Searching the web is a great feature in theory, but every implementation I've used so far looks at the top X hits and then interprets it to be the correct answer. When you're talking to an LLM about popular topics or common errors, the top results are often just blogspam or unresolved forum posts, so the you never get an answer to your problem. More of an indicator that web search is more unusable than ever, but inte…
I've found that OpenAI's Deep Research seems to be much better at this, including finding an obscure StackOverflow post that solved a problem I had, or finding travel wiki sites that actually answered questions I had around traveling around Poland. However it finds its pages, they're much better than just the top N Google results.
Not sure how OpenAIs version works, but grok's approach is to do multiple rounds of searches, each round more specific and informed by previous results