Learning and careers decision
Complete Interview Prep
A single developer can build a useful, narrower interview-practice app (question generation, answer evaluation, storage) using open-source prior art; reproducing any proprietary content, polished UX, or a full production SaaS would be harder and is not covered by the minimal replacement.
Visit website↗Built by Luca Ardito, who ships 3 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.
$100one-off50 h to build
$25/mo6 h/mo upkeep
No published price to break even against.
Open-source builds that already do this
Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need - the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship. All Complete Interview Prep alternatives, with the arithmetic →
What a replacement has to do
- User requests a practice interview or question set → system generates questions via LLM → user submits answers (text) → system evaluates answers with LLM and stores results → user reviews feedback and tracks progress.
What it still won’t have
- Proprietary question banks and curated content
- Polished product UX and brand polish
- Any proprietary scoring or analytics not reproduced
- Built-in mobile apps or polished cross-device experience
- Customer support and managed hosting SLAs
What remains hard
- Product polish and ongoing maintenance
First-year cost
No published price
Complete Interview Prep 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
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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 minimal interview-prep web app using React for the frontend, Node/Express for the backend, Postgres for storage, and OpenAI-compatible LLM API for generation. In scope: user signup/login (email or OAuth), request practice interview (select role/level), generate question sets from templates, accept typed answers, call LLM to produce feedback and scores, store past sessions, and a simple progress dashboard. Out of scope: real-time video interviews, marketplace of instructors, native mobile apps, and proprietary question banks. Include error handling for API failures, rate limits, and DB errors, and provide unit and integration tests and a Docker-based deployment and CI pipeline.
How we checked
How the score was reached
- Partly verdict base52
- An open-source build was found+5
- 3 cited sources+3
- Evidence score60
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 · 3
Every page the run actually retrieved.
- official productComplete Interview Prep — product page
- open sourcesantifer/career-ops
- open sourceMadsLorentzen/ai-job-search
Integrity checks
What held up, and what did not.
