Dev Interrupted

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.
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LinearB: Learn how to transform your SDLC and build an engineering context engine at linearb.io
gitStream: Explore LinearB's workflow automation tool for routing pull requests at linearb.io/platform/gitstream
Follow Ori and Dan on LinkedIn: Ori Keren | Dan Lines
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.

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 LinkedIn
Subscribe to our YouTube Channel
Leave us a Review
Follow the hosts:
Follow Andrew
Follow Ben
Follow Dan
Follow today's stories:
Bots Have Officially Taken Over the Internet, Humans Are The Minority
Claude Fable 5 and Claude Mythos 5
What it feels like to work with Mythos
Sam Altman says OpenAI's top token spender uses 100 billion tokens a month — and they're not even the world leader
How I Cut Our AI Spend in Half | "Tokenmaxxing" is Dead
Cleaning up after AI rockstar developers
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.

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
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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 blog
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.

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 LinkedIn
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Leave us a Review
Follow the hosts:
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Follow today's stories:
The AI SaaSpocalypse is a mirage
Mathematicians warn of AI threats to profession as industry encroaches
Introducing MAI-Code-1-Flash
AI Agent Guidelines for CS336 at Stanford
Trust Factory
You Don't Love systemd Timers Enough
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.

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 LinkedIn
Subscribe to our YouTube Channel
Leave us a Review
Follow the hosts:
Follow Andrew
Follow Ben
Follow Dan
Follow 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.