Product teams spend thousands of dollars on research that sits in slides nobody reads. Insights get lost. Decisions revert to hunches. I knew AI could bridge this gap—I just had to prove I could build it.
Over 20 product manager, designer, and researcher interviews
Next.js, Pinecone, OpenAI, MongoDB
Marketing site, content, 60-second persona creation
Beta program live, customer acquisition
Over 20 product manager, designer, and researcher interviews
Next.js, Pinecone, OpenAI, MongoDB
Marketing site, content, 60-second persona creation
Beta program live, customer acquisition
Visit the live product at rooost.co
Create a persona in under 60 seconds
Upload your research content
Natural conversation interface
Persona answers cited & linked
Building user trust through transparent quality assessment. Every persona receives a 0-100 score based on three components:
Basic persona data fields manually completed
Quality-gated research analysis with data decay
Research recency + profile maintenance
Engineered a seamless persona data transfer system from marketing site to user accounts—prospects can try before signing up, boosting conversion.
This web application is a case study in the Product Pairs methodology. Using Claude Code as my development partner, I delivered what traditionally requires a 5-person team—writing 19,000 lines of production code across product, backend, and infrastructure.
One human + AI partner = an entire product team.
The tech isn't the hard part anymore—AI makes building possible for anyone willing to learn. If you think it, you can create it. The real challenges are understanding what's worth building and cutting through market noise. When everyone can build, deep understanding of user needs and markets become the core differentiators. Breaking through the noise as a solo designer/developer to get your product noticed becomes the biggest challenge.