[yusina]

> I would read the official documentation of each db, forums, blog posts, stackoverflow entries, etc. It was time consuming on the searching side. The time it took to read all the sources was fine for me (it's learning time, so that's always welcomed).

This learning time that you welcomed is what you will now miss out on. The LLM gives you an answer, you don't know how good it is, you use it, and soon enough, if running into a similar issue, you will need to ask the LLM again since you were missing out on all that learning the first time which would have enabled you to internalize all the concepts.

It's like the regex engine example from the article. An LLM can create such a thing for you. You can read through it, it might even work, but the learning from this is orders of magnitudes less than what you get if you build this yourself.

[dakiol]

I think it depends. LLMs can link references of where they took the content they throw at you. You can go and read such references. I like what LLMs provide, and at the same time I don't wanna blindly follow them, so I always allocate time for learning whether it's with LLMs or not.

[nunodonato]

Only if you use LLMs wrong. Today's models have deep research which will generate a comprehensive analysis with proper citations

[msgodel]

I feel like I should point out that's the dialog engine not the model itself.

[yusina]

I think you either didn't read my response or missed the point. No matter if the LLM output is useful or not, the learning outcome is hugely impacted. Negatively.

It's like copying on your homework assignments. Looks like it gets the job done, but the point of a homework assignment is not the result you deliver, it's the process of creating that result which makes you learn something.