Cooked Career

Cooked Career started as a lightweight product to help Computer Science students and professionals struggling to get their first or next job. Through early research and community conversations, we learned that the CS job market felt “cooked”: highly competitive, opaque, and frustrating for job seekers. 

Rather than guessing the solution, we treated this as a problem-validation exercise: could the product resonate strongly enough to drive adoption and revenue with the right positioning and distribution?

I adopted a distribution-first strategy, using real-time user feedback to shape both the product and its roadmap.

• Initially tested LinkedIn, X, and email as distribution channels, but none gained meaningful traction

• Learned quickly and kept tight feedback loops, turning a typical 2-week sprint into 1-week rapid cycles

• Launched posts in Reddit communities where CS students and professionals were most active

• Posts blew up, many became #1 post of the week in the community

• Engaged directly with users through over 100 DMs to understand their challenges

We turned real user feedback into high-impact features, iterating weekly and continuously optimizing the funnel in real-time:

• “Can I see your resume? Can I copy your resume?” → Resume Library: Built a curated library of job-winning resumes for users to browse and learn from

• “Can you review my resume?” → FAANG Resume Review + ATS Optimizer: Hired a former FAANG recruiter to provide expert reviews. Added automatic ATS optimization to improve users’ chances of passing applicant tracking systems

• “I have to share my resume for others to review” → Anonymizer Feature. Enabled users to share resumes safely and anonymously, removing friction for collaboration

This approach let us validate the problem quickly, ship high-value features, and grow revenue faster than traditional development cycles, all while keeping user feedback tightly integrated into every product decision.

Generated revenue within 48 hours with zero ad spend

• Launched posts in Reddit communities where CS students and professionals were most active

• Zero ad spent, generate viral content on Reddit, receiving 4K+ upvotes and 1.5M+ impressions

• Acquired 522 users in the first 48 hours, scaling to 1.1K users in the first month

• Shipped 5 product releases in the first month

• Optimized website and funnel messaging in real-time: Visit → signup +30%; Signup → trial +15%; Paid conversion 12%
  
  

• Distribution comes before product, getting in front of users is more valuable than polishing features.

• Validate demand early and at scale, fast feedback loops teach you what matters; there’s little point in building a perfect product no one will use.

• AI accelerates iteration, tools like Cursor, Claude Code, Lovable, Vercel, and Supabase let you prototype, ship, and iterate much faster, compressing learning cycles.