What do you mean exactly? Would be fun to try to replicate.
You give ChatGPT a URL and expect it to be able to get the <title> tag from the HTML? Or you're pasting the whole HTML document?
> Repeat what I've set as the requirements in other words to ensure you understand it. Describe concisely at least two different approaches you could take to solve the problem while explaining the reasoning for why it's a useful approach. Chose the best approach, then think through how the problem could be solved step-by-step. Finally implement each step and provide a full solution.
Yesterday I used that to build (iteratively) a Rust CLI that downloads the last X HN comments have group-counts them by domain. Ended up being ~100 lines that GPT wrote by itself without any errors along the way.
The model was never able to reason; it was only able to generate responses that masqueraded as reasoning. Thorough investigations of its "reasoning process" reveal this at every stage of its development.
Math tutoring is a very legit application. It will be an incredible learning tool — but it needs better logical reasoning abilities with arithmetic. It seems like an easily solvable problem, given that math problems and answers are easy to scale into massive datasets.
Simplified example:
> system-prompt message
> user message: teach me linear algebra
> assistant: Sure, here's how [...] ```math 1 + 1```
> user message (but generated by application): ```1 + 1 = 2```
> assistant: and since 1 + 1 = 2, [...]
LLMs are great at generating text, but not at math, so make something else do the math for the LLM and then it can focus on what it does best.