Getting the Words Right

Summary: A working glossary for the series. These definitions aim for practical usefulness, not false precision. Use them to stabilize the language of the guide while still leaving room for local variation. How to Use This Glossary This glossary is meant to help you read the series and reuse the ideas in your own setting. The terms here are intentionally operational. They are not trying to be the last word in formal ontology. Some of these terms are durable enough to carry across notes with roughly the same meaning. Others change shape depending on the context. When that happens, the short definition here should help orient you, and the linked note should supply the nuance. At a Glance TermShort meaning anchorA durable reference point tied closely to observable reality. containerA grouping wrapper used to organize, coordinate, or summarize work. contextThe history, situation, relationships, and interpretation needed to make sense of what is happening.

TermShort meaning couplingThe degree to which parts of the system depend on one another to move effectively. dynamic optimizationTreating the work as search, learning, and adaptation over time. endurantA relatively stable thing you can point to at a moment in time. endurant fidelityHow well your chosen durable objects match the reality of the work. eventA bounded occurrence inside a larger unfolding process. Event StormingA way of reconstructing the real history, decisions, actors, and state changes behind visible artifacts. legibilityA simplified, portable representation that makes a system easier to see and manage. métisLocal, situated practical judgment that helps people make things work in context. perdurantSomething that unfolds over time and only makes sense across a history or sequence. perdurant strategyHow you choose to model time, rhythms, and process variation. RAG statusA compressed red-amber-green signal whose usefulness depends on the quality of the model underneath it. real SDLC(s)The many actual paths work takes in practice. scale of the localHow much of the surrounding system a team must understand to act well. stateThe condition of anendurantat a point in time.

TermShort meaning static optimizationTreating the work as if the objective, constraints, and solution can be fixed early. summary containerA roll-up wrapper that compresses many realities into one signal. theoretical SDLCThe official or standard lifecycle people use to talk about work. transitionA meaningful change in state, usually best modeled as an event. Core Ontology Terms Anchor Ananchoris a kind ofenduranttied closely to observable reality. It stays close to what actually changes in the world: a team, a service, a metric, a production change, a customer segment, or another durable point of reference. Anchors are where you look when you need to understand reality rather than merely organize it. See Containers vs. Anchorsand Twelve Practical Moves. Container Acontaineris a grouping wrapper used to organize work, coordinate attention, or summarize effort.Initiatives, projects, epics, and similar wrappers often work this way. Containers are useful, but they are easy to mistake for the underlying reality, especially when their contents drift over time. See Containers vs. Anchors,Theoretical SDLC vs. Real SDLC(s), andWill It Scale?. Container-anchor misalignment Container-anchor misalignmenthappens when the wrapper says one thing and the closer-to-reality anchors say another. The initiative looks green, for example, while the service, team, or metric underneath it is clearly in trouble. See Containers vs. Anchors.

Endurant

Anendurantis something treated as wholly present whenever it exists. In this series, that usually means a durable reference point such as a team, service, release, metric, or another thing whose identity can persist while its properties change. See Endurant vs. Perdurant,From Clear Flows to Complex Systems , andTwelve Practical Moves. Event Aneventis a bounded occurrence inside a larger unfolding story. Events matter because they preserve what changed, when, and often why. When the history matters, events usually belong in the model more than a static label does. See Endurant vs. PerdurantandCase Study: Event Storming Perdurants. Missing perdurant Amissing perdurantis what happens when a model preserves the durable object but loses the unfolding story around it. You still have the item, but not the sequence, transitions, loops, and interpretation needed to understand its condition. See RAG Status, Endurants, and Perdurants. Nouns versus verbs Nouns versus verbsis a reminder that many formal nouns in organizations are really shorthand for ongoing activity. An initiative, objective, orepicoften points at a process of coordination and interpretation more than at a neat object. See Case Study: Event Storming Perdurants andTwelve Practical Moves. Perdurant Aperdurantis something that unfolds through time. It is made legible through its phases, history, transitions, and events rather than by a single snapshot. In practice, many things organizations name as if they were stable objects are better understood as perdurants: unfolding activity, coordination, negotiation, and learning over time. See Endurant vs. Perdurant,Case Study: Event Storming Perdurants, andTwelve Practical Moves .

State

Stateis the condition of anendurantat a point in time. A machine can

be running or stopped. A service can be degraded or healthy. A team

can be overloaded or stable. State helps describe the condition of the

durable thing, while the change between states is better modeled as an event. See Endurant vs. Perdurant. Summary Container Asummary containeris a higher-level roll-up wrapper that compresses many different realities into one headline signal. Portfolio status, theme status, and quarterly roll-ups often behave this way. They can help leaders navigate, but they often strip away exactly the context needed for correct interpretation. See RAG Status, Endurants, and Perdurants. Temporal parts Temporal partsare the phases or segments that make up a perdurant. They matter because they let you describe an unfolding thing in terms of before, during, after, and the meaningful pieces in between. See Endurant vs. Perdurant. Tight endurant-perdurant mapping Tight endurant-perdurant mappingmeans the stable thing being tracked lines up well with the unfolding work around it. This is one reason some operating metrics and statuses feel truthful while others feel thin or misleading. See RAG Status, Endurants, and Perdurants. Time-slice or snapshot test Thetime-sliceorsnapshot testis a practical modeling question: if you freeze time, do you still have the whole thing, or only one moment in its unfolding? If the whole thing is present, you are probably looking at an endurant. If the meaning depends on the sequence, you are probably looking at a perdurant. See Endurant vs. Perdurant. Transition Atransitionis a meaningful shift from one state to another. In this guide, transitions are important because they often preserve the real operational story better than snapshot categories alone. See Endurant vs. PerdurantandRAG Status, Endurants, and Perdurants.

Wrong endurant

Awrong endurantis a thing the organization has decided to treat as

stable even though it is too fluid, overloaded, or internally inconsistent

to bear that role well. Once that happens, reporting gets cleaner while understanding gets worse. See RAG Status, Endurants, and Perdurants andFactors Shaping Legibility and Métis. Representation and Sensemaking 4E cognition 4E cognitionis shorthand for embodied, embedded, extended, and enactive views of cognition. In this series, it matters because it supports the idea that understanding is often generated through participation, tools, rituals, and interaction, not just by reading a packet. See Context Is Not Just Transmitted andAI Opportunities (and Caveats). Action and understanding co-evolve Action and understanding co-evolvemeans people often do not fully understand first and act second. In complex settings, action changes the situation, which changes the signals, which changes the interpretation. Understanding is part of the process, not always a prerequisite to it. See Context Is Not Just Transmitted. Compensation Compensationis the extra work people do when the official model is too thin to support the work. Parallel spreadsheets, repeated explanations, side channels, and hand-built tracking are often not redundancy for its own sake. They are attempts to rebuild lost context. See Métis vs. LegibilityandTwelve Practical Moves. Context Contextis not just background information. It includes relevant history, state changes, relationships, constraints, timing, interpretation, and the interaction needed to produce shared understanding. In complex settings, context often has to be generated together rather than merely transmitted. See Context Is Not Just Transmitted,Case Study: Event Storming Perdurants, andAI Opportunities (and Caveats).

Legibility

Legibilityis the drive to make a system visible, readable, portable, measurable, and governable. Legible representations are not inherently bad. The problem begins when the simplified representation gets mistaken for the whole reality. See Métis vs. Legibility,Factors Shaping Legibility and Métis , andWill It Scale?. Legibility sufficiency test The legibility sufficiency testasks whether the artifact can stand on its own without constant translation from insiders. If a newcomer cannot make sense of it, or if the real meaning only lives in surrounding conversations, the artifact is not doing as much work as it appears to be doing. See Métis vs. Legibility. Métis Métisis local, situated practical judgment. It is the know-how people develop by working in the real setting, not just by reading the official representation of it. Métis matters most where the categories are unstable, the work is changing, and actors must interpret in motion. See Métis vs. Legibility,Coupling, Legibility, and Métis, andFactors Shaping Legibility and Métis . Multiple lenses, one system Multiple lenses, one systemrefers to the need to view the same reality differently for executives, operators, product, finance, and others without inventing separate worlds. The challenge is to support different views while staying anchored to the same underlying reality. See AI Opportunities (and Caveats). Official, real, and ideal models Theofficial modelis how the organization says things work. The real modelis how they actually work. Theideal modelis how people think they should work. Useful diagnosis often starts by comparing all three rather than pretending one of them is the whole story. See AI Opportunities (and Caveats).

Portable versus interaction-generated context

Portable contextis context you can package and move with relatively

little loss.Interaction-generated contextis understanding that only

emerges through working, talking, and interpreting together. The distinction matters because many organizations try to solve the second problem with tools built for the first. See Context Is Not Just Transmitted. Shannon-style communication Shannon-style communicationtreats communication as the transmission of a message from one party to another, with success depending on correct encoding and decoding. That model can help in stable settings, but it is too thin for situations where understanding emerges through interaction. See Context Is Not Just Transmitted. System-métis mismatch Asystem-métis mismatchappears when formal systems assume stable categories, clear boundaries, and portable meaning while the real work depends on local judgment and ongoing interpretation. Much of the friction in operating systems comes from this mismatch. See Métis vs. Legibility. Translation layers Translation layersare structures, people, or tools that help reconcile differences in vocabulary, model, or perspective across groups. They can be genuinely useful, but they can also mask unresolved disagreement if they make mismatch look more settled than it is. See AI Opportunities (and Caveats). System Conditions and Design Abstraction quality Abstraction qualityis how well the shared model compresses reality without becoming misleading. Good abstractions reduce friction while still supporting local judgment. Poor abstractions increase translation work and brittle coordination. See Coupling, Legibility, and Métis.

Command Towers

Command Towersdescribes a regime of high legibility and centrally imposed structure. It can create a strong sense of visibility, but it often suppresses local judgment and slows adaptation because so much depends on the shared model being updated from the center. See Coupling, Legibility, and Métis . Constraint strategy Constraint strategyis where and how control is applied in the system. A better strategy usually relies on fewer, more reliable anchors and decision points rather than trying to make everything equally visible and equally governed. See Factors Shaping Legibility and Métis. Coupling Couplingis the degree to which parts of a system depend on one another to move well. Higher coupling usually increases the need for better abstractions, richer context, more translation, or more local judgment. It is one of the main reasons the same operating model works well in one setting and fails in another. See Coupling, Legibility, and MétisandFactors Shaping Legibility and Métis. Coupling reality versus coupling abstraction Coupling reality versus coupling abstractionseparates dependencies that are genuinely in the work from dependencies introduced by the model, planning wrapper, or coordination structure. This distinction matters because some coordination pain is real and some of it is self-inflicted. See Factors Shaping Legibility and Métis. Endurant Fidelity Endurant fidelityis the degree to which the durable things in your model match the durable things in reality. If the wrong object becomes the official reference point, the system accumulates translation work and false confidence. See Factors Shaping Legibility and MétisandTwelve Practical Moves. Federated Islands Federated Islandsdescribes a low-legibility, high-métis environment where local groups can work effectively on their own terms but shared

understanding across the system is weak. It often feels better locally

than a locked grid, but global coordination becomes fragile. See Coupling, Legibility, and Métis . Hands-Off Gridlock Hands-Off Gridlockdescribes a system with weak shared structure and too much coordination burden crossing boundaries. No one is truly in control, but the lack of stabilizing abstractions does not create freedom so much as perpetual negotiation. See Coupling, Legibility, and Métis. Locked Grid Locked Griddescribes a system with high coupling and weak abstractions, where work is forced through rigid structures that do not match reality. It is one of the most brittle states because both legibility and métis are constrained. See Coupling, Legibility, and Métis. Loose perdurant flow Loose perdurant flowis a way of describing knowledge work without pretending it behaves like one neat left-to-right cascade. There may still be a flow, but it often looks more like interlocking threads of work, impact, possibility, and sensemaking. See Twelve Practical Moves. Perdurant Strategy Perdurant strategyis how you choose to model rhythms, cadences, histories, and variations in how work unfolds. Some systems can tolerate one dominant cadence. Others need multiple overlapping rhythms and cannot honestly be reduced to a single clean flow. See Factors Shaping Legibility and Métis,From Clear Flows to Complex Systems, andTwelve Practical Moves . Scale of the Local Thescale of the localis how much of the surrounding system a person or team must understand to act well. Sometimes the local really is small. Sometimes the local is already large, which means autonomy cannot eliminate coordination work. See Factors Shaping Legibility and Métis.

Operational Frames and Practices AI AIis treated here as a tool that can translate, summarize, connect, and support navigation across messy systems. It can help, but it can also harden bad abstractions, over-compress real variation, and create false confidence if the underlying model is weak. See AI Opportunities (and Caveats). ### Blast radius {#glossary-blast-radius} Blast radiusis the downstream effect a signal, decision, or change has across the surrounding system. In this series it helps explain why a small shift in one place can produce large invisible coordination work elsewhere. See Case Study: Event Storming Perdurants. Containment problem Thecontainment problemis what happens when organizations keep adding higher-level wrappers so work can be summarized cleanly upward. Those wrappers can improve navigability while degrading fidelity. See Will It Scale?. Dynamic optimization Dynamic optimizationis a way of framing work where the objective evolves, the constraints can be reshaped, and the solution is discovered over time rather than computed upfront. In this series it fits product work because the important endurants are often still being clarified, the perdurant is still unfolding, and learning changes the target as you go. See Static vs. Dynamic Optimization,Perdurant strategy,Constraint strategy , and Endurant fidelity. Event Storming Event Stormingis a way of reconstructing the real history of a domain by surfacing actors, events, decisions, information changes, and dependencies across time. In this series it is especially useful because it restores the relationship between visible artifacts and the richer perdurants behind them. See Case Study: Event Storming Perdurants. Fractal structures Fractal structuresare patterns that can repeat across levels without becoming meaningless, but only when they remain anchored to local reality rather than copied mechanically. The lesson is not “reuse everything,” but “reuse only what preserves fidelity across scales.” SeeWill It Scale?. Left of the ticket Left of the ticketrefers to the messy, interpretive, relational work that happens before a durable artifact appears in a tool. It matters because organizations often mistake the first visible row in a system for the beginning of the real story. See Case Study: Event Storming Perdurants. Organism, not bigger cell Organism, not bigger cellis a reminder that scaling changes the nature of the system. Larger systems develop coordination needs and properties that are not just enlarged versions of the smaller case. See Will It Scale?. Promotion versus reality Promotion versus realitynames the moment a messy evolving situation becomes a durable official artifact and then starts to be treated as the story itself. The promoted object is useful, but it is rarely the full history. See Case Study: Event Storming Perdurants. RAG status RAG statusis a red-amber-green signal used to summarize current condition. It works best when it sits on top of stable endurants, visible transitions, and intelligible perdurants. It breaks down when the tracked object is vague, the unfolding story is invisible, or the roll-up container hides conflicting realities. See RAG Status, Endurants, and Perdurants and Containers vs. Anchors. Real SDLC(s) Real SDLC(s)are the many actual paths work takes in practice. Different work varies by uncertainty, coordination load, time horizon, decision structure, risk, and value timing. That is why one official lifecycle is often too blunt to describe what is really happening. See Theoretical SDLC vs. Real SDLC(s) .

Scale

Scalein this guide is not just “more of the same.” It changes what

counts as local, what needs coordinating, what abstractions can hold,

and whether the same terms still refer to the same kind of thing. See Will It Scale?. Scaling assumption Thescaling assumptionis the belief that the same labels, structures, and flows can be stretched upward without changing kind. Much of the pain around organizational design comes from discovering that what worked locally no longer names the same reality at larger scale. See Will It Scale? . Static optimization Static optimizationis a way of framing work where the objective, constraints, and solution are treated as knowable early enough to plan around directly. It can be useful in clearer, more stable systems, but it becomes misleading when teams apply it to work whose goals, constraints, and meaning shift during execution. See Static vs. Dynamic Optimization, What to standardize, and Perdurant strategy. Theoretical SDLC Thetheoretical SDLCis the official or standard lifecycle people use to describe how work should move. It is often useful as a coordinating abstraction, but it is still a model. Problems begin when the model is treated as the whole reality. See Theoretical SDLC vs. Real SDLC(s). What to standardize What to standardizeis the practical design question that matters more than whether everything should follow one official process. The series generally favors standardizing interfaces, milestones, decision points, and risk signals more than imposing one universal path. See Theoretical SDLC vs. Real SDLC(s) .