BU72 AAI-04|BU37 × Agentic Closure Lineages From Capability Closures to Sustainable Evolution

This paper develops BU72 AAI-04|BU37 × Agentic Closure Lineages as the fourth file in the B_U-based Agentic AI series. Its central claim is that Agentic AI should not be evaluated merely by the number of agents, tools, workflows, or autonomy levels it can assemble. The decisive transition is from capability modules to sustainable closure lineages. A capable agent can run; a closure lineage can be retained, reweighted, recomposed, pruned, and evolved under real selection pressure. The paper connects BU37’s evolution classification matrix with the five core capability closures introduced in the Agentic AI series: Readout, Actuation, Constraint, Stability, and Learning. Each closure is reclassified as a small ontology with its own objects, operators, boundaries, states, residuals, verification gates, recovery modes, cost structure, and settlement conditions. These closures are therefore not simple engineering modules. They are evolutionary lineages inside an agentic closure ecology. The paper argues that large-model expansion alone cannot produce sustainable Agentic AI. A larger model may improve local readout, but it does not automatically create stable execution, valid constraints, failure recovery, cost discipline, or long-term learning. Nature provides the stronger analogy: durable evolution does not rely on a single all-purpose organism. It proceeds through differentiated closure lineages that compete, cooperate, specialize, recombine, and survive under multiple selection pressures. BU72 therefore reframes Agentic AI development as a shift from single-agent optimization to closure-lineage evolution. Readout closures evolve toward higher-fidelity evidence binding; Actuation closures evolve toward verifiable and rollback-capable action; Constraint closures evolve toward dynamic gating; Stability closures evolve toward residual recovery and failure settlement; Learning closures evolve toward gated experience compression and retained strategy updates. The final judgment is that sustainable Agentic AI will not come from building a bigger agent. It will come from an ecosystem of closure lineages operating on the same settlement surface, where each closure can specialize, combine, fail safely, update responsibly, and remain retained only when it continues to produce standing under real task, cost, risk, and verification pressure.