Built a full-stack job portal aggregating government, private, IT, and other sector jobs. Developed the platform with Next.js 14 and Supabase PostgreSQL, including Google OAuth authentication. Created a Python web scraper using BeautifulSoup and Requests to collect job listings automatically, with daily execution through GitHub Actions. Deployed on Vercel with GitHub CI/CD and implemented responsive UI and SEO optimization.

The scraper is the part most people underestimate on a job board. Listings move, sites change markup, and half your value is freshness. Honestly just curious how you're handling rescrapes -- full sweep on a schedule, or diffing against what's already in Postgres? I've built...

“Duolingo does it” is one of the easiest ways to make a weak product decision sound researched. Someone suggests a feature. Someone else points to Duolingo. Now the idea feels validated. I saw this happen during a product review. The reference gave us a useful example of how an interaction could work. The visible feature was only the surface. Behind it were assumptions about the audience, the behavior being encouraged, how often someone uses the product, and what the product is trying to teach. Those assumptions belonged to Duolingo. Copying the feature would have brought them into a completely different product without anyone discussing whether they fit. In that review, we kept Duolingo as the reference and went back to our own users before deciding what to build.