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

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 LinkedIn
Subscribe to our YouTube Channel
Follow the hosts:
Follow Andrew
Follow Ben
Follow Dan
Follow today's stories:
After starting the tokenmaxxing panic, Uber's CTO is back with a very different AI story
Auto mode is now the default in Claude Code for Pro, Max, and Team plans
Introducing Muse Glimmer: An Open Agentic Model That Runs on Your Device
Why Open Source Matters for AI
Your SDLC is your context engineering
Do personalized skills help coding agents? An empirical study of developer interaction histories
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.