“Built for speed and freshness - no stale jobs, ever. Real-time alerts ensure users apply first, not last”
Job seekers waste valuable time on repetitive, manual searches across platforms
Loading metrics...
Build a better job board with cleaner UX and modern design.
User interviews revealed the real problem wasn't the interface - it was the data. Job seekers checked multiple sites daily because no single source was comprehensive or fresh enough.
Instead of competing on UX, compete on data quality and freshness. Build a data-first product that serves multiple user segments.
Constraints and decisions that shaped product
Instead of: Build a polished consumer app first to attract end users
Instead of: Maximize company coverage before optimizing for speed
Instead of: Build a full web application with search and filtering
Key technical choices and the reasoning behind them
Aligning stakeholders with competing priorities
Overwhelmed by existing options
"I've tried everything. They all show the same outdated jobs. Why is this different?"
Built transparent live dashboard showing real platform metrics. Users can see actual job counts and data freshness.
Platform provides comprehensive coverage across 3,700+ companies that users can verify themselves.
Frustrated by lack of specialized role coverage
"Established Job Boards don't surface the roles I'm looking for."
Integrated with public pages that companies use, capturing roles before they hit major boards.
Product captures specialized roles from companies that primarily hire through their ATS.
Difficulty filtering for true remote positions
"I waste time on jobs that say remote but are actually hybrid or specific locations."
Built remote job filtering with location parsing to distinguish true remote from hybrid positions.
Users can filter by remote-friendly positions across all integrated companies.
Aggregated jobs from 3,700+ company career pages, delivering opportunities to users before they appear on major boards. The platform handles the monitoring so job seekers can focus on applying.
Quantified impact of the transformation
A failure that taught me more than success
Month 3: Data quality dropped significantly for major employers. Users reported seeing outdated jobs.
Prioritized coverage expansion over monitoring. Didn't have alerting for data freshness issues until users complained.
Lost 3 early adopter users permanently. Trust is hard to rebuild once broken.
Implemented proactive quality monitoring with automatic alerts when freshness drops. Added user-facing "data health" indicator so users could see quality status. Reached out personally to churned users with improvement roadmap.
Product quality is a feature. Users will forgive missing features, but not broken promises. Build monitoring before you need it.
Building scalable systems from the ground up
Adding new company coverage was slow, limiting ability to respond to user requests
Created a standardized architecture to identify companies actively hiring
User-driven prioritization meant focus on companies that mattered most to users, not arbitrary lists.
Grew from 100 to 2,500+ companies in 4 months. User satisfaction increased as they saw their requests implemented.
Reflection on what could have been done differently
Impact: Built features users didn't prioritize (advanced filters) before features they needed (email alerts)
Continuous user interviews from day 1, even with a small user base
Would have shipped email alerts 6 weeks earlier
Impact: Delayed public launch waiting for "complete" coverage
Launch with top 100 companies, validate, then expand
Would have gotten market feedback 4 months earlier
Data-driven product decisions
Every product decision is informed by real user behavior data. The live analytics dashboard shows actual user interactions, helping prioritize features based on what users actually do - not what they say they want. This data-driven approach led to removing the 6-hour filter (low value despite usage), prioritizing location-based search (high engagement), and focusing on application flow optimization.
Compete on what matters most to users. For job seekers, it was data freshness, not UI polish.
Trust is earned through transparency. Showing data quality metrics increased user confidence.
User requests are gold. Best features came from listening to early adopter feedback.
Interested in how I can help your team ship faster? I'd love to hear what you're working on.