Joshua Mwaniki

The Invisible Ceiling. For years, the founder of CPASS built platforms for the "bottom-of-the-pyramid." But when the pandemic lockdowns hit, a brutal truth was exposed: while corporate employees had "accumulated trust" (salaries, benefits, work histories), informal workers had nothing. When the world stopped, their skills vanished because they were tied to local, fragile networks. "Work in the informal sector does not compound," the founder explains. "It doesn't turn into security or future opportunity. Most informal work offers only immediate income, which is exhausting and drains motivation. I realized the status quo wasn't just inefficient—it was a structural failure that made participation too risky for the people who needed it most."

Work as a Ladder, Not a Series of Gigs. Most investors focus on "giving people jobs." CPASS is built on the opposite conviction: The key is making work worthwhile by making it visible. To an engineer, CPASS is a high-fidelity inference engine that maps experiential work onto global qualification frameworks (ESCO, O*NET, ISCO-08) in real-time. It reconciles disconnected standards through a directed competency graph. To a stranger, it's simpler: "Millions of people know how to do their jobs but have no proof. CPASS turns what they can actually do into a credential that governments, employers, and lenders finally trust."

The Brutal Death of the Platform. The most painful moment of the residency at The Forge was a realization that required killing a live product. Initially, the team positioned CPASS as a secondary feature of their own gig platform. "At Web Summit, the market spoke. The platform was seen as incremental; CPASS was seen as structural," says the founder. "The brutal part was accepting we had to shut down a live platform with users and momentum to avoid hedging our focus. We had to stop building for the end-user and start building the infrastructure for the entire world."

The Convergence of Rights and AI. This solution would have failed five years ago. Today, it is a technical and regulatory necessity. "Five years ago, worker data was effectively owned and locked in by platforms. Today, there is a regulatory mandate for data portability." Simultaneously, the computational power required to map thousands of skills across conflicting national standards has finally arrived. What used to take months of manual mapping now happens in hours via AI-driven skill graphs, making real-time skill inference feasible at scale. Combined with a team specializing in agentic coding, they are uniquely qualified to build the "living system" of human skills.