The useful question is what changes for users, developers or buyers, and whether the announcement stays industry context or becomes something people can actually use.

The GitHub Copilot app introduced stacked sessions and pull requests, allowing developers to chain updates in a repository where each change builds on the previous one. A developer demonstrated this by modernizing a personal project that had not been updated since 2014, using React 15, Less for CSS, and an outdated version of react-bootstrap. The process involved multiple AI-assisted sessions, with Copilot automatically creating new branches and pull requests when adjustments were needed, streamlining what would have been a manual and error-prone task.

During the modernization effort, the developer encountered compatibility issues due to an existing partially updated development branch. Copilot’s ability to switch sessions and port styling decisions to the correct branch prevented wasted effort. The app closed an unsuccessful pull request and initiated a new one targeting the development branch, reducing frustration and saving time. This feature allowed the developer to pivot quickly without starting over, a significant improvement over traditional workflows.

Further testing revealed outdated React warnings tied to react-bootstrap, prompting the developer to seek an upgrade plan. Copilot’s Plan mode recommended replacing the library entirely, but the developer opted to break the work into smaller, manageable sessions to avoid scope creep. This approach aligned with the stacked pull request model, ensuring incremental progress without overwhelming changes. The developer noted that AI-assisted workflows can tempt users to overhaul entire codebases at once, but stacked sessions help maintain focus and control.

The developer described the experience as transformative, highlighting the efficiency of stacked sessions and pull requests in the GitHub Copilot app. By chaining updates in sequence, the feature enabled a structured modernization process, reducing manual coordination and errors. The developer concluded that this workflow could represent a significant shift in how developers manage long-term code maintenance, particularly for legacy projects.