and identity platform at 1password.com 1Password for Developers: Dive into the new developer tooling, credential brokering, and secure AI workflows at 1password.dev Oracle Red Bull Racing: Read more about the F1 team's systems engineering at redbullracing.com Connect with Nancy: 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.
S6 · E65
August 21 · 24 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.
S6 · E64
August 18 · 44 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.
S6 · E63
August 14 · 34 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.
S6 · E62
August 11 · 47 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.
S6 · E61
August 7 · 38 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.
S6 · E60
August 4 · 48 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.
S6 · E59
July 31 · 26 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.
S6 · E58
July 28 · 44 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.

Showing 1–20 of 35 episodes