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

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 PondOFFERSStart 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.

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/XOFFERSStart 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.

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 expertiseOFFERSStart 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.

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 LinesOFFERSStart 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.

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 developersOFFERSStart 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.

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 PlatformsFollow 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 blogOFFERSStart 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.

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 PlatformsFollow 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 EnoughOFFERSStart 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.

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 PlatformsFollow 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 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 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 PlatformsFollow 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 MethodologyOFFERSStart 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.

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 PlatformsFollow 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 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.