TL;DR: Writing custom scripts may be more effective for communicating with LLMs than using a fancy GUI. Details follow below :-).
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Like many here, I’ve been using both GitHub Copilot on VS Code and copy-pasting from a ChatGPT window.
Copilot is super hit or miss. Honestly, it rarely spits out anything useful unless I’m writing really repetitive code, where it might save me a few keystrokes. But even then, I could often just use some "Vim tricks" (like recording a macro or something) and get the same result. The built-in chat is a total waste of time... sigh.
ChatGPT has been way more helpful. But even with that, I often feel like it’s just a really fancy rubber duck or a glorified search engine. Still, it's way better than a Google/Bing search sometimes. I’ve been using a prompt someone here shared (maybe this one verbatim? [0] I need to shop for prompts again :-p) and that could be making a difference... I did not A/B test prompts but at least ChatGPT stopped apologizing so much lol.
I do want to try Cursor and Zed AI since I’ve heard good things. I also saw a recent post here about layouts.dev [1], and it looks really impressive. I’ve been asking ChatGPT for nice Tailwind CSS patterns, and the workflow in the that tool seems really streamlined and nice for web design (only caveat is... I'm not really interested in NextJS right now #shrug). BTW, nobody ever seems to talk about Gemini? I personally don't reach for it almost ever, for whatever reason...
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Now for the part about scripting your LLM interaction yourself... I’ve been working on a passion project lately, a programming languages database. I stumbled across this cool pattern [2] where I write code that generates data, and that data can then be used to generate more code. (Code is data is code, right?). I used OpenAI's Structured Output [3] and after massaging TypeScript types and JSON Schemas for a while, it generated pretty easy to digest output.
The interesting part is that you can use this setup to feed prompts into ChatGPT in a much easier way. Imagine something like this:
const code = SelectThingfromCodeBase(); // Not necessarily SQL! Perhaps just concatenating your files as ppl mention here.
const answer = sendChatGPT(promptFrom(code));
const newCode = generateCodeFrom(answer);
profitFrom(newCode); // :-p
I think this pattern has a lot of potential, but I need to play around with it more. For now, I’ve got a super crude but working example of how I pulled this off for my little programming languages database (coming soon, hopefully :-p). I did this so me or a contributor can run a script to generate the code for a pull-request to add more data to my project.
NOTE: my example isn’t very... "meta" since the data<->code thing doesn't really describe the project itself. To expand on this idea, we might need to dust off some of the old declarative tools like UML or 4GLs or come up with something inspired by those things. If this sounds vague, it’s because it is—but maybe it makes some sense to someone here :-p.
----
Like many here, I’ve been using both GitHub Copilot on VS Code and copy-pasting from a ChatGPT window.
Copilot is super hit or miss. Honestly, it rarely spits out anything useful unless I’m writing really repetitive code, where it might save me a few keystrokes. But even then, I could often just use some "Vim tricks" (like recording a macro or something) and get the same result. The built-in chat is a total waste of time... sigh.
ChatGPT has been way more helpful. But even with that, I often feel like it’s just a really fancy rubber duck or a glorified search engine. Still, it's way better than a Google/Bing search sometimes. I’ve been using a prompt someone here shared (maybe this one verbatim? [0] I need to shop for prompts again :-p) and that could be making a difference... I did not A/B test prompts but at least ChatGPT stopped apologizing so much lol.
I do want to try Cursor and Zed AI since I’ve heard good things. I also saw a recent post here about layouts.dev [1], and it looks really impressive. I’ve been asking ChatGPT for nice Tailwind CSS patterns, and the workflow in the that tool seems really streamlined and nice for web design (only caveat is... I'm not really interested in NextJS right now #shrug). BTW, nobody ever seems to talk about Gemini? I personally don't reach for it almost ever, for whatever reason...
----
Now for the part about scripting your LLM interaction yourself... I’ve been working on a passion project lately, a programming languages database. I stumbled across this cool pattern [2] where I write code that generates data, and that data can then be used to generate more code. (Code is data is code, right?). I used OpenAI's Structured Output [3] and after massaging TypeScript types and JSON Schemas for a while, it generated pretty easy to digest output.
The interesting part is that you can use this setup to feed prompts into ChatGPT in a much easier way. Imagine something like this:
I think this pattern has a lot of potential, but I need to play around with it more. For now, I’ve got a super crude but working example of how I pulled this off for my little programming languages database (coming soon, hopefully :-p). I did this so me or a contributor can run a script to generate the code for a pull-request to add more data to my project.NOTE: my example isn’t very... "meta" since the data<->code thing doesn't really describe the project itself. To expand on this idea, we might need to dust off some of the old declarative tools like UML or 4GLs or come up with something inspired by those things. If this sounds vague, it’s because it is—but maybe it makes some sense to someone here :-p.
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0: https://www.reddit.com/r/ChatGPTPro/comments/15ffpx3/comment...
1: https://news.ycombinator.com/item?id=41785751
2: https://github.com/EmmanuelOga/plangs2/blob/main/packages/ai...
3: https://platform.openai.com/docs/guides/structured-outputs