I've been job hunting for a while. Every interview meant
2-3 hours of manual prep — researching the company,
guessing questions, writing out answers.
So I built Hiddea.
How it works
- User pastes a job listing URL
- We scrape the listing + company page with Cheerio
- Claude API analyzes everything and generates:
- Role-specific behavioral questions with STAR frameworks
- Technical questions based on the actual stack in the listing
- Company culture insights
- Personalized study plan
Tech stack
- Next.js 14 (App Router) — web + API routes
- React Native (Expo) — mobile
- PostgreSQL + Redis — database & caching
- Claude API (Sonnet) — AI engine
- Drizzle ORM — type-safe queries
The interesting part — prompt engineering
The hardest part wasn't the scraping or the UI.
It was getting Claude to generate questions that are
actually specific to the listing, not generic templates.
Key insight: you have to explicitly tell the model to
cross-reference the tech stack, seniority level, and
company size — otherwise it defaults to generic output.
What I learned
- "Anyone can do this with ChatGPT" is the most common objection → True, but most people don't. The value is the setup, not the AI.
- Scraping job listings is messier than expected → LinkedIn blocks, Indeed has paywalls, Greenhouse is clean
- Prompt caching saves ~40% on Claude API costs
What's next
- CV upload + matching against job requirements
- Mock interview mode
- Multi-language support (already have 4 languages)
Try it at hiddea.com — free, no credit card needed.
Happy to answer questions about the implementation 👇
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