Introduction
Why This Guide
How many times have you heard an executive team complain that they have no visibility into what is happening? They are surrounded by slides, dashboards, RAG statuses, and data, but still do not really know what is going on.
How many times have you heard a team complain that they are overwhelmed, that they have no sense of the real priorities, and that they are in constant swivel-chair mode "reporting" on things without much confidence that the reporting matters, or reaches the right ears?
How often have you heard people talk about the workarounds they need just to get any work done? And how they dread the moment a leader assumes context that is not really there, because they saw a status somewhere that was meant to tell the truth, but got flattened, filtered, or whitewashed on the way up?
How often have you heard people complain that there were no set definitions for things, but then when someone finally did try to set those definitions, it took the life and variety out of the thing itself? What was once variable, contextual, and real became an oversimplification to placate someone who needed a neat dashboard.
The inspiration for this short guide came from a simple observation: operations, especially in complex domains, involves information architecture and ontology creation. But it is very different from what you might do if you were doing operations management in a factory or manufacturing setting. The concepts are slippier. The flows and feedback loops are more variable. What you call things is extremely important, but also much more of an art than in more deterministic settings.
Words alone will rarely sink the ship. But they absolutely can contribute to headaches, misalignment, wasted motion, false confidence, and harmful flattening.
Who Is This For
This guide is for people working in and around product development operations, especially where the work is hard to name cleanly and harder to represent well.
It is for leaders and operators who have to decide what to call things, how to structure status, how to design planning and reporting views, and how to make complex work more legible without flattening it beyond usefulness.
That includes people in product operations, technology operations, transformation work, portfolio or planning functions, architecture, delivery leadership, platform leadership, and adjacent roles responsible for operating models, governance, coordination, or shared language.
In This Guide
In this guide, we will explore how people name work, how those names drift as they move across a system, how containers get mistaken for reality, how summaries lose context, and why so many operating problems are really problems of representation, interpretation, and scale.
Table of Contents
| Note | Key Outcome |
|---|---|
| The Unfolding | Shift from static artifacts and fixed stages toward unfolding work, feedback, and evolving representations. |
| Endurant vs. Perdurant | Get a sharper language for separating stable things from unfolding activity. |
| From Clear Flows to Complex Systems | See why the same model works cleanly in some systems and breaks in others. |
| Static vs. Dynamic Optimization | See why product work is usually a search-and-learning problem, not a solve-once problem. |
| RAG Status, Endurants, and Perdurants | Understand why status reporting feels truthful in some contexts and misleading in others. |
| Containers vs. Anchors | Learn where to look when you need reality, not just organization. |
| The Limits of Cascades | See why cascade and pyramid models are useful shorthand but weak representations of how product systems really work. |
| Métis vs. Legibility | Recognize why formal clarity and real local understanding often pull against each other. |
| Case Study: Event Storming Perdurants | See how much hidden history sits to the left of the visible ticket or initiative. |
| Theoretical SDLC vs. Real SDLC(s) | Stop mistaking one official process for the many real paths work actually takes. |
| Transformation Journey as Ontology Shifts | Notice how transformation changes the meaning of key terms, not just the workflow. |
| Coupling, Legibility, and Métis | See how different system conditions create very different coordination problems. |
| Factors Shaping Legibility and Métis | Get a practical lens for judging how much structure, judgment, and translation a system needs. |
| Will It Scale? | Spot when a model that works locally is being stretched past reality. |
| Context Is Not Just Transmitted | Understand why context often has to be generated through interaction, not just passed along. |
| AI Opportunities (and Caveats) | See where AI can genuinely help and where it can harden weak abstractions. |
| Twelve Practical Moves | Leave with concrete decisions and moves you can use right away. |
| Glossary | Keep the core language of the guide straight as you apply it in your own context. |
Keep Reading
The Unfolding