Why I Built FloFactor

Tools like Cursor, Claude Code, Codex, and agentic development systems changed how I build software. Once I had a clear spec, a coherent architecture direction, and crisp implementation steps, AI could help build at a speed that would have felt impossible a short time ago.

But the speed only appeared after the judgment work was done. Before code could start, I still had to decide whether the idea mattered, what users needed, how the experience should behave, what technical trade-offs were acceptable, and what quality bar the implementation had to clear.

I found myself building a manual operating system around the AI development workflow. I would pressure-test the strategy, validate the positioning, write a product spec, shape the UX, translate that into architecture, break the work into milestones, then review the AI team's plan before letting implementation begin.

The workflow worked, but only because I was carrying the context. I was the person remembering every decision, reconciling conflicting recommendations, preserving product intent, and deciding whether the result was ready to ship.

FloFactor does not replace product judgment. It replaces the manual orchestration around that judgment. It turns product context into prioritized opportunities, product specs, technical specs, implementation plans, and review gates that AI engineering tools can execute.

The bottleneck is no longer engineering capacity. The bottleneck is turning expert product and technical judgment into something a fast AI development team can trust. That is why FloFactor exists.