The self-authoring wiki, beating brain fry, and Obsidian as memory is a trap

Forget the massive GPU clusters. According to Tim Dettmers, research scientist at Ai2, you can build a state-of-the-art AI coding agent with what he calls a "hot plate and a frying pan." This week on Dev Interrupted, Andrew sits down with Tim to unpack how his resource-strapped team built the SERA model using a fraction of the compute power of major labs. They explore the tactical engineering behind synthesizing training data from private codebases without verification tests, proving that the open-source community is uniquely positioned to out-specialize frontier models. Finally, Tim shares his contrarian take on the future of token economics, explaining why the cost of AI might actually spike as compute efficiency hits a physical wall.OFFERSStart 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 LINEARBAI 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.

Have you or a loved one been afflicted by "brain fry" after managing too many autonomous agents? This week on the Friday Deploy, Andrew and Ben explore the cognitive toll of orchestrating AI swarms and share Kelly Vaughn’s expert strategies for avoiding burnout. The hosts also discuss Google's new campaign to punish websites that hijack the back button, the breakthrough of running Gemma 4 natively on mobile devices, and a new 8-step maturity model for building agentic data pipelines. Finally, they dive into a heated debate over whether Obsidian flat-files are a scalable memory solution for AI, comparing the methodology to Andrej Karpathy's new agent-compiled wiki system.Read the guide: The APEX FrameworkFollow 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:Introducing a new spam policy for "back button hijacking"Google Gemma 4 Runs Natively on iPhone With Full Offline AI InferenceWater Town: The Agent Swarm Data StackStop Calling It Memory: The Problem with Every "AI + Obsidian" TutorialThe Wiki That Writes ItselfBreaking out of the "brain fry" spiral of AIAfter Burnout by Kelly VaughnOFFERSStart 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 LINEARBAI 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.

Are your AI agents quietly ignoring their guardrails just to get the job done? This week on Dev Interrupted, Andrew sits down with Wayfound AI founder and CEO Tatyana Mamut to discuss why traditional, deterministic software testing falls completely short when evaluating stochastic AI models. They explore the growing strategic divide between OpenAI and Anthropic, the urgent need for independent "guardian agents," and what it takes to run a company with just 4 humans and 27 agents. Finally, they break down how to stop the chaotic game of telephone between engineers and business leaders by relying on "Deep-T" subject matter experts to evaluate what good AI output actually looks like.Read the guide: The APEX FrameworkFollow 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:Wayfound AI: Secure your autonomous enterprise and align your AI workforce with an independent agent supervision platform.Moltbook: Explore the viral social network built exclusively for AI agents, where you can observe Tatyana's OpenClaw agent, Aphasia, in action.Anthropic's Agent Autonomy Research: Read Anthropic's report on how people actually use agents and why post-deployment monitoring is an absolute necessity.OpenClaw: Explore the viral, open-source personal AI assistant framework.Follow Tatyana Mamut on LinkedInOFFERSStart 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 LINEARBAI 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.

Is the secret to slashing your token costs by 65% forcing your LLM to speak like a caveman? This week on the Friday Deploy, Andrew and Ben test out a hilarious new Claude plugin that reduces AI output to primitive shorthand before diving into Anthropic's $100 million push to win the cybersecurity arms race with Project Glasswing. The hosts also unpack the sudden release of four game-changing open-source models—including Gemma 4 and Holo3—and explain why modern AI benchmarks are proving that humans still have a cognitive edge. Finally, they wrap up by sharing how they deploy custom background agents to hack their way through expo floors at industry conferences.Read the guide: The APEX FrameworkFollow 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:Project GlasswingTool School: Benchmarking 101 (How To Read AI Model Report Cards)Four Open Models Just Proved You Can Own Frontier AI at Every ScaleJuliusBrussee/cavemanOFFERSStart 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 LINEARBAI 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.

Are your AI coding tools actually making your team faster, or are they just creating downstream chaos? This week, Ben Lloyd Pearson and Dan Lines introduce APEX, LinearB’s new engineering leadership framework built explicitly to measure and manage software delivery in the AI era. Moving beyond traditional frameworks like DORA and SPACE, APEX balances AI Leverage, Predictability, Efficiency, and Developer experience to ensure upstream code generation translates into actual business value. Tune in to learn how to break past the illusion of coding speed, prevent AI slop from clogging your review pipelines, and discover which pillar of the APEX framework your team needs to tackle first.Download the APEX FrameworkFollow 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 APEX Framework: Explore the full operating model, visual breakdowns, and the guide to operationalizing the metrics.Workflow Automation: Learn about LinearB's gitStream (policy-as-code for PR automation) and WorkerB (developer bot for minimizing idle time).OFFERSStart 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 LINEARBAI 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.

Are advertisements not-so-secretly infiltrating your code reviews? This week on the Friday Deploy, Andrew and Ben break down the controversy over GitHub Copilot injecting promotional tips into pull requests and unpack the massive Anthropic code leak that exposed Claude Code's hidden features. The hosts also explore Shopify's strategy for cutting AI inference costs by 75x using smaller, self-hosted models. Finally, they discuss the game-changing Pretext rendering library, the cyclical hype of "dead" tech trends, and how agent-wielding "vibe maintainers" are rewriting the rules of open-source software.Read the guide: The APEX FrameworkFollow 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:GitHub backs down, kills Copilot pull-request ads after backlashSoftware's Next Epoch: Our Investment in R.I.P. grepAnthropic accidentally leaked Claude Code's entire source. Here's what 512,000 lines revealShopify Cuts Inference Cost by 75x Using Qwen 3 for Merchant Data ExtractionPretext Does What CSS Can't — Measuring Text Before the DOM Even ExistsVibe MaintainerOFFERSStart 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 LINEARBAI 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.

AI agents have officially arrived on an internet that simply wasn't built for them. So how do we build the infrastructure to keep them safe, productive, and contained? This week, Andrew sits down with Matt Boyle, Head of Product, Design and Engineering at Ona (formerly Gitpod), to discuss evolving cloud development environments into secure, enterprise-grade "agent jails." They explore the mechanics of Project Veto’s kernel-level security, the slow death of the traditional IDE, and how the rise of AI is transforming developers into full-stack, T-shaped product owners. Finally, Matt shares his vision for the future of the SDLC, detailing how organizations can safely balance strict compliance with the bleeding edge of autonomous software factories.Download the APEX FrameworkFollow 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:Learn more about Ona (formerly Gitpod) and read their latest blog announcements, including Veto.Connect with Matt on LinkedIn | X (Twitter)OFFERSStart 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 LINEARBAI 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.

Is OpenAI killing off its viral video generator to pivot toward the enterprise market? This week on the Friday Deploy, Andrew and Ben banter over the demise of Sora and examine Anthropic's new Auto Mode safety controls. The duo then explores a major New York Times piece that proves the conversation about the end of traditional computer programming is officially going mainstream. Finally, they cover Microsoft's attempt to win back frustrated Windows 11 users and break down the POST leadership framework to help you build a more balanced engineering team.Read the guide: The APEX FrameworkFollow 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:OpenAI pulls the plug on Sora video app, Disney dealAuto mode for Claude CodeCoding After Coders: The End of Computer Programming as We Know ItMicrosoft's "Fix" for Windows 11: Flowers After the BeatingPOST: People, Operations, Strategy, TechnologyOFFERSStart 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 LINEARBAI 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.

Over 88% of developers use AI regularly, but AI-assisted pull requests merge at less than half the rate of human-authored code. In this episode, Dan Lines and Ben Lloyd Pearson break down the findings from LinearB's 2026 Engineering Benchmarks Report to reveal how AI is fundamentally reshaping software delivery. They explore the stark behavioral differences between unassisted, AI-assisted, and fully agentic pull requests, highlighting how AI accelerates code generation but exposes massive bottlenecks in the review process. Tune in to learn why organizations must prioritize AI readiness, data quality, and context engineering before they can translate raw AI adoption into actual business impact.LinearB 2026 Engineering Benchmarks Report: Download the full 48-page report to see where your metrics stand.Follow the show:Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts:Follow AndrewFollow BenFollow DanOFFERSStart 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 LINEARBAI 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.

Are rolling token blackouts and late-night AI coding shifts about to become the new normal for developers? This week on the Friday Deploy, Andrew and Ben explore the shifting economics of AI compute before debating whether the Model Context Protocol (MCP) was fundamentally overhyped. The hosts also dive into "context anchoring" to prevent model compaction during long coding sessions, why optimizing the wrong bottlenecks makes AI an amplifier for bad processes, and the nostalgic resurgence of the decentralized "small web." Finally, they break down the new rules of workplace AI etiquette to help you avoid serving your coworkers "sloppy pasta" disguised as real work.Read the guide: The APEX FrameworkFollow 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:MCP is Dead; Long Live MCP!Context AnchoringIf you thought the speed of writing code was your problem - you have bigger problemsThe “small web” is bigger than you might thinkStop SloppypastaOFFERSStart 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 LINEARBAI 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.