I think we've been approaching AI web search the wrong way. Instead of searching for information... I tried assigning an entire research task. I built a Web Search Agent to track the biggest AI launches from the past week. Here's what happened.

1/ Normally this means opening way too many tabs. Company blogs. GitHub. Product Hunt. Hacker News. X. Then trying to connect everything into one useful picture. The searching isn't the hard part. Making sense of it is.

2/ So instead of writing another long prompt, I configured a reusable research agent. Its job was simple: Research the latest AI launches. Read the relevant sources. Group similar announcements. Explain why they matter. Return one structured report with citations.

3/ Then I hit Run. Instead of giving me another page of links... it searched across public sources, read the relevant pages, and built one report. Every key point links back to where it came from. That makes it much easier to verify before acting on anything.

4/ That was the biggest shift for me. A search API gives you information to work through. A Web Search Agent completes a research task and hands back something you can actually build decisions around. Same web. Completely different workflow.

5/ I can already think of a few places I'd use this: • monitoring competitors • tracking product launches • researching companies before outreach • following fast-moving AI markets If your work depends on current web research, it's worth trying. Build your own Web Search Agent:

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This feels much closer to having a research assistant than a search engine.

Opening twenty tabs every morning gets old fast. This is a better approach.

The citations are what sold me. Much easier to verify everything.

Definitely feels more useful for founders and product teams than standard search.

The reusable agent part is much more interesting than another prompt.

I like that the output is actually structured instead of just another list of links.

Having the original sources attached makes the results much more trustworthy.

This would save a lot of time for competitor research every week.

Progress like this is what keeps a community engaged.

Assigning complete research tasks to an agent instead of one-off searches produces much more useful output. This approach turns web search into a real workflow tool rather than a basic lookup.

cool setup. how did you handle false positives? they can really throw off task tracking.