Thread by @RubenHssd

OpenAI shared the most complete library of guides to prompt chatgpt.

47 links of videos & academic papers.

I read them all, and made a top 10.

#1 → prompt engineering

Starting with the basics:
→ prompting techniques

All the techniques you need to know:
> zero-shot
> few-shot
> self-consistency sampling
> chain of thoughts (CoT)
> tree of thoughts (ToT)

First, what is the Chain of Thought?

#2 → chain of thoughts

It's a prompting technique that forces the LLM to think before giving a good answer.

Start by creating:
→ a step-by-step reasoning process.

Breaking down a problem into bite-size steps is easier for humans... & LLMs.

#3 → tree of thoughts:

What is the Tree of Thoughts?

It helps you brainstorm with the LLM.
> it creates a tree-like structure of ideas.
> each idea is a step to solve a problem.

You're the one selecting the right path:
→ the LLM simply provides options.

Now for the most famous video:

#4 → Andrej Kharpathy shared this famous Youtube video a year ago about:

> how to build GPT form scratch
> reading & exploring the data
> tokenizations

Here's the link:


And a month ago, he did a new one explaining how to build a tokenizer:

#5 → the tokenizer is a necessary component of an LLMs.

It's like a puzzle maker. It takes a big piece of language & breaks it down into smaller puzzle pieces (token).

I'm fascinated by Andrej Kharpathy teaching us everything for free:

#6 → jailbreak LLMs

1. Find a rule chatgpt needs to follow:
→ never use the word "computer"

But if you ask the right questions:
chatgpt say the forbidden "computer".

Just like "DAN" became famous, it's a reminder any LLM can be jailbreak.

For another prompting technique:

#7 → multi-agent debate

You create multiple agents & make them discuss with each other.

→ LLMs debate their answers over a few rounds to arrive at a common answer.

It helps for:
> mathematics.
> reasoning processes
> reducing hallucinations

#8 → reAct + CoT:

The benchmark said combining ReAct & CoT is the best way to prompt LLMs.

ReAct is a fact-driven method:
> ask the LLM to reason & act.

CoT sometimes makes up information that isn't true.

The best approach for answering questions is to combine their strengths.

#9 → prompt perfect

OpenAI shared a (paid) tool that helps you rewrite a perfect prompt for you.

All you need to do is:
> write your prompt
> send it
> click on "optimize"

And the chatbot craft a new prompt for you that you can edit & send again.

#10 → Open AI evals
Evals are designed to evaluate LLMs.

It's crucial for anyone working with LLMs.

It helps you understand how updates in model versions can impact your project.

Here's where to find it: github(dot)com/openai/evals

Last thing before you scroll away:

I run daily tests on LLMs like chatgpt, gemini & claude everyday to master them.

Check my profile @rubenhssd for more.

If you'd like to support me, a like or a simple RT goes a long way :)