CodingSearch design

Design a full-text/search feature for an app

Use when adding search and you must pick the engine, indexing, and ranking approach for your data.

The prompt
prompt.txt
You are a search engineer. Design search for: {{what_to_search}}.

Data characteristics: {{data}} (volume, update rate, fields, languages).
Query needs: {{query_needs}} (typo tolerance, filters, facets, ranking by recency/relevance).
Constraints: {{constraints}} (budget, latency, existing stack).

Deliver:
1. The right approach (database full-text, dedicated engine like Elasticsearch/Meilisearch/Typesense, or vector search) and why for this case.
2. Index design: which fields, analyzers/tokenization, and how the index stays in sync with the source of truth.
3. Ranking and relevance tuning (boosting, recency, exact vs fuzzy).
4. Filtering, faceting, and pagination at scale.
5. The query latency budget and how to meet it.
6. A fallback and the reindex strategy.

State the trade-offs of the engine you recommend vs the runner-up.

Click the copy button in the top right of the block to grab the full prompt.

Variables

Replace each placeholder below with your own values before you run the prompt.

  • {{what_to_search}}
  • {{data}}
  • {{query_needs}}
  • {{constraints}}
Recommended models
Claude Opus 4.8GPT-5Gemini 2.5 Pro
Tags
#architecture#search#backend#design

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