This fifth installment tackles scaling: getting agents to work in parallel without falling into "merge hell". Williams starts from the premise that multi-agent orchestration comes down to balancing three interdependent dials — cost (determined by model selection), wall-clock time (determined by parallelization width), and accuracy (determined by contract quality). These factors are coupled: parallelism only improves cost efficiency at constant accuracy if the work partition is clean. Increasing width without clean contracts degrades accuracy and causes conflicts to spike.
The architectural principle is sharp: "control flow is code; judgment is models". Williams refuses to hand scheduling decisions to frontier models; deterministic scripts do the orchestrating, with models stepping in only where judgment is genuinely required. The system is organized into four specialized lanes: a Contract Desk (frontier model) that drafts contracts, a single-writer-per-partition Builder Pool (only one agent writes to a given partition), a shared Prosecution Pool with fresh contexts, and a sequential Integrator Lane.
Model-tier routing follows three principles: rail density (the denser the test coverage and deterministic checks, the lower the tier can go), the escalation ladder (on failure, regenerate by moving up a tier), and DAG float (critical-path analysis decides whether to climb the ladder or jump straight to a higher tier so as not to delay the critical path).
For wall-clock time, Williams identifies four signals that predict merge conflicts before work even starts: file scope overlap, radius in the import graph, historical co-change coupling, and namespace collisions. The width certified by this forecast typically falls between three and five agents — beyond that, collision risk cancels out the gain.
Finally, accuracy without introspection: rather than asking a model clarification questions (unreliable), cheap agents are fanned out to generate multiple interpretations of the request. Where the N agents converge, the request is demonstrably unambiguous; where they diverge, the ambiguity becomes measured and actionable. Williams closes with field practices: batching permissions pre-flight, distinguishing in-flight validators from prosecution gates, preferring work-stealing queues over static assignments, and observing a strict merge order — foundation, then shared packages, then apps.