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Dev Interrupted

Dev Interrupted

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337 episodes · showing the newest 200

Balancing AI innovation with compliance and governance | Capital One’s Abhijit Bose

46 min

Capital One SVP Abhijit Bose, who leads the company’s enterprise AI and ML platforms, has spent more than 20 years in AI and ML, and his answer is to make governance the platform’s job instead of the developer’s. This week on Dev Interrupted, he joins Dan Lines for LinearB’s AI Enablement Series to walk through how every harness change at Capital One now runs through evals that measure token cost, latency and quality before it reaches users. Abhijit also breaks down MACAW, the bank’s multi-agent framework behind Chat Concierge. Save your seat: Deliver outcomes when human attention can't keep up Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's guest: Chat Concierge: Driving the future of car buying with agentic AI. The multiagent car-buying assistant that runs on Capital One’s GenAI platform.MACAW: Capital One at EMNLP 2025. Capital One’s introduction to MACAW, the multi-agent framework behind Chat Concierge.VulnHunter: Announcing VulnHunter. The open-source agentic code security tool Abhijit points to when talking about AI and cybersecurity.Connect with Abhijit: LinkedInOFFERS 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.OFFERS Start Free Trial: Get started with LinearB's AI productivity platform for free.Book a Demo: Learn...

Bet on research, not on vibes | Together AI’s Dan Fu

45 min

This week, Dev Interrupted takes a field trip all the way down to the GPU. Leading the way is Together AI’s VP of Kernels Dan Fu, a co-author of FlashAttention who also runs a research lab as an assistant professor at UC San Diego. He joins Andrew to talk about how ideas now move from the lab into production models within months, and what it means to build a cloud for AI. Dan argues that AI is an accelerant for individual engineers, and that the more domain expertise they bring, the faster it lets them go. They close the conversation on how DRIs and managers keep track of ownership and AI spend when your star players get even faster  Save your seat: Deliver outcomes when human attention can't keep up Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's guest: OpenWALDO: The open source AI project Greg launched, built on open weights, artifacts, licenses, data and originsOpenWALDO Slack: Join the community Greg invites listeners intoOpenWALDO on GitHub: The project’s code and toolingCIQ: Greg’s company, where he is founder and CEORocky Linux: The enterprise Linux distribution whose community Greg set upWhy Open Source Matters for AI: Tim O’Reilly’s piece on open weights, protocols and the architecture of participationConnect with Greg: LinkedInOFFERS 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 n...

Do the models you use have an AI bill of materials? | CIQ’s Gregory Kurtzer

44 min

Most companies control the prompts they send to a model, but not what went into it. That’s the gap CIQ founder and CEO Gregory Kurtzer, who set up the community that built Rocky Linux, wants an AI bill of materials to close. This week on Dev Interrupted, he joins Andrew to make the case for OpenWALDO, a community-backed corpus of AI training data built on open weights, artifacts, licenses, data and origins. Greg explains why open weights alone don’t make a model open source, and why a model trained on copyleft code raises a licensing question nobody has litigated. They close the conversation on why the community side of open source matters more than ever now that AI lets more people contribute. Save your seat: What your software factory is doing to your engineers Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's guest: OpenWALDO: The open source AI project Greg launched, built on open weights, artifacts, licenses, data and originsOpenWALDO Slack: Join the community Greg invites listeners intoOpenWALDO on GitHub: The project’s code and toolingCIQ: Greg’s company, where he is founder and CEORocky Linux: The enterprise Linux distribution whose community Greg set upWhy Open Source Matters for AI: Tim O’Reilly’s piece on open weights, protocols and the architecture of participationConnect with Greg: 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 devel...

Multiplayer AI will revolutionize the way we work | OpenClaw Foundation’s Vincent Koc

46 min

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 LinkedInSubscribe to our YouTube ChannelFollow the hosts: Follow AndrewFollow BenFollow DanFollow 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...

Building the software factory from the spec up | LinearB's Ariel Illouz & Ofer Affias

45 min

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 LinkedInSubscribe to our YouTube ChannelFollow the hosts: Follow AndrewFollow BenFollow DanFollow 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: LinkedInOFFERS 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...

A neutral home for MCP, A2A, goose, and more | AAIF co-founder Manik Surtani

48 min

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 LinkedInSubscribe to our YouTube ChannelFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's guest: Agentic AI Foundation (AAIF): The foundation's home for working groups, blogs, events and news https://aaif.ioThe 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.orgA2A joins AAIF: The foundation's announcementModel Context Protocol (MCP): One of the AAIF's founding projects https://modelcontextprotocol.iogoose: The open source agent Manik oversaw at Block, now an AAIF project https://block.github.io/gooseAGENTS.md: The AAIF's third founding project https://agents.mdagentgateway: An open gateway for agentic AI traffic, including token spend tracking https://agentgateway.devAgent Router: The related AAIF project Manik mentions alongside agentgateway https://theagentrouter.aiAGNTCY: The Cisco-backed agent stack whose ACP spec gave way to A2A https://agntcy.orgConnect with Manik: LinkedIn | XManik's Substack: Manik's writing on open source an...

Why AI made code review the new bottleneck, and the metric that spotted it | Newsela's Dee Wilcox

27 min

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 LinkedInSubscribe to our YouTube ChannelFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's guest: Learn more about Newsela: https://newsela.comAccelerate Everyone: Dee's Substack on engineering leadership https://accelerateeveryone.substack.comConnect with Dee: LinkedInOFFERS 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.

Securing tomorrow’s git forge, so we can reimagine everything else | Entire's Thomas Dohmke & Apiiro's Idan Plotnik

55 min

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 LinkedInSubscribe to our YouTube ChannelFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's guest: Entire: https://entire.io/Entire CLI (open source): https://github.com/entireio/cliApiiro: 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/patchmageddonConnect with Thomas: LinkedIn | Twitter/XConnect with Idan: LinkedInOFFERS 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 t...

Treat your data pipelines like code, because your agents already do | MotherDuck's Jordan Tigani

45 min

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 LinkedInSubscribe to our YouTube ChannelFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's guest: MotherDuck: The DuckDB-powered data warehouse built for small data and agents at motherduck.comWater-Town: Read Jordan's take on the agent swarm data stack, his riff on Gastown, at motherduck.com/blogFlights: Learn how MotherDuck turns data ingest into scheduled Python scripts your agents can write at motherduck.com/blogDives: See how MotherDuck replaced its BI tool with LLM-written TypeScript visualizations at motherduck.com/blogGuides: Read the docs on MotherDuck's new Markdown context layer for agents at motherduck.com/docsMotherDuck Blog: Keep up with all things MotherDuck at motherduck.com/blogMotherDuck Community: Join the community Slack at community.motherduck.comConnect 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...

The factory gets darker, Meta migrates to Slack, and throwing 10,000 PhDs at math problems

36 min

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 LinkedInSubscribe to our YouTube ChannelFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: The Era of AGIA Bad Day For Humans, a Worse Day For HumanityMeta is switching to Slack because it says it's better for AI agentsAgency and AgentsThe Superdark FactorySpec-Driven Development for Agentic Software Engineering: Harnessing Human-Agent TeamworkInside Dev Interrupted’s agentic newsroom and what it reveals about the future of tech mediaKiro 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.

Your agents are starving! Airbyte’s Michel Tricot on the data ingestion crisis

44 min

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 LinkedInSubscribe to our YouTube ChannelFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's guest: Airbyte: Explore the open-source data integration platform powering AI context at airbyte.comAgent Blueprint: Read Michel Tricot's newsletter on building agentic data infrastructure on SubstackConnect 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.

NVIDIA acquires Hugging Face, OpenClaw 2.0 goes multiplayer, and the Linux kernel fights back against AI scrapers

33 min

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 LinkedInSubscribe to our YouTube ChannelFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: NVIDIA to Acquire Hugging FaceTeaching Everyone to Fish for TokensOpenClaw 2.0, AccidentallyCreepy crawliesReject Change, SometimesGood Culture is the Biggest Productivity Hack, Not AIOFFERS 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.

Why software factories fail without humans | HumanLayer, Warp & LinearB

58 min

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 LinkedInSubscribe to our YouTube ChannelFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's guest: 1Password: Explore the enterprise password and identity platform at 1password.com1Password for Developers: Dive into the new developer tooling, credential brokering, and secure AI workflows at 1password.devOracle Red Bull Racing: Read more about the F1 team's systems engineering at redbullracing.comConnect 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.

Build fences not sandboxes, earn the currency of trust, and share the cognitive burden of agents across engineers

36 min

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 LinkedInSubscribe to our YouTube ChannelFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: Ox alphaFundamentals of Trust in EngineeringConceptual integrity and counting lines of codeGraph Engineering: The Complete Guide to Building Multi-Agent AI SystemsFences, not SandboxesHow to Grow From Senior to Staff Engineer in the AI EraOFFERS 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.

Can agents keep a secret? We asked 1Password’s CTO Nancy Wang

47 min

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 LinkedInSubscribe to our YouTube ChannelFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's guest: 1Password: Explore the enterprise password and identity platform at 1password.com1Password for Developers: Dive into the new developer tooling, credential brokering, and secure AI workflows at 1password.devOracle Red Bull Racing: Read more about the F1 team's systems engineering at redbullracing.comConnect 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...

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

24 min

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 LinkedInSubscribe to our YouTube ChannelFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: Incident Report for GitHubCursor launches Origin code hosting platform as GitHub outage exposes opening in AI coding raceAsk HN: Alternatives to GitHubEveryone building a software factory wants the same proofIntroducing Warp FactoriesLanding the planeOFFERS 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.

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

44 min

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 LinkedInSubscribe to our YouTube ChannelFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's guest: Strands Agents SDK: Explore the open-source framework for building model-driven agents at strandsagents.comMCP 7.28): Dive into the new stateless specification at modelcontextprotocol.ioFollow 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 langu...

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

34 min

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 LinkedInSubscribe to our YouTube ChannelFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: After starting the tokenmaxxing panic, Uber's CTO is back with a very different AI storyAuto mode is now the default in Claude Code for Pro, Max, and Team plansIntroducing Muse Glimmer: An Open Agentic Model That Runs on Your DeviceWhy Open Source Matters for AIYour SDLC is your context engineeringDo personalized skills help coding agents? An empirical study of developer interaction historiesOFFERS 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.

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

47 min

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 LinkedInSubscribe to our YouTube ChannelFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's guest: The AI Productivity Gap Report: Read the full report and explore the 2026 data from 2.7 million PRsLinearB: Learn how to measure AI leverage and optimize your engineering workflows at linearb.ioConnect with Yishai: LinkedInOFFERS 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.

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

38 min

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 LinkedInSubscribe to our YouTube ChannelFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: Microsoft Tells Engineers ‘Tokenmaxxing Is Not What We Are Optimizing For’The Shape of Things to ComeThe Shape of Things to Come - Part 2: Model Welfare for Agentic EngineersHow AI helped Socrates to help me actually understand myselfThe Month AI Conquered Math: The Full StoryHow to Build an Effective Agent HarnessMaking AI Visible, Not Vanished: How AI Policies Reshape Developer Experience on GitHubOFFERS 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.

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

48 min

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 LinkedInSubscribe to our YouTube ChannelFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's guest: Asana: Explore the work management platform and learn more about Agentic Work Management at asana.comStack AI: Read about Asana's acquisition of the no-code AI workflow automation platform on the Asana BlogConnect with Arnab: LinkedInOFFERS 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.

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

26 min

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 LinkedInSubscribe to our YouTube ChannelFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: Why Software Factories FailA guide to cloud software factories for engineering leadersYou just hired a million bad employees.An AI that only sees the latest version will never protect your original ideaThe Orchestrator's TaxOFFERS 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.

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

44 min

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 LinkedInSubscribe to our YouTube ChannelFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's guest: CircleCI: Explore the leading continuous integration and delivery platform at circleci.comThe Confident Commit: Subscribe to Rob's newsletter and podcast for data-backed software delivery insights on CircleCI's websiteThe Confident Commit Podcast: Listen to Rob’s podcastState of Software Delivery: Read CircleCI's annual report analyzing millions of CI workflows to benchmark your team's performanceGather.dev: Apply to join the curated, invite-only community for senior engineering leaders at gather.devFollow 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 recommendatio...

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

29 min

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 LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: Are AI labs pelicanmaxxing?OpenAI and Hugging Face partner to address security incident during model evaluationChina'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 limitsWho’s Afraid of Chinese Models?SWE-Review: Closing the Loop on Issue Resolution with Agentic Code ReviewThe Army Is Burning Through Its AI TokensOFFERS 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.

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

35 min

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 LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's guest: Rippling: Explore the workforce management platform at rippling.com Introducing Rippling Data Cloud: AI-powered BI that understands your workforceFollow 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.

Rebuilding CLIs for agents, it’s time to get MCP-certified, and why human code review will never catch up

23 min

This week on the Friday Deploy, Ben and Andrew explore Codex's obsession with the isRecord type guard and break down the Linux Foundation's new MCP certification. They also discuss the fundamental mechanics of agentic loops and CircleCI's new agent-first CLI redesign. Finally, they dive into longitudinal research proving that AI creates a massive pull request bottleneck, highlighting why automated code review is the only sustainable path forward. Register: The Engineering Productivity Gap live workshop on July 30 Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: I'm pretty sure isRecord is our faultIntroducing the MCPA: the First Official Certification for the Model Context ProtocolIf you give a Goose an MCP serverWhat the hell is a loop, anyway?Rebuilding the CircleCI CLI from scratchAI Writes Faster Than Humans Can Review: A Longitudinal Study of an Enterprise 2x MandateOFFERS 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.

How to see in the dark factory | LaunchDarkly's Cameron Etezadi

47 min

The era of the "two-pizza" engineering team is officially dead, replaced by the "two-slice" team and a massive token budget. This week, LaunchDarkly CTO Cameron Etezadi joins the show to explain why traditional guardrails are breaking down and how engineering teams can regain control using runtime agent frameworks. He introduces the concept of the "dark factory," a highly automated assembly line for safely observing, flagging, and deploying AI-generated code to production.  The conversation turns to the new ROI of software development, why engineers must now act as frontline managers, and how to navigate the build-versus-buy dilemma in the modern token economy. As AI speeds up how code gets written, the real bottleneck moves downstream to review, testing, and release, where software either delivers measurable value or quietly stalls. Check out the latest research from LinearB on how to measure that value. Life Beyond Tokenmaxxing Workshop: Watch the full replay on demand at linearb.io  Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's guest: LaunchDarkly AgentControl: Learn how to govern your probabilistic AI with runtime agent frameworks at launchdarkly.com/platform/agent-control The Goal by Eliyahu M. Goldratt: Read the quintessential business novel on the theory of constraints at Amazon The Phoenix Project by Gene Kim: Explore the seminal book on IT, DevOps, and business success at IT Revolution SimAnt: Dive into the history of the 1991 classic electronic ant colony simulation at Wikipedia. Follow Cameron: 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 & Pro...

How to cultivate expertise with local models, delegating to subagents, and we all really stopped reading, huh?

28 min

Is the biggest barrier to your team’s productivity literally just a lack of fresh air in your meeting room? This week on the Friday Deploy, Ben and Andrew dive into the rise of highly capable open source models like GLM 5.2 and the messy reality of running local AI for coding tasks. The hosts also discuss the cultural shift away from deep reading in a world obsessed with AI summaries, emphasizing the importance of protecting your first brain. Finally, they review a legendary tale from Meta's engineering history. Life Beyond Tokenmaxxing Workshop: Watch the full replay on demand at linearb.io  Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: The bottleneck might be the air in the roomGLM-5.2 is the step change for open agentsViability of local models for codingAI Erodes a Legacy of ReadingI Shipped a Facebook Feature So Fast Sheryl Sandberg Called an Emergency Meeting to Stop MeOFFERS 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.

Agents moved where the work happens (and using MCP to find it again) | Slack’s Jaime DeLanghe

51 min

This week on Dev Interrupted, Slack’s Chief Product Officer, Jaime DeLanghe, joins the show to explain why enterprise AI value depends on embedding custom bots directly into your existing team communication loops rather than deploying them inside isolated, single-player chat silos. She breaks down the platform's shift toward open ecosystem standards like the Model Context Protocol (MCP) and how dynamic UI frameworks are transforming standard channels into active execution environments. Jaime details the operational realities of managing autonomous software fleets, including a striking look at how leading companies are placing hundreds of custom agents directly onto their corporate org charts. Life Beyond Tokenmaxxing Workshop: Watch the full replay on demand at linearb.io  Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's guest: Slackbot MCP Client: Learn more about connecting your tools to Slackbot via the Model Context Protocol at the Slack BlogSlack Developer Hub: Start building your own agentic workflows and explore the latest tools at slack.devConnect with Jaime: LinkedInOFFERS 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.

Empathetic leadership for tech overlords, a good backlog completes itself, and who’s agent is this, anyways?

36 min

This week on the Friday Deploy, Andrew Zigler is joined by Zapier’s Kelly Vaughn to dive into the sudden return of Anthropic's Fable model, the realities of multi-threaded agentic engineering, and why the lowly engineering backlog is finally having its moment. To wrap things up, they review Charity Majors' latest advice on empathetic leadership and explore why the best way to win a workplace disagreement is to stop arguing and let an AI build the proof of concept. Life Beyond Tokenmaxxing Workshop: Watch the full replay on demand at linearb.io  Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's guest: Follow Kelly on LinkedInFollow Kelly on SubstackCheck out Kelly's website kvlly.comFollow today's stories: Redeploying Fable 5It’s Time To Put Humans Back In The SoftwareThree Ways to Give an AI Agent an IdentityBenchmarking AI Agents for Real Data ScienceWhy I Stopped Arguing With PeoplePaging Charity! How can engineering leaders avoid becoming Bond villains?The backlog is finally getting its momentOFFERS 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.

How LinearB helps Kraken find hidden bottlenecks across thousands of engineers | Nik Sudan

43 min

Are you confusing a skyrocketing AI token bill with actual engineering value? This week on Dev Interrupted, Kraken's Engineering Operations Lead, Nik Sudan, joins the show to break down the harsh realities of moving agentic AI projects from pilot to production without compromising code health. He unpacks why raw AI adoption is a flawed vanity metric, detailing how his team uses tools like the LinearB MCP server to combine high-level engineering metrics with granular repository data to uncover hidden workflow bottlenecks. Finally, Nik reveals his exact playbook for translating complex data, like P90 cycle times, into a clear, business-driven narrative that secures vital buy-in from non-technical stakeholders.  Life Beyond Tokenmaxxing Workshop: Watch the full replay on demand at linearb.io  Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's guest: LinearB MCP Server: Learn how to chat with your engineering data and uncover hidden bottlenecks at linearb.io/platform/mcp-serverThe APEX Framework: Read LinearB's guide on the operating model for AI-era engineering teams at linearb.io/resources/apex-frameworkKraken: Learn more at www.kraken.comWebsite / Follow Nik:niks.space 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 o...

The discernment horizon, loop-driven development, and a wizard’s very defensible pond

28 min

Is the golden age of exponential AI growth already flattening out? This week on the Friday Deploy, Ben and Andrew unpack Steve Yegge's "Flat Curve Society" theory to explore what happens when frontier models stop getting exponentially better. The hosts also dive into the evolution of loop-driven development, the value of markdown based local knowledge bases, and why comparing different AI models usually just exposes the flaws in your own prompts. Finally, they review Midjourney's bizarre new echolocation spa concept and explore the true limits of AI disruption through the hilarious allegory of "The Wizard with the Very Defensible Pond."  Life Beyond Tokenmaxxing Workshop: Watch the full replay on demand at linearb.io  Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: A New Era of MidjourneyThe Flat Curve SocietyFrom Test-Driven to Loop-Driven DevelopmentA failed universal language explains why you keep picking the wrong AI outputBuilding a Local Knowledge Base in Google's Open Knowledge Format (OKF)The Wizard With the Very Defensible PondOFFERS 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.

Your developers are the attack surface now and vibe coding as a vulnerability | Tanya Janca

46 min

Developers are like water: if you make your security protocols too difficult, they will find a way to flow right around them. This week on Dev Interrupted, bestselling author and OWASP Top 10 Project Leader Tanya Janca returns to unpack why vibe coding has officially made the list of the most critical security risks in software development. Tanya breaks down the psychology of bad code, explains why the modern software engineer has become the primary attack surface, and shares actionable strategies for shifting security left directly into your AI prompts. Finally, she provides practical, behavioral solutions for building a golden path that makes secure coding the easy choice for your engineering team.  Register here: for the June 25th workshop, Life Beyond Tokenmaxxing, to learn how to measure real AI impact and ROI across the SDLC. Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's guest: SheHacksPurple: Learn secure coding from Tanya at shehackspurple.caDevSec Station: Listen to Tanya's bite-sized security podcast for developers at devsecstation.comSecure My Vibe: Download Tanya's free AI secure coding prompt library at securemyvibe.ca The Psychology of Bad Code: Read Tanya's insightful blog series on behavioral economics and application security on the SheHacksPurple BlogOWASP Top 10: Learn more about the most critical security risks to web applications at owasp.orgTanya’s Newsletter: Sign up for Tanya’s newsletter at  newsletter.shehackspurple.ca  Connect with Tanya: LinkedIn | Twitter/XOFFERS 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...

Microsoft’s wandering eyes, data labeling duties for senior devs at Meta, and prod is the new source code

38 min

This week on the Friday Deploy, Ben and Andrew unpack the sudden disappearance of Fable 5 and discuss whether Meta's aggressive pivot to AI data labeling is destroying its legendary engineering culture. The hosts also explore the rise of highly capable open source Chinese models like GLM 5.2 and why tech giants are considering them to slash skyrocketing inference bills. Finally, they dive into new research proving that as AI execution takes over, human domain expertise and strict production observability are more critical than ever.  Register here: for the June 25th workshop, Life Beyond Tokenmaxxing, to learn how to measure real AI impact and ROI across the SDLC. Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: KayfableWhy is Meta destroying its engineering organization?AI demands more engineering discipline. Not lessZ.ai’s open-weights GLM-5.2 beats GPT-5.5 on multiple long-horizon coding benchmarks for 1/6th the costMicrosoft Mulls China’s DeepSeek for Copilot, Probably to Trump’s ChagrinAgentic coding and persistent returns to expertiseOFFERS 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.

Your SDLC needs a productivity context engine

39 min

What if the secret to fixing your overwhelmed SDLC is not a better AI coding model, but a smarter productivity context engine? This week on Dev Interrupted, LinearB founders Ori Keren and Dan Lines join the show to discuss the messy middle of AI adoption and the painful transition from the traditional SDLC to the Agentic Development Life Cycle. They unpack why the era of cheap AI experimentation is over, how rising token costs are forcing engineering leaders to prioritize strict business ROI, and how autonomous tools are fundamentally changing the daily workflow of developers. Register here: for the June 25th workshop, Life Beyond Tokenmaxxing, to learn how to measure real AI impact and ROI across the SDLC. Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's guest: LinearB: Learn how to transform your SDLC and build an engineering context engine at linearb.iogitStream: Explore LinearB's workflow automation tool for routing pull requests at linearb.io/platform/gitstreamFollow Ori and Dan on LinkedIn: Ori Keren | Dan LinesOFFERS 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.

How to harness your dragon with Fable, tech leaders turn to model routing, and coping with AI rockstars

35 min

Anthropic just dropped a dragon-class model on our laps, but can you steer it without torching your codebase in the process? This week on the Friday Deploy, Ben and Andrew unpack the sudden arrival of Fable 5 and how to leverage it to scrutinize your systems before the massive API paywall hits. They also take aim at the unsustainable trend of tokenmaxxing and explore how intelligent model routing can drastically cut your AI spend. Finally, they tackle the unmaintainable mess left behind by AI rockstar developers and share how they are orchestrating their own agent-to-agent collaboration. Register here: for the June 25th workshop, Life Beyond Tokenmaxxing, to learn how to measure real AI impact and ROI across the SDLC. Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: Bots Have Officially Taken Over the Internet, Humans Are The MinorityClaude Fable 5 and Claude Mythos 5What it feels like to work with MythosSam Altman says OpenAI's top token spender uses 100 billion tokens a month — and they're not even the world leaderHow I Cut Our AI Spend in Half | "Tokenmaxxing" is DeadCleaning up after AI rockstar developersOFFERS 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.

All software is an optimization of tokens and time (and speed is still the moat) | AMD’s Anush Elangovan

52 min

What happens when you strip away decades of engineering abstractions and let AI navigate the wild west between your initial intent and the final outcome? This week on Dev Interrupted, Anush Elangovan, VP of AI Software at AMD, returns to unpack the rapid shift toward an agentic software development lifecycle. Anush introduces the concept of "Agentic IO," a workflow where engineers focus strictly on high-level goals while AI handles the complex implementation. The conversation also highlights the expanding productivity wingspan of modern developers, the power of local open source models, and why speed remains the ultimate competitive moat.  Learn why: LinearB is a Leader in the 2026 Gartner® Magic Quadrant™ for Developer Productivity Insight Platforms Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's guest: AMD ROCm: Learn more about AMD's open-source software stack for AI at rocm.docs.amd.com and on GitHub.AMD Advancing AI 2026: Register for AMD's flagship global AI event taking place July 22-23 in San Francisco at amd.com/advancing-ai.Follow Anush on LinkedIn: Anush Elangovan | AMD blogOFFERS 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.

Microsoft breaks free from OpenAI, using your harness to add drag instead of velocity, and the Linux built-ins you're sleeping on

27 min

This week on the Friday Deploy, Ben and Andrew unpack the AI build-versus-buy debate, Microsoft's new independent foundation models, and the growing revolt of mathematicians against unsubstantiated AI-generated proofs. The hosts also explore Stanford’s Socratic rulebook for AI coding assistants and discuss Kent Beck's warning that engineering teams need to build "trust factories" to counter the rapid chaos of AI-assisted development. Finally, they close with a defense of Linux primitives and why you should probably be using a systemd timer instead of the latest shiny AI tool.  Learn why: LinearB is a Leader in the 2026 Gartner® Magic Quadrant™ for Developer Productivity Insight Platforms Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: The AI SaaSpocalypse is a mirageMathematicians warn of AI threats to profession as industry encroachesIntroducing MAI-Code-1-FlashAI Agent Guidelines for CS336 at StanfordTrust FactoryYou Don't Love systemd Timers EnoughOFFERS 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.

How to turn your 1000x engineer into a 10x everyone | LinkedIn’s Karthik Ramgopal

52 min

This week, Andrew sits down with LinkedIn Distinguished Engineer Karthik Ramgopal to explore the reality of deploying agentic platforms across a massive organization. Karthik unpacks the mechanics of AI memory, spanning procedural and episodic structures, and explains how to build durable engineering primitives that actually last. Finally, the two discuss the enduring importance of system fundamentals and why LinkedIn is restructuring its internship program into AI-native pods to foster a new culture of two-way mentorship.  Learn why: LinearB is a Leader in the 2026 Gartner® Magic Quadrant™ for Developer Productivity Insight Platforms Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's guest: Follow Karthik on LinkedIn: Karthik Ramgopal 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.

The cost of intelligence will never be this cheap again, the failure of intensive specs, and how bots disguise inefficient workflows

38 min

Are we officially entering the "Eternal Sloptember"? This week on the Friday Deploy, Ben and Andrew unpack the quiet rebellion against skyrocketing API costs as teams transition to fine-tuned local models. They also explore the changing physical architecture of AI data centers, the dangers of using autonomous tools as a crutch for broken workflows, and why spec-driven development is critical for keeping agentic code in check. Finally, the hosts share their latest personal agent experiments, from benchmarking open-source models on a local Mac Studio to taming an AI-generated second brain. Learn why: LinearB is a Leader in the 2026 Gartner® Magic Quadrant™ for Developer Productivity Insight Platforms Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: Outsourcing plus LocalAI will soon become more economical vs Frontier labsAI Datacenters Were Built for GPUs. What Happens When You Remove the GPUs?"The AI Can Do It" Is Not an Excuse To Tolerate a MessThe Eternal SloptemberI’m tired of talking to AIIf you let AI do your writing, I will come to your house and kill youA Blast from the Past: SDD and the Illusion of Known ScopeAndrew’s paper: Mise en Place for Agentic Coding: Deliberate Preparation as Context Engineering MethodologyOFFERS 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...

Observability is your profit center now | Honeycomb’s Christine Yen

47 min

What if you stopped treating observability as a simple insurance policy and started viewing it as a profit center? This week, Andrew sits down with Honeycomb CEO Christine Yen to explore how observability, data science, and product development are colliding in the agentic era. Christine explains why production signals must become compiler inputs for autonomous agents and how MCP tools are democratizing telemetry for entire organizations. Finally, the two discuss Honeycomb's latest Innovation Week announcements and the exact strategy for reframing observability from basic risk mitigation into a clear revenue accelerant. Learn why: LinearB is a Leader in the 2026 Gartner® Magic Quadrant™ for Developer Productivity Insight Platforms Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: Honeycomb Blog: Read deep dives on SLOs at honeycomb.io/blogHoneycomb Innovation Week: Explore the latest announcementsRequired Reading: Check out the book Observability Engineering by Charity Majors, Liz Fong-Jones, and George Miranda.HumanX Interview: A Codebase Is No Longer the Source of Truth"Production is a Compiler Input": Chad Fowler's take on the future of code generation. Follow Christine on LinkedInOFFERS 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...

What Google didn’t announce at I/O, defining “dark flow” and ignoring your first brain to build your second one

30 min

Andrew and Ben recap the biggest announcements from Google I/O, breaking down everything from the new Gemini Spark agent to Gemini 3.5 Flash. They also explore how leaders can distill their management style using AI, debate whether complex note-taking apps are a form of procrastination, and call on listeners to participate in a new vibe coding research study. Finally, Andrew shares his "Skills Olympics" methodology for stress-testing and managing his own personal fleet of AI agents.  Learn why: LinearB is a Leader in the 2026 Gartner® Magic Quadrant™ for Developer Productivity Insight Platforms Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: PollyReach: Give your agent a real number and voice to make calls.Google is launching its own version of OpenClawGoogle touts its tokenmaxxing and capex spending amid AI orgyVibe Coding Experience SurveyDistilling yourselfOpen-source alternative to ObsidianOFFERS 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.

Android is the frontier for agents and other lessons from Google I/O | Matthew McCullough

27 min

With Google I/O 2026 underway this week, Andrew sits down with Matthew McCullough, VP of Android Development Experiences at Google, to talk about the AI evolution happening across the Android ecosystem. Matthew shares his insights on why developers are rapidly transitioning into agent orchestrators, why CLIs are cool again, and how tools like AI Studio have rolled out a massive welcome banner for anyone to actively participate in the creation process. Finally, the two explore the future of mobile user interfaces and how the latest Android 17 developments are stripping away legacy friction to seamlessly get users straight to the good part. 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.

Agents get their own AOL, Andrew gets published, and vibe coding is actually good?

40 min

Is vibe coding actually good now? This week on The Friday Deploy, Andrew and Ben explore the convergence of vibe coding and agentic engineering, unpack the decline of the traditional technical interview, and discuss why companies like Warp are prioritizing AI prototypes over planning meetings. They also celebrate Andrew's newly published research on "mise en place" context engineering. Finally, they break down the enterprise AI "last mile" crisis and share how they are using personal knowledge graphs to upskill their own agents. Read the guide: The APEX Framework Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: AOL for agentsVibe coding and agentic engineering are getting closer than I’d likeMise en Place for Agentic Coding: Deliberate Preparation as Context Engineering MethodologyBuild, then alignThink the technical interview is dead? Think againThe last mile is where enterprise AI actually diesOFFERS 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.

It’s Tuesday and your tech stack is obsolete (again). Now what? | Theory Venture’s Bryan Bischof

55 min

Does it feel like your favorite AI tool is declared dead one week, only to be resurrected the next? This week, Andrew sits down with Bryan Bischof, Head of AI at Theory Ventures, to explore the hidden levers of inference systems and the industry's obsession with prematurely writing off useful tools. Bryan shares his experiences with why prompt optimization is mostly a dead end, the secret to building high-performing data agents, and how his team builds operational software for VCs. The two also break down the origins of the satirical rip-grep.com and drop hints about Bryan's highly anticipated next AI game show experiment.  AI Council 2026: Catch Bryan's track on inference systems and get tickets. Read the guide: The APEX Framework Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: Events: Catch Bryan's track live at the AI Council Conference.Writing: Check out the April Fools manifesto at rip-grep.comTheory Ventures: Learn more about the work happening at Theory Ventures.X/Twitter: @BEBischofLinkedIn: Bryan BischofOFFERS 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.

Goblins in prod, the messy middle of AI adoption, and everything is a harness now

31 min

Are you stuck in the "messy middle" of AI adoption where individual productivity doesn't actually translate to organizational impact? This week on the Friday Deploy, Andrew and Ben break down the hilarious and terrifying realities of agentic intention drift, exploring how a "goblin" invasion in ChatGPT and poorly scoped tokens are wreaking havoc on production environments. They also navigate this messy organizational adoption phase, discussing why senior developers are accelerating while juniors stall out on the K-shaped productivity curve. Finally, the hosts wrap up with a look at the open-source renaissance of agentic harnesses like Lattice and Pi.dev. Read the guide: The APEX Framework Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: Where the goblins came fromAI didn't delete your database, you didWhen everyone has AI and the company still learns nothingFragments: May 5Specsmaxxingclaude code is not making your product betterOFFERS 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.

Teach the primitives or watch your competitor define them | Baseten’s Philip Kiely

35 min

If you aren't the one educating your users on the fundamentals of AI, your competitors will happily do it for you. This week on Dev Interrupted, Andrew sits down with Philip Kiely, Head of AI Education at Baseten and author of Inference Engineering, to discuss why the secret to winning the AI market is owning the educational narrative through active market development. They explore the rise of the "Double-T" shaped engineer, the hidden complexities of scaling the inference stack, and why the most successful AI companies treat developer education as a mission-critical go-to-market motion. Read the guide: The APEX Framework Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: Baseten: Explore the inference platform where Philip serves as Head of AI Education. Inference Engineering: Download the free PDF or order a paper copy of Philip's comprehensive guide to the AI infrastructure stack. LinkedIn: Philip Kiely X/Twitter: @philipkiely Website: philipkiely.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.

Tokenmaxxing scoreboards, the vegan LLM from before 1931, and 30% of the web is now AI-generated

38 min

Are you at the top of your company's tokenmaxxing leaderboard yet? This week on the Friday Deploy, Andrew and Ben explore the controversial trend of "tokenmaxxing" sweeping through tech giants like Meta and Disney, as well as GitHub Copilot's shift to usage-based pricing that signals the end of the cheap AI era. The hosts also break down a terrifying incident where a rogue AI agent wiped out a production database and examine a new "vegan" language model trained exclusively on pre-1931 historical data. Finally, they react to a study revealing that 35% of all new websites are now AI-generated and close out the show with the drunk musings of a senior engineer.  Read the guide: The APEX Framework Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: An AI Agent Just Destroyed Our Production Data. It Confessed in Writing.Tokenmaxxing Is The Dumbest Metric In Tech Right NowIntroducing talkie: a 13B vintage language model from 1930Study Finds A Third of New Websites are AI-GeneratedFlipbook is an infinite visual browser generated entirely on demand in real time.Drunk Post: Things I’ve Learned as a Senior EngineerOFFERS 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.

Giving robots a brain | Intrinsic’s Brian Gerkey

51 min

What if deploying a new capability to an industrial robot arm was as seamless as pushing an update to a web app? This week, Andrew sits down with Brian Gerkey, CTO of Intrinsic and a titan of the open-source robotics community, to discuss how modern AI is finally giving robotics the "brains" to handle the unpredictable physical world. Brian breaks down how to move away from rigid, monolithic automation toward software-defined, modular robotics using tools like ROS (Robot Operating System) and digital twins. Finally, Brian invites developers of all backgrounds to test their skills in Intrinsic's new AI for Industry Challenge by using AI to solve one of the hardest problems in manufacturing: plugging in a tangled cable.  Read the guide: The APEX Framework Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: Brian’s Website: Learn more about Brian's work, research, and history in the open-source robotics community. Intrinsic: Explore the robotics software company led by Brian, which provides tools like Flowstate to build and deploy intelligent robotic solutions.AI for Industry Challenge: Get the toolkit and register to compete in Intrinsic's new challenge to solve complex dexterous manipulation and cable routing.ROS (Robot Operating System): The open-source middleware suite that has become the global standard for robotics software development.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 descri...

The harness is the showdown, the humans are the tool calls, and have you seen my Claude Code buddy?

37 min

Is the era of cheap, unlimited AI tokens officially over? This week on the Friday Deploy, Andrew and Ben walk through the sudden wave of AI pricing chaos—from GitHub Copilot’s panic-paused signups to Anthropic's confusing pricing tests—and break down the terrifying Vercel security breach caused by a single over-permissioned AI tool. They also examine 12 game-changing architecture patterns exposed in the Claude Code leak to help you safely orchestrate your own agentic workflows. Finally, they discuss how to avoid the lethal trifecta of agentic security risks before mourning the tragic deletion of their Claude Code buddies. Read the guide: The APEX Framework Follow the show: Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts: Follow AndrewFollow BenFollow DanFollow today's stories: Changes to GitHub Copilot Individual plansIs Claude Code going to cost $100/month? Probably not—it’s all very confusingAnthropic, OpenAI, Google, and Microsoft agree that the harness is the product. They disagree on the price.12 Agentic Harness Patterns from Claude CodeVercel April 2026 security incidentFragments: April 21Claude Managed Agents: get to production 10x fasterOFFERS 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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