Glossary

Short definitions of every term used across this site, grouped the same way the Full Reference document is — structure and team design first, then flow and constraints. Click through to the full section for the complete explanation.

Structure & Team Design

Ashby’s Law of Requisite Variety A regulator can only absorb as much variety (complexity/uncertainty) as it has capacity to match; if the variety of what it’s regulating exceeds that capacity, control breaks down. Full Reference 2.1 →

Conway’s Law Organizations design systems that mirror their own communication structure — the architecture of a system reflects the architecture of the team that built it. Full Reference 2.2 →

Brooks’s Law Adding people to a late software project makes it later, because new arrivals raise coordination and communication overhead faster than they add output. Full Reference 2.3 →

The Reverse Conway Maneuver Deliberately restructuring teams to match the system architecture you want, so Conway’s Law works in your favor instead of against it. Full Reference 2.4 →

Team Topologies Skelton and Pais’ framework of four team types (stream-aligned, platform, enabling, complicated-subsystem) and three interaction modes (collaboration, X-as-a-Service, facilitating) for operationalizing the Reverse Conway Maneuver. Full Reference 2.5 →

Stream-Aligned Team A team aligned to one end-to-end flow of value — a product, a feature set, or a client engagement — able to deliver against it with minimal hand-offs to other teams. Full Reference 2.5 →

Team API Everything another team can consume from a given team without needing direct access to it: its documentation, service interfaces, release practices, and communication channels. Full Reference 2.4 →

Cognitive Load The total domain knowledge, operational responsibility, and coordination a team must hold to do its job — Ashby’s Law of Requisite Variety applied at team scale. Full Reference 2.5 →

Beer’s Viable System Model (VSM) Stafford Beer’s cybernetic model of the functions any autonomous, self-regulating organization needs in order to remain viable amid a changing environment. Full Reference Part 6 →

Flow & Constraints

Little’s Law In any stable queueing system, the average work in progress equals the arrival rate multiplied by the average time each item spends in the system (L = λW). Full Reference 8.1 →

Theory of Constraints Every system has exactly one binding constraint on its throughput at any given time; improving anywhere else doesn’t raise system output, only the Five Focusing Steps applied to the constraint itself does. Full Reference 8.2 →

WIP (Work in Progress) The amount of work actively in flight in a system at a given moment — not assigned, but genuinely being worked on or waiting between steps. Full Reference 8.5 →

The Five Focusing Steps The Theory of Constraints’ operating cycle: identify the constraint, exploit it, subordinate everything else to it, elevate it, then repeat on the next constraint. Full Reference 8.2 →

Kingman’s Formula (VUT Equation) Estimates average wait time from variability (V), utilization (U), and processing time (T); wait time rises non-linearly as utilization approaches 100%. Flow Formula Calculator →

Weinberg’s Context-Switching Numbers A practitioner heuristic estimating how much effective capacity a person loses as the number of concurrent projects they hold increases. Flow Formula Calculator →

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