How to use Claude to prototype a search intelligence tool
The author prototyped search intelligence with Claude and Claude Code, encountered excessive API consumption, then used SerpAPI and Lovable for a tool used daily.
news.ycombinator.com
Suggested prompt
Suggested prompt written by Agents In Use, not the source author. Replace bracketed inputs and review tool permissions first.
Prototype [search intelligence tool] for [tracked topics] with a frontend and backend. Use [search API] for on-demand results, trend charts, and summaries. Define the data architecture and expected API calls before implementation, and make [API usage budget] visible for review.
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See placements →Evidence at a glance
Sourced account- Source author
- noashavit
- Original account
- Read the source ↗
- Published
- Source link checked
- Reported result
- The Claude Code prototype exhausted API credits after 30 minutes. After adopting SerpAPI and using Lovable, the author produced a shareable tool they use every day.
- Human involvement
- The author noticed API credit exhaustion, changed the data source, tried multiple builders, and reports daily use of the result.
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How the agent did it
- Build a Claude artifact with hardcoded queries and regular refreshes.
- Use Claude Code to build a frontend and backend with on-demand search.
- Encounter exhausted API credits after 30 minutes of prototyping.
The author began a search intelligence tool as a Claude artifact with hardcoded queries for topics they followed and regular automatic refreshes. It worked, but lacked flexibility. They moved to Claude Code and built a frontend and backend with on-demand search, multiple API calls, trend charts, and AI summaries.
That prototype exhausted their API credits after 30 minutes. The author attributes the problem to missing data architecture: they had described features rather than a system, and Claude Code built what they requested. The post presents this as a design mistake, rather than evidence that Claude solved the architecture problem.
The author then adopted SerpAPI and tried a refined prompt in other builders. Bolt.new helped initially but stalled when pushed. Lovable produced a working prototype in the first session, followed by a couple more sessions to make it shareable. After a week of evening work, the author says they use the resulting tool every day.
The shared tool offers an AI analyst overview, search trends, relevant results, and recent LinkedIn posts for a keyword, topic, or person, using the user’s SerpAPI key.
Who it's for: Builders exploring search products who can evaluate API consumption and revise their system design.
Prompt
Suggested prompt (written by Agents In Use, not the author's)
Source: Hacker News · noashavit
Frequently asked questions
Why did the Claude Code prototype run out of credits?
The author says it burned API calls unexpectedly and lacked a real data architecture. They had described features, not a system, and exhausted API credits after 30 minutes.
Which builder produced the shareable version?
The author reports a working prototype in the first Lovable session and a shareable version after a couple more. Claude and Claude Code were used for earlier versions.
More details
Remaining steps
- Adopt SerpAPI and test a refined prompt in bolt.new and Lovable.
- Continue Lovable sessions until the prototype is shareable.
About this account
Claude generated the initial artifact and Claude Code built requested frontend and backend features; later builders produced further versions.
Platform: Hacker News. Attribution: https://news.ycombinator.com/item?id=47989460. Prompt: Suggested (written by Agents In Use, not the author's). Sourced by the Agents In Use pipeline.
Credit: noashavit on Hacker News
Source published
Added to Agents In Use
Source checked
Tools and topics
Claude artifacts · Claude Code · SerpAPI · bolt.new · Lovable
Prototyping · Search data · API usage
Editorial completeness: 100/100. Measures documented fields, not agent performance or verified outcomes.