Rizom: Distributed Teams That Scale

Rizom Collective is a distributed consultancy founded by Yeehaa (Jan Hein Hoogstad), a writer, developer, and ecosystem architect exploring the intersection of technology, culture, and organizational design. The project emerged from years of experience building education platforms (Offcourse) and bootcamps, where Yeehaa observed that the real bottleneck in organizations wasn't talent—it was knowledge flow. The founding conviction is that traditional organizations trap knowledge in two places: key people's heads and scattered tools. This creates dependency on individuals rather than systems. Rizom represents a concrete attempt to build the alternative: infrastructure that allows distributed teams to operate like a single, adaptive organism while maintaining individual autonomy and ownership.

Traditional organizations fail to scale because knowledge gets trapped in people and tools. When domain experts are unavailable or leave, projects grind to a halt. New hires repeatedly ask the same questions, interrupting busy teammates. Important context becomes inaccessible when decisions need to be made. Coordination costs grow faster than the team. Consultancies face the inverse problem: they mobilize expertise slowly (months instead of hours), losing knowledge when engagements end, and creating coordination overhead that defeats the purpose of flexibility. The root cause is the same: poor knowledge sharing infrastructure and no systematic way to maintain specialization, credibility, and coordination across distributed teams.

Rizom operates on three integrated layers. First, a network of independent professionals with shared methodology and AI infrastructure that enables them to mobilize specialized expertise in hours instead of months. Second, AI agents (Rover, Recall, Ranger) that solve the knowledge-sharing problem at scale—maintaining specialization maps, building credibility signals, and enabling coordination across distributed teams. Third, a methodology grounded in Transactive Memory Systems (TMS), an organizational psychology framework explaining how high-performing teams actually work. TMS has three dimensions: specialization (knowledge is distributed, people know who knows what), credibility (team members trust each other's expertise), and coordination (the right knowledge reaches the right person at the right time). The infrastructure combines personal knowledge brains that evolve like Git repositories, outcome-based certification that enables trust without gatekeepers, and open standards (HTTP, MCP, ACP) that prevent platform lock-in. A franchise model with equity stakes ensures individuals own what they build within the ecosystem. Rather than treating organizations as problems to be solved, Rizom treats them as living things to be cultivated—designing for emergence, resilience, and adaptive capacity instead of control and optimization.

Rizom represents a working proof that distributed teams don't have to sacrifice excellence for flexibility. By grounding the platform in TMS principles and building AI infrastructure that handles operational overhead, the network enables outcome-based work without the usual coordination tax. The model addresses three failure patterns simultaneously: it eliminates bottlenecks by distributing knowledge, prevents knowledge loss through systematic capture and accessibility, and reduces coordination costs through AI-augmented collaboration. The deeper outcome is methodological: Rizom demonstrates that organizations built like machines eventually break down, while those designed like living systems—with conditions for emergence rather than control—become more resilient. The project continues to evolve, with the underlying conviction unchanged: we need structures that work more like living systems than machines, not because hierarchy is bad, but because our tools and contexts have outgrown what traditional organizational models can handle. This approach borrows from permaculture, biomimicry, and regenerative design, translating ecosystem architecture principles into digital infrastructure that enables professionals to think together the way humans actually think—messily, tangentially, creatively.