Pipeline Architecture & Asymmetric Cost

Primes about how staged processing systems allocate cost unevenly across their pipeline: architectural splits for cheap versus expensive paths (fast-path/slow-path, two-store architecture, batch processing), and structural cost asymmetries that undermine naive optimization (Jevons paradox, last mile delivery, switching cost).

19 primes in this family — primes that sit near one another in abstraction space (k-means over structural-signature embeddings). Each is shown with its short description.

• Asymmetric Attack Defense Cost — On a shared channel, the cost ratio between producing harm and producing correction determines whether defense is sustainable by effort or requires structural redesign.
• Asymmetric Interface Tolerance — At any interface, each side's strictness in enforcing the spec is an independent design parameter, and the four combinations produce qualitatively different long-term equilibria.
• Asymmetric Screening — A cheap, deliberately one-sided-error filter gates an expensive authoritative check.
• Batch Processing — Collect many discrete work-items so a costly setup is paid once and amortised over the group, trading lower per-item cost for higher per-item latency.
• Brandolini's Law — Producing a corruptive claim is structurally cheaper than correcting it, so open channels saturate with uncorrected error.
• Community-Distributed Adversarial Learning — A sharing adversary community out-learns a slow-updating rule system because discovery cost amortizes across many opponents.
• Coordination-Overhead Inversion — A support scaffold recursively reproduces its own coordination demand until the supporting layer consumes more capacity than the activity it was meant to support.
• Fast-Path / Slow-Path Architecture — Handle the common case cheaply and escalate the exceptional case to an expensive path via a trigger.
• Jevons Paradox — Improving the efficiency with which a resource is used lowers the effective price of its output, expands demand, and can raise total resource consumption rather than lower it.
• Last Mile Delivery — The final segment from a consolidated trunk to heterogeneous individual endpoints costs disproportionately, and its share of total cost grows as upstream efficiency improves.
• Optimal Stopping Rule — A rule maps a sequence of observations to a halt decision, trading the cost of stopping too early against stopping too late.
• Pipeline — Sequential processing stages.
• Premature Optimization — Committing local refinement effort before global structure is known pays both search-cost and rigidity-cost without the information to spend either well.
• Return Path — Every forward-flow pipeline serving goal-directed users requires a separately-designed backward channel whose optimisation criteria invert the forward channel's.
• Rhetorical Velocity — Compose an artefact in anticipation of how others will cut, remix, and forward its fragments.
• Serial Local Optimization Failure — Stages arranged in series each optimize a local objective while treating their effects on other stages as outside that objective, so individually rational choices compound into an outcome worse than joint optimization.
• Stovepipe System — Capabilities built as parallel vertical stacks that each re-implement shared concerns, with no horizontal layer between them, are locally efficient but globally incoherent and pay a super-linear integration tax.
• Switching Cost — Moving between stateful modes incurs a per-transition overhead — unload, load, cold-start, residual interference — that is structurally distinct from steady-state cost and dominates under frequent switching.
• Two-Store Architecture — A fast interference-prone store and a slow integrated store coupled by a periodic transfer mechanism, paying for both speed and integration by maintaining two oppositely-optimised substrates.