01| Someone builds a working website from a single prompt, posts the video, and a room full of development professionals concludes that AI can build a global anti-poverty platform. Those are not adjacent claims. They are not in the same building. The first is a demonstration; the second is a decade of integration work in places with bad connections, four languages on one street, and users who have been disappointed by institutions before. 02| So we split the question in two,

01| Building IkoCiti means producing a global digital infrastructure — layers of technology, a set of marketplaces, training systems, data pipelines, compliance scanning, the PI Exchange. Code, architecture, integration, security, governance. That is the object. 02| A meaningful slice of that work is genuinely absorbed by AI today. Code generation is real. Scaffolding is real. Documentation production — the part every technical team hates and skips — runs faster with AI than

01| Traditional development economics scale in a straight line. Serve more people, hire more staff, open more offices, absorb more management. Cost per person served stays flat or drifts up. That is the structural reason the sector has spent enormous sums without producing structural change: its economics fight scale instead of compounding with it. Every organization in it is punished for growing. 02| IkoCiti only works on a different curve. Each new CITI must cost a fraction

01| "AI at IkoCiti" is too vague to design against. There are two distinct populations of agents, they serve different masters, they fail differently, and conflating them produces bad decisions. 02| Platform agents run operations. They match projects with buyers, scan for compliance problems, watch project execution for anomalies, aggregate data, keep the marketplaces moving, handle intake and scheduling. Users mostly never meet them. When they work, nobody notices. When they

01| The economic case for agents is about cost. The human case is about capability, and it is the one I care about more. Every Ikosi who works with an assistant should come away more capable than they would have been alone. Not flooded with output. Not patronised. Not confidently misled. 02| Concretely, the assistant helps research and analyse a problem in the barrio or on the platform. It offers the right template for the work at hand — a project plan, a report, a proposal,

01| Agents are not a department. They are threaded through the work, and the useful question is not "where is the AI" but "what verb does it own at each point". 02| Creating a project. The assistant helps a Maveriq draft the plan, surfaces comparable projects that already ran, and runs the compliance scan that gates progress. It does not generate the project. The Maveriq does. This is the single most important boundary in the book part, and it is easy to cross by accident: a

01| Every AI capability we consider gets one question before adoption, and it is not "does it work" or "what does it save". It is: does this serve self-perpetuation or replace it? 02| If AI accelerates training without removing the human teacher, it serves. If it replaces the teacher, the loop has nothing left to replicate. If it surfaces patterns that help a Maveriq decide better, it serves. If it decides for her, it has removed the thing the platform exists to build. If it

01| It will be wrong. Not occasionally and visibly, which is manageable, but sometimes systematically and invisibly, which is not. Designing for that is the whole of governance. 02| The failure modes we plan against. Capability shortfall — agents absorb far less than designed, the curve flattens, the funding gap opens. Quality decay — output that looks fine in aggregate and contains a consistent error nobody catches without a targeted audit: a compliance scan that misses one

01| A donor gives a dollar. It passes through a headquarters, a regional office, a country office, a prime implementing partner, a sub-grantee, and finally a local organization that does the actual work. Each layer keeps a share. The officially reported overhead figure captures one layer of that. The cascade captures all of them, and it is almost never published as a single number. By the time the dollar reaches an actual activity on an actual street, a large part of it is go