When Coding Gets Faster, What Breaks Next? | React Universe On Air

AI can generate code faster than your team can review, test, or release it. That extra output can turn the next stage of software delivery into a bottleneck.

Matt Hargett, Consulting Principal Engineer at Callstack, joins Łukasz Chludziński to examine how AI agents change the software development lifecycle (SDLC). Drawing on nearly 30 years of experience, from QA at McAfee to agent workflows today, Matt explains how to find the current constraint and anticipate where work will pile up next.

In this episode, we discuss:

➡️ Why an on-time release can still lose money through support and infrastructure costs

➡️ How to give agents goals, context, and explicit quality expectations

➡️ How coverage-guided fuzzing can become an overnight testing and repair loop

➡️ How deployment bottlenecks grow release batches, and where phased rollouts and over-the-air updates fit

➡️ When to rethink Jira tickets and handoffs between teams

➡️ How to measure whether AI adoption improves delivery through support load, uptime, and production feedback

Which part of your delivery process would struggle if coding got twice as fast? Share your experience in the comments, and subscribe for more React Universe On Air conversations.

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