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Do you have a strategy to supplement ChatGPT to handle post-2021 updates to languages and libraries? I tried it on a NextJS repo and it came up with something that looked like it would have been correct a few versions ago, but I had to make some manual changes. Certain fast-moving ecosystems might frequently have this issue.
Incredible work, this is the most exciting AI dev tool I've come across! Do you have a strategy to supplement ChatGPT to handle post-2021 updates to languages and libraries? I tried it on a NextJS repo and it came up with something that looked like it would have been correct a few versions ago, but I had to make some manual changes. Certain fast-moving ecosystems might frequently have this issue.
You can give Sweep docs about a framework and it should help a lot.
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The code produced in the "getInitials" function handles absolutely no corner cases whatsoever. It also didn't add any tests to the PR. All this does is making sure your website will crap all over itself 2 weeks into using this tool (death by a thousand cuts style) and you'll need to hire more people to fix whatever this thing fucks up. Just about the opposite of what automation is supposed to help with. Good luck!
That's completely right, the testimonials will look really strange if the names have 3+ words in them. That's why we're targeting really strong developers to review Sweep's PRs. An experienced dev(like you) will be able to read the code, think "hey this needs tests and edge cases" and then request changes instead of merging it.
Is Sweep also taking in suggestions and then incorporates them with follow-up commits to the PR?
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I just had it fix some outdated copy in a part of the UI. The nice thing is I didn't have to find the file myself, I just described what was wrong like I would a junior eng and let it find and fix it. Worked on the first try!
That's exactly the use case we want. We also let you specify the file path (ex: "main.py"). We noticed that Sweep's search works way better if there are comments, because the comments match up really well with the search queries (language language is easier than language code)
It'd significantly increase the costs though.
And I'm curious to know more about your costs of deployment and running on Modal.
Excellent, this solves the #1 problem I've had with LLM development assist -- providing context of the existing application source when making new requests. Delivering the output via a PR is a nice touch. Already created 2 PRs. Still need a tiny bit of tweaking manually before I merge these, but definitely saved at least 30 mins. Here are the 2 PRs that it generated for others curious to see its capabilities: https:/…
How is your experience with Modal? And I'm curious to know more about your costs of deployment and running on Modal.
The developer experience is also great, so we highly recommend it :)
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That's completely right, the testimonials will look really strange if the names have 3+ words in them. That's why we're targeting really strong developers to review Sweep's PRs. An experienced dev(like you) will be able to read the code, think "hey this needs tests and edge cases" and then request changes instead of merging it.
Thanks for staying constructive and on topic. Super interesting tool and amazing video! Is Sweep also taking in suggestions and then incorporates them with follow-up commits to the PR?
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That's exactly the use case we want. We also let you specify the file path (ex: "main.py"). We noticed that Sweep's search works way better if there are comments, because the comments match up really well with the search queries (language language is easier than language code)
Did you consider first asking LLM to explain what a code snippet does and use that instead? It'd significantly increase the costs though.