Conserved amount, negotiable placement. Prompting perturbs one architecture, an AI reviewer both

Abstract

Tesler's conservation law holds that a problem carries an irreducible amount of complexity. Brooks separates that essential part from the accidental part a solution adds. If the essential part is fixed, architecture is placement rather than quantity, and the question is which levers move placement. An AI agent implements sixty accumulating change requests on one REST endpoint under two architectures, a mutative Spring controller and an additive OfficeFloor pipeline, under five conditions, ten runs per cell, model fixed. Four are external controls, from a bare change request to the disclosed structural cost function. The fifth is different in kind. A second agent reviews each change and reasons about cohesion itself. Amount is steady. Across all ten cells the finished complexity varies by 7% to 20% over four operationalisations, and the complexity the sixty rules added by 21% to 29% within an architecture. Placement is not. Under the four external controls the plasticity ratio between the architectures is near 1 on six amount metrics (five of six intervals contain 1) against 2.7 to 10.0 on eleven placement metrics (ten of eleven above 1). The mutative architecture moves, the additive one does not, and the disclosed formula brings it to the additive arm's untouched placement. The AI reviewer is the one lever that moves the additive arm, on one family only. It consolidates the pipeline, raising change- and mass-concentration on every such metric, interval excluding zero, while leaving coupling, file count and per-node complexity untouched. The price is reported in full. Strict correctness fell in most comparisons though each rule was implemented correctly in over 99% of checkpoints, and all three outcome measures favour the concentrated codebase. The contribution is a measurable property of an architecture and its lever, not a verdict on either.