Can I vibe code Asinseed?

Build a full-stack Amazon Keyword Research web application using Next.js (App Router), Tailwind CSS, PostgreSQL, and Prisma. 1. DATA MODEL: Create schema models for 'Asin' (asin_code, title, image_url, updated_at), 'Keyword' (term, search_volume, organic_count), 'AsinKeywordRank' (asin_id, keyword_id, rank_position, relevancy_score, last_checked), and 'LookupHistory' (id, query, created_at). 2. BACKEND API: Implement an API route POST /api/reverse-asin that accepts an Amazon ASIN string. Integrate with a mock data adapter (or third-party Amazon SERP API provider) to fetch keywords that rank for this ASIN. Return an array of keywords with search_volume, rank_position, and relevancy_score. Store result records in PostgreSQL. 3. FRONTEND UI: Create a clean dashboard with a prominent ASIN search input. Render results in a fast DataGrid with columns for Keyword, Search Volume, Rank Position, Relevancy Score, and Search Volume Trend indicator. Add client-side filtering by minimum/maximum search volume, rank position range, and keyword text search. Include a button to export filtered tables to CSV. 4. FAILURE HANDLING: Handle invalid ASIN formats with regex validation before requesting data. Render rate-limiting error messages gracefully when API quotas are hit. Out of scope: user authentication, payment processing, and internal web-scraping proxy management.

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