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Comment by qiller | Hacker News Reader

Are there any good write ups for LLM prompt engineering for beginners? Would love to recommend something to our Javascript developers - like this repo is great, but the basics are definitely getting lost in the python code

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Start with something like Phind.com or AutoExpert for ChatGPT Plus:

- https://phind.com

- https://chat.openai.com/g/g-LQHhJCXhW-autoexpert-chat

Phind has a whole Discord channel and they're pretty focused on building a great tool aimed at programmers. It's approaching pinned-tab status for me.

Yea sign up for ChatGPT Plus and make custom GPTs for yourself. That's where you can experiment with prompt engineering (custom instructions) to solve your immediate problems in a reusable way, without having to host a server or anything.

Disclosure: I work for Microsoft; this advice is my own.

Note that openai add more custom things to the prompt than you do, so you can't just drop your things into an assistant and have them work.

The prompt techniques in this submission are not for beginners. You can get >80% of the way there with using a simple system prompt such as:

    You are an expert JavaScript programmer. Write a JavaScript function based on the user input.

    You must obey ALL the following rules:
    - Only respond with the JavaScript function.
    - Never put in-line comments or docstrings in your code.

And then editing iteratively based on the output to whatever your desired use case is. If you want to test ChatGPT system prompts directly in a UI, you can do that in the OpenAI Playground: https://platform.openai.com/playground?mode=chat

Right, but going beyond the general purpose knowledge. For example wondering about best practices or approaches for building agents for a proprietary API - not extensive enough for something like Pinecone and all the knowledge should in theory fit into context

I'm shocked people are even talking about prompt engineering like it's a new discipline, when the measure of success is basically how you feel about the results.

I've found that GPT-4 works pretty well if you just talk to it like a person.

I found this resource [0] handy for getting a grasp on all the different terms people use (zero/one-shot, tree of thoughts, RAG, etc). It's not super detailed, which is actually a good thing for an introduction—it just gives a high-level introduction to each technique before linking to papers and other resources for more in-depth research if the technique seems likely to help. It was enough for me (a professional developer) to get started on some side projects with Mistral.

[0] Prompt Engineering Guide (https://www.promptingguide.ai/)

Excellent resource, thanks a lot!

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