GitHub’s Post

An impressive step toward making version control and collaboration even more seamless. Looking forward to seeing how developers leverage these capabilities.

Smaller, focused pull requests aren't just a developer best practice, they're a business advantage. Faster reviews, fewer conflicts, and quicker releases help engineering teams deliver value with greater confidence. Great feature from GitHub. 👏

Stacked pull requests fix the review bottleneck, and on a codebase this old the thing that makes them stick is the test surface underneath. The risky part of an 8 year old repo is rarely the change itself, it is the behavior nobody ever wrote down, so a stack only moves fast when each layer has something proving the old behavior still holds. Good to see the tooling catch up to how people actually want to break work apart.

Stacked sessions make the most sense for modernization because they force the agent work back into reviewable units. The trap I’ve seen is letting each stack layer inherit too much implicit context; then reviewers have to debug the chain instead of the change. I’d want every PR in the stack to carry its own migration invariant, test delta, and rollback note. That keeps AI-generated scope creep visible, especially when replacing old dependencies while preserving behavior.

A great post about someone using Copilot to modernize a decade-old React app, stacked sessions, stacked PRs, the works. The AI tooling is genuinely impressive. But it's a sharp reminder that our biggest bottleneck was never "can someone write this code" — it's everything we bolted on around the writing.

AI increases the amount of code a team can change, but human review capacity doesn’t scale at the same rate...Making changes smaller and independently reviewable may become even more important in AI-assisted development, not less. Besides, the real win with stacked PRs is reducing review surface while keeping every step independently testable. Once that breaks, the complexity comes back fast.

I think the real question isn't what tools you use, it's whether your team still remembers why the code was written the way it was. I've seen teams throw Copilot at legacy systems and end up with modern syntax wrapped around assumptions nobody understands anymore. I don't think AI fixes the knowledge gap. I think it just lets you ship broken faster.

Modernizing legacy code is key to building scalable software.

re-hiring that super star who wrote it all 8 years ago and getting some of that tribal knowledge back. hahaha