10x100: Collaborative Sense-Making for Coordinated Transformative Action

The 2022 IPCC report delivered a stark message: humanity had less than 1,000 days to peak greenhouse gas emissions and begin the transformation toward a livable future. The scale of change required was unprecedented—vast, systemic transformations across energy, food, governance, and economy. Yet despite mounting evidence and urgency, meaningful action remained fragmented, slow, and inequitably distributed.

The coordination problem was clear: thousands of changemakers—working in policy, civil society, business, and research—were acting in silos. Insights weren't translating to action. Learning wasn't scaling. Strategic alignment across sectors remained elusive at precisely the moment when it mattered most.

The question became: How could we create a framework that bridges insight and action, enabling diverse actors to strategically align, learn together, and drive transformative interventions within tangible timeframes?

10x100 emerged as a learning-centered mission management framework designed to tackle the polycrisis through strategic alignment and peer learning in concrete 100-day cycles.

Drawing from Nordic mission-oriented innovation approaches—particularly Danish frameworks for structuring societal transformations around shared missions—10x100 invited organizations and networks to commit to "giant leaps" toward transformative outcomes. Rather than abstract goals, participants defined specific, measurable interventions aligned with broader planetary missions, tracked and refined through structured 100-day cycles.

The framework centered on a three-phase protocol:

1. Looking Outward
Acknowledge complex urgency through collaborative foresight and continuous reflection on biophysical realities and systemic interdependencies.

2. Sensing Inward
Imagine transformative interventions beyond current practice through reflective leadership, focusing on planetary outcomes rather than incremental improvements.

3. Acting Forward
Organize for systemic shifts through ecosystem alignment, peer learning, and mutual accountability.

Every 100 days, participants gathered for Mission Quarterlies—public learning events offering steady rhythm for collective sensemaking, pattern recognition, and strategic recalibration.

A core innovation was the approach to collaborative sensemaking and data pooling. Organizations participating in 10x100 would:

• Align internal goals with 10x100 missions - connecting their specific initiatives to broader transformation objectives
• Share learning data across organizational boundaries - contributing insights, blockers, and breakthroughs to a collective knowledge base
• Enable pattern recognition at scale - identifying what works, what doesn't, and why, across diverse contexts
• Support cross-learning and strategic coordination - helping initiatives in different sectors learn from each other's experiences

This required thinking through federated data governance—how could organizations share sensitive strategic information while maintaining autonomy and control over their data?

I joined 10x100 during the second 100-day cycle in a dual role: strategic consulting and hands-on product development. Working alongside a multidisciplinary team led by Caroline Paulick-Thiel (Politics for Tomorrow) and collaborating with Dark Matter Labs and the Center for Complexity at RISD, I helped design and prototype the digital infrastructure to support practitioners navigating transformative change.

What I Built: The 10x100.cc Prototype

The core challenge was: How do we create a tool that supports continuous reflection, surfaces learning, and enables coordination across diverse change initiatives—without adding burden or noise?

I designed and prototyped a mobile conversational interface that:

• Guided practitioners through the Looking Outward → Sensing Inward → Acting Forward protocol

• Used AI-powered dialogue to engage participants regularly, surfacing:

  • Key learnings and insights from their work
  • Blockers and challenges they were facing
  • Opportunities for cross-learning and strategic alignment

• Applied Generative Transfer Learning (GTL) to:

  • Identify patterns across disparate initiatives
  • Suggest policy recommendations for governments and institutions
  • Enable learnings from one context to inform solutions in another

• Explored federated data architectures for:

  • Collaborative data governance among participants
  • Privacy-preserving sharing of insights across organizations
  • Enabling collective intelligence while maintaining autonomy

The prototype was designed as a practitioner feedback tool—a companion for those working on the frontlines of transformation, helping them make sense of complexity in real time while contributing to collective learning.

We applied for Mozilla funding to develop this further. While the funding didn't materialize, the design work demonstrated a viable path for AI-assisted coordination and peer learning at scale.