Try for free
Data Day with Greg Michaelson
Data Day with Greg Michaelson

Rob Zuber - The Future of Software Engineering in the Age of AI Agents

20 June 2026 55:06 Greg Michaelson

Listen to episode

About this episode

In this episode of Day Today, Greg Michaelson sits down with Rob Zuber, CTO of CircleCI, for a wide-ranging conversation about software engineering, developer tools, AI coding agents, and the future of building software.

Rob shares his journey from manufacturing engineering and factory-floor data analysis to leading one of the most influential companies in modern software delivery. Along the way, he discusses the evolution of CI/CD, lessons from the dot-com era, and why today's AI boom feels both familiar and fundamentally different.

Topics include:

  • The origins and evolution of CircleCI
  • Why speed and feedback loops remain the core of software delivery
  • How engineering teams are using AI coding agents like Claude Code and Codex
  • Managing token costs and AI infrastructure at scale
  • The changing role of IDEs, terminals, and developer interfaces
  • Agent experience (AX) and designing products for both humans and AI systems
  • Fine-tuning models versus large-context workflows
  • The future of code reviews, pull requests, and automated validation
  • What software engineering organizations will look like as AI-generated code becomes the norm

Rob also explores a provocative question: if AI can write code, can we eventually trust systems enough that humans no longer need to review every line? The discussion offers a thoughtful look at where software development is headed and the challenges engineering teams must solve next.

Whether you're a software engineer, engineering leader, startup founder, or AI enthusiast, this conversation provides valuable insight into the technologies and workflows reshaping the future of software development.

More AI podcast episodes

Browse all →

Want to find AI jobs?

Join thousands of AI professionals finding their next opportunity

We respect your inbox. Unsubscribe at any time.

© 2026 Data Day with Greg Michaelson. All rights reserved.

Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.

Still have questions?

Contact Support