Uncategorised decision
Mood2Movie
A small team or experienced developer can reproduce the core Mood2Movie functionality in about a week using public movie APIs and simple ranking logic; no durable moats are evident on the site.
Visit website↗Built by Marc Lou, who ships 32 products in this index
Not priced
No pricing page we fetched carried a figure, so there is nothing to compare against. The build side is still real.
$50one-off20 h to build
$15/mo3 h/mo upkeep
No published price to break even against.
No open-source build does this yet
Nothing published replaces this one, so a replacement starts from an empty file. Here is what it would have to cover.
What a replacement has to do
- User selects a mood → system finds and ranks movies that match that mood → shows a ranked list with metadata and links.
What it still won’t have
- Brand recognition and any proprietary curated dataset or editorial curation
- Polish of a production web UX (animations, A/B testing, large-scale reliability)
- Any commercial integrations or paid metadata/licensing the vendor might have
What remains hard
- Product polish and ongoing maintenance
First-year cost
No published price
Mood2Movie does not publish a price we could read, so there is nothing to compare against. What building costs is below.
Money you would actually spend
Time you would spend
—
What you would spend
What we assumed
The verdict above measures whether you could build it. This one is only about money.
Runnable build prompt
Build a small web app (Next.js React frontend, Node/Express or serverless API) that maps a chosen mood to movie search queries, calls the TMDB API to fetch metadata, ranks and caches results in Redis or an in-memory cache, and renders a responsive list with posters, ratings, and external links. In scope: mood selection UI, mood→query mapping (rule-based), TMDB integration, result ranking, caching, basic analytics, deployment to Vercel or similar. Out of scope: training large models, licensed studio content hosting, multi-tenant billing. Include error handling for API failures, retry/backoff, and unit/integration tests for the mapping, API client, and ranking logic.
How we checked
How the score was reached
- Build verdict base78
- Evidence score78
The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.
How scoring works →Integrity checks
What held up, and what did not.
