The writing is not a general content collection. Each piece is a specific argument made to a specific audience inside the sector: organizational leaders, funders, finance staff, movement technologists. Together they build the case for AI built for the movement, not the market — and each one is written from inside the operational seat it is arguing about.
Each piece was written for a specific audience inside the sector. Together they make the case that social justice organizations have both the permission and the obligation to build intelligence infrastructure that serves their values.
Written for organizational leaders. What corporate America extracts, movement organizations can reclaim. The case for treating organizational knowledge as legacy infrastructure rather than a byproduct of daily operations.
Read on LinkedIn → ArticleWritten for funders and movement technologists. A framework for thinking about coordinated intelligence across organizations that need to move together without losing their autonomy, where movement technology, AI, and social justice organizing intersect.
Read on LinkedIn → ArticleWritten for movement technologists and organizational leaders. Why movements need to own their AI infrastructure rather than rent it from platforms that extract organizational knowledge as a condition of access. The data sovereignty argument, made plainly.
Read on LinkedIn → ArticleWritten for organizational leaders and the finance staff already carrying more strategic intelligence than the leadership structure credits. Vanguard culture concentrates that intelligence in one person and creates a permanent ceiling on what the organization can know. AI can democratize strategic participation when it is built for that purpose.
Read on LinkedIn →Quick thinking on AI adoption, movement technology, and what it means to build tools that serve the people doing the work.
On the real fear underneath AI adoption conversations and what it means for how we introduce these tools in movement organizations.
Read on LinkedIn → PostCutting through the hype to describe what AI tools are doing in practice inside organizations and what that means for the sector.
Read on LinkedIn → PostOn working at the intersection of movement values and technology infrastructure. The personal framing behind the practice.
Read on LinkedIn → PostThe finance coordinator, the ops manager, the development support person. The people closest to the data are the ones most equipped to work with AI tools built around that data.
Read on LinkedIn → PostOn the danger of adopting AI tools that extract organizational knowledge and return generic outputs. What movement-aligned adoption looks like instead.
Read on LinkedIn → PostOn the cost of technological stagnation in the sector and why social justice organizations cannot afford to cede the AI landscape to corporate tools built on incompatible values.
Read on LinkedIn →The framework behind everything. Covers knowledge as legacy rather than extraction, the turnover tax on movement work, why data sovereignty is a structural constraint and not a policy preference, and what it means for AI to serve collective liberation rather than corporate efficiency. The philosophy is not separate from the tools. It is the reason the tools were built the way they were. See the tools that follow from it.
A movement-aligned approach to institutional memory and collective intelligence. The foundational text for understanding why data sovereignty is non-negotiable and how AI can preserve rather than extract organizational knowledge.