In this video, we'll talk about AI prompt engineering.
Prompt engineering is the process of designing and refining prompts to guide AI systems in
the best possible way, to get efficient output.
And there's a couple of core techniques.
First, be explicit.
The more explicit you are, the better your answer can be.
So not just install a web server, but better use install Apache on Ubuntu 24.04, so that
AI can consider all the differences that might apply if you're not specific.
As for structure, that is also a part of be specific.
If you ask generate a YAML file, generate a configuration file, and so on, then AI
knows what to do, and it can be more specific.
And also, it might be a good idea to provide examples.
If you want a solution to comply to certain standards that are used within your organization,
you might want to feed an example.
So that looks like this, and then you copy-paste the YAML code that you normally would use.
Iterate and refine.
And that means that you need to evaluate the answer that the AI system has given you.
And then you can perfectly ask, hey, improve the previous answer with information about.
And while you do so, make sure that AI doesn't forget about what you did in the previous
answer.
If you are going to iterate, that is a real risk that might be happening.
And also, it's a good idea to break tasks into pieces.
And if you respect all of this, you should be more efficient in your prompt engineering
and get better results.