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

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• OpenWALDO: The open source AI project Greg launched, built on open weights, artifacts, licenses, data and origins
• OpenWALDO Slack: Join the community Greg invites listeners into
• OpenWALDO on GitHub: The project’s code and tooling
• CIQ: Greg’s company, where he is founder and CEO
• Rocky Linux: The enterprise Linux distribution whose community Greg set up
• Why Open Source Matters for AI: Tim O’Reilly’s piece on open weights, protocols and the architecture of participation
• Connect with Greg: LinkedIn

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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

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• OpenWALDO: The open source AI project Greg launched, built on open weights, artifacts, licenses, data and origins
• OpenWALDO Slack: Join the community Greg invites listeners into
• OpenWALDO on GitHub: The project’s code and tooling
• CIQ: Greg’s company, where he is founder and CEO
• Rocky Linux: The enterprise Linux distribution whose community Greg set up
• Why Open Source Matters for AI: Tim O’Reilly’s piece on open weights, protocols and the architecture of participation
• Connect with Greg: LinkedIn

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• MCP Server: Interact with your engineering data using natural language to build custom reports and get answers on the fly.

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

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• OpenClaw Foundation: openclaw.org The foundation behind OpenClaw, which Vincent serves as chief architect.
• OpenClaw: openclaw.ai The open source personal AI assistant at the center of the conversation.
• OpenClaw 2.0, Accidentally: openclaw.ai/blog/openclaw-2-accidentally The release post for OpenClaw 2.0 and its multiplayer features.
• OpenClaw on GitHub: github.com/openclaw The org’s open source repos, all under MIT.
• OpenClaw security: openclaw.ai/security The project’s security page, which Vincent points to for the full record of reported vulnerabilities.
• Git Crawl: github.com/openclaw/gitcrawl The team’s GitHub issue and pull request crawler that keeps their agents aware of work across the repo.
• Crabbox: github.com/openclaw/crabbox The testing infrastructure the team built when nothing out there fit.
• Tideglass: github.com/vincentkoc/tideglass Vincent’s side project for inferring intent and preference profiles for agents.
• Beads: github.com/steveyegge/beads Steve Yegge’s git-backed issue tracker for coding agents.
• Wikinomics: dontapscott.com/books/wikinomics The book on mass collaboration that Vincent keeps coming back to.
• Connect with Vincent: LinkedIn | X

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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

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• LinearB Metrics Builder: The custom metrics builder Ariel's team built spec-first, a project he puts at six months without AI. 
• LinearB AI benchmarks: The AI engineering productivity gap: how elite teams pull ahead in 2026. 
• Connect with Ariel: LinkedIn 
• Connect with Ofer: LinkedIn

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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

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• Agentic AI Foundation (AAIF): The foundation's home for working groups, blogs, events and news https://aaif.io
• The Daily Agentic AI Newsletter: The AAIF's news and views, published on LinkedIn.
• A2A: The agent-to-agent protocol that grew out of Google and recently joined the AAIF https://a2a-protocol.org
• A2A joins AAIF: The foundation's announcement
• Model Context Protocol (MCP): One of the AAIF's founding projects https://modelcontextprotocol.io
• goose: The open source agent Manik oversaw at Block, now an AAIF project https://block.github.io/goose
• AGENTS.md: The AAIF's third founding project https://agents.md
• agentgateway: An open gateway for agentic AI traffic, including token spend tracking https://agentgateway.dev
• Agent Router: The related AAIF project Manik mentions alongside agentgateway https://theagentrouter.ai
• AGNTCY: The Cisco-backed agent stack whose ACP spec gave way to A2A https://agntcy.org
• Connect with Manik: LinkedIn | X
• Manik's Substack: Manik's writing on open source and AI. https://maniksurtani.substack.com

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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

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• Learn more about Newsela: https://newsela.com
• Accelerate Everyone: Dee's Substack on engineering leadership https://accelerateeveryone.substack.com
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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

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• Entire: https://entire.io/
• Entire CLI (open source): https://github.com/entireio/cli
• Apiiro: https://apiiro.com/
• Apiiro Guardian Agent: https://apiiro.com/blog/introducing-apiiro-guardian-agent/
• JPMorgan's Patchmageddon report: https://privatebank.jpmorgan.com/nam/en/insights/latest-and-featured/eotm/patchmageddon
• Connect with Thomas: LinkedIn | Twitter/X
• Connect with Idan: LinkedIn

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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

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• MotherDuck: The DuckDB-powered data warehouse built for small data and agents at motherduck.com
• Water-Town: Read Jordan's take on the agent swarm data stack, his riff on Gastown, at motherduck.com/blog
• Flights: Learn how MotherDuck turns data ingest into scheduled Python scripts your agents can write at motherduck.com/blog
• Dives: See how MotherDuck replaced its BI tool with LLM-written TypeScript visualizations at motherduck.com/blog
• Guides: Read the docs on MotherDuck's new Markdown context layer for agents at motherduck.com/docs
• MotherDuck Blog: Keep up with all things MotherDuck at motherduck.com/blog
• MotherDuck Community: Join the community Slack at community.motherduck.com
• Connect with Jordan: LinkedIn | X
  
  
  

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• AI Code Reviews: Automate reviews to catch bugs, security risks, and performance issues before they hit production.
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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

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• The Era of AGI
• A Bad Day For Humans, a Worse Day For Humanity
• Meta is switching to Slack because it says it's better for AI agents
• Agency and Agents
• The Superdark Factory
• Spec-Driven Development for Agentic Software Engineering: Harnessing Human-Agent Teamwork
• Inside Dev Interrupted’s agentic newsroom and what it reveals about the future of tech media
• Kiro Pro for students: kiro.dev/students 

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• AI Code Reviews: Automate reviews to catch bugs, security risks, and performance issues before they hit production.
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• 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.

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

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• Airbyte: Explore the open-source data integration platform powering AI context at airbyte.com
• Agent Blueprint: Read Michel Tricot's newsletter on building agentic data infrastructure on Substack
• Connect with Michel: LinkedIn

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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

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• NVIDIA to Acquire Hugging Face
• Teaching Everyone to Fish for Tokens
• OpenClaw 2.0, Accidentally
• Creepy crawlies
• Reject Change, Sometimes
• Good Culture is the Biggest Productivity Hack, Not AI

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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.