My colleagues and I built a research prototype that integrates social media conversations about a paper into the paper reading experience. It retrieves relevant social media discussions about a paper and presents them alongside it, with double-sided synchronization so you can see which parts of the paper a discussion relates to and which discussions exist for any given section. The research paper on this work is published at UIST 2025 (https://dl.acm.org/doi/10.1145/3746059.3747647).
Today I got access to the new GitHubNext product, Copilot Workspace. I decided to test it on an old tiny Python package I developed three years ago for fun. The library is meant to simulate random walks. At that time I opened an issue for handling dead-end cases by randomly jumping to new states. Today I used the same issue for the starter. You can see the results of Copilot Workspace.
Caveats:
1. It looks very neat
2. It took nearly 5 minutes to come up with the solution after specification, planning, and then opening a pull request
3. the proposed solution is not actually true. Although it catches a valid case by checking if there is a row in the transaction matrix summed up to 1, this case is already prevented in `__init__`. A more plausible solution would be to check if the current state has a diagonal 1 in the transition matrix, which results in the random walker going back to the same state after that.
Reading the documentation, I was expecting more tbh.
As I found out there is no way to customize the API. The response is always a JSON dump of that google Sheet.