Like sibling commenter mentioned, simonw’s blog is a great resource.
Regarding your point around being able to whip up the code yourself - the point is to have a decent starting point to save time and energy. Like you said, you know the edge cases so you could skip the boring parts using GPT and focus purely on fixing those. Though, with more prompting (especially providing examples), GPT can also handle that for you.
I have nearly 2 decades of experience as a developer and it took me a while to reorient my flow around LLMs. But now that I have, it’s truly gamechanging.
And since you asked, here’s my system prompt:
You are an experienced developer who follows industry standards and best practices. Write lean code and explain briefly using bullet points or numbered lists. Elaborate only when explaining concepts or making choices. Always mention which file and where to store provided code.
Tech Stack: < insert all the languages, frameworks, etc you’d like to use >
If I provide code, highlight and explain problematic code. Also show and explain the corrected code.
Take a deep breath and think step by step.
Also, always use GPT4 and customize the above to your style and liking.
I will definitely try this out when I have time later in the day.
There is some code I would really prefer not to write that is a decent test case for this and won't expose company code to GPT. Will give feedback when I am done. Maybe you are correct.
If you really want to experiment, give Cursor a try. It’s free up to a limit, so maybe it’ll be enough for your example use case.
It handles even more complex use cases and will automatically include/patch code for you via the inbuilt LLM framework. This helps with iteration and modifications as you massage it to what you need. Plus, it’ll scan your code and find the languages/frameworks automatically.
Finally, keep in mind that the goal should not be perfect production code - that’s just Twitter AI hype. It’s about saving time and energy for you (the human) to achieve more than possible before.
I tried your prompt and the above approach and it took me about 45 minutes of putsing around to get a result I am happy to begin iteration on.
Effectively: I have an 80bit byte array representing a timestamp struct consisting of a 48 bit unsigned integer for seconds and a 32 bit unsigned integer representing nanoseconds. The byte array is big endian and the host systen is little endian.
I gave it full signatures for all functions and relevant structs and instructions on how I would want the parsing done regarding algorithmic complexity and yet it still took multiple iterations to get anything useful.
At this point it is converting to little endian during the decode then doing a check if host the system is big endian and converting back to big endian if that is true.
There is likely some easy optimisations to be done where there and I would have definitely have gotten to this point quicker had I just written the 10 lines of code this needed and would have done the optimisations where I'm pretty sure that entire operation can happen in a few instructions.
Regarding your point around being able to whip up the code yourself - the point is to have a decent starting point to save time and energy. Like you said, you know the edge cases so you could skip the boring parts using GPT and focus purely on fixing those. Though, with more prompting (especially providing examples), GPT can also handle that for you.
I have nearly 2 decades of experience as a developer and it took me a while to reorient my flow around LLMs. But now that I have, it’s truly gamechanging.
And since you asked, here’s my system prompt:
You are an experienced developer who follows industry standards and best practices. Write lean code and explain briefly using bullet points or numbered lists. Elaborate only when explaining concepts or making choices. Always mention which file and where to store provided code.
Tech Stack: < insert all the languages, frameworks, etc you’d like to use >
If I provide code, highlight and explain problematic code. Also show and explain the corrected code.
Take a deep breath and think step by step.
Also, always use GPT4 and customize the above to your style and liking.