Earlier quoted context omitted.
You can just use Cursor as a chat assistant if you want.
But then you're paying far more than just using Claude web which can be used for tasks other than coding.
Tracking Copilot vs. Codex vs. Cursor vs. Devin PR Performance
41–50 of 124 posts
Re: Tracking Copilot vs. Codex vs. Cursor vs. Devin PR Performance
#42Re: Tracking Copilot vs. Codex vs. Cursor vs. Devin PR Performance
#43https://play.clickhouse.com/play?user=play#V0lUSCByZXBvX3N0Y...
I've also added some less popular agents like jetbrains-junie, and added a link to a random pull request for each agent, so we can look at the example PRs.
Re: Tracking Copilot vs. Codex vs. Cursor vs. Devin PR Performance
#44Total PRs between Codex vs Cursor is 208K vs 705, this is an enormous difference in absolute PRs. Since cursor is very popular, how does their PRs is not even 1% of codex PRs?.
Re: Tracking Copilot vs. Codex vs. Cursor vs. Devin PR Performance
#45Total PRs between Codex vs Cursor is 208K vs 705, this is an enormous difference in absolute PRs. Since cursor is very popular, how does their PRs is not even 1% of codex PRs?.
Re: Tracking Copilot vs. Codex vs. Cursor vs. Devin PR Performance
#46Total PRs between Codex vs Cursor is 208K vs 705, this is an enormous difference in absolute PRs. Since cursor is very popular, how does their PRs is not even 1% of codex PRs?.
The happy path way of getting code out of Codex is a PR. This is emphatically not true for Cursor.
Re: Tracking Copilot vs. Codex vs. Cursor vs. Devin PR Performance
#47(Disclaimer: I work on coding agents at GitHub) This data is great, and it is exciting to see the rapid growth of autonomous coding agents across GitHub. One thing to keep in mind regarding merge rates is that each of these products creates the PR at a different phase of the work. So just tracking PR create to PR merge tells a different story for each product. In some cases, the work to iterate on the AI generated co…
This is a great point! But there's an important tradeoff here about human engineering time versus the "learning in the open" benefits; a PR discarded privately consumes no human engineering time, a fact that the humans involved might appreciate. How do you balance that tradeoff? Is there such a thing as a diff that's "too bad" to iterate on with a human?
We are looking into paths where we can support this more personal/private kind of PR, which would provide the foundation within GitHub to support the best of both worlds here.