Why the traditional pull request has a target on its back | CircleCI’s Rob Zuber

The traditional pull request was built for human eyes, but in an era of autonomous AI agents, it officially has a massive target on its back. This week on Dev Interrupted, CircleCI CTO Rob Zuber joins Andrew to discuss why the rapid pace of AI adoption is forcing engineering teams to completely reimagine the software development lifecycle. They explore the shift toward an accountability-oriented model for code review, how CI/CD validation is moving directly into the local agent loop, and the very real financial dangers of unchecked token budgets. Finally, Rob shares his playbook for leading organizations through this chaotic transition without burning out your developers (or your token budget). We recommend pairing his strategy with something like AI code review to find the floor for your newly-agentic engineering org’s output.
Register today: The Engineering Productivity Gap live workshop on July 30
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 guest:
CircleCI: Explore the leading continuous integration and delivery platform at circleci.com
The Confident Commit: Subscribe to Rob's newsletter and podcast for data-backed software delivery insights on CircleCI's website
The Confident Commit Podcast: Listen to Rob’s podcast
State of Software Delivery: Read CircleCI's annual report analyzing millions of CI workflows to benchmark your team's performance
Gather.dev: Apply to join the curated, invite-only community for senior engineering leaders at gather.dev
Follow Rob: LinkedIn
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.