Analytics and monitoring decision
Starter Story
A minimal searchable database and newsletter can be built and self-hosted by one developer in ~40 hours, but Starter Story's value largely comes from its proprietary, curated dataset and editorial content which would be costly to replicate.
Visit website↗Not priced
No pricing page we fetched carried a figure, so there is nothing to compare against. The build side is still real.
$100one-off40 h to build
$25/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
- Search and filter a curated database of founder case studies, read individual interviews/case pages, and subscribe via email.
What it still won’t have
- The breadth and scale of Starter Story's live dataset (thousands of curated projects)
- Editorial interviews and deep founder episode content
- Brand trust and audience reach
- Ongoing live updates and aggregated revenue signals
What remains hard
- Proprietary data
2,996+ real, revenue-generating projects — the tools they built on, how they grew, and the full breakdown behind each one.
- Proprietary data
$3B+ /mo in combined revenue · updated live
- Proprietary data
The widest database of real founder data.
First-year cost
No published price
Starter Story 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 searchable case-study database web app using Next.js (React) + TypeScript, Postgres (hosted on Supabase), and Vercel for hosting. Core features: (1) admin CSV import and small admin UI to create/edit case study records; (2) public browse UI with category/tags filters and full-text search (use Postgres full-text or Algolia); (3) case detail pages showing tools used, revenue, costs, and timeline fields; (4) email magic-link auth and newsletter signup using SendGrid; (5) export search results to CSV. Out of scope: conducting or transcribing editorial interviews, automated revenue verification, and scaling to thousands of live-updated records. Include server-side validation, error handling, API rate limits, unit/integration tests for import and search, and deployment scripts for Vercel + Supabase. Provide README with setup, migration, and backup instructions.
How we checked
How the score was reached
- Partly verdict base52
- 3/3 assessment runs agreed+4
- Hard moats found in the evidence-3
- Evidence score53
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 →Cited sources · 1
Every page the run actually retrieved.
Integrity checks
What held up, and what did not.
