Endurance Design

Principles #

Endurance cares about systems – so humans can too. Amplify human intelligence, not replace it.

1. Safety first design – grounded in complex adaptive systems theory (R. Cook)
2. Cognitive scaffolding – supporting cumulative culture and psychological safety
3. Value flow (UX) – centered on relevance realization (J. Vervaeke)
4. Autonomy – promise-theoretic approach (M. Burgess)
5. Surprise minimization under constraints
6. Learning organization
   • Building a theory about hierarchical objects with explanatory capacity
   • Making abstract things sensible

Economic perspective #

We frame our goal for platform design in terms of scope economy, where competitive advantage and economic value are derived from joint production across product engineering teams.

Cognitive scaffolding for teams enables cooperation by maintaining shared causal models and explicit expectations — providing structured support that offloads cognitive effort and reduces the cost of delays.

This knowledge flow facilitates optimal decision-making among trusted agents — both human and AI — while enhancing the capacity for market adaptation.

⦿ Strategic perspective #

Platform design should provide capabilities that help execute business (what) / product (how) activities in a measurable and repeatable way.

This approach mirrors the verification – validation cycle: ensuring that we are building the right capabilities (validation), and that we are building them correctly (verification).

To support execution with confidence, we do capability design for [Flow] — figuring out the best possible configuration where autonomous decision-making is possible.

[Activity] is a special arrangement of states – a special configuration – of relevant events that happen. [Capability] provides conditions in which relevant events happen and has the power to maintain activity over time.

With the right capability design, we identify high-relevance and low-cost future states with low friction and high precision — leading us to the best possible outcomes.

Here, our approach to platform design is fully compatible with the DORA+SPACE framework. We should have the ability to measure performance — such as software delivery and reliability — and validate our capabilities against target outcomes like organizational performance and individual well-being.

But considering our defined principles, we aim to design a platform with a tighter and more explicit verification-validation loop, where cognitive scaffolding and knowledge flow take advantage of joint context. For that purpose, in every cycle we ask the question:

What are we model for? Fit to the model. Adapt

And our platform should help human+AI agents make sense of what is going on and what to do next.

Composable design #

To effectively achieve the design targets for Flow, the platform should implement four independent components that are capable of providing conditions for information propagation — aligning perception, context, and action.

• Observability
• Decision
• Inference
• Assist

Conceptual mapping #

+-------------------------------------------------------------+
|                       Endurance Platform                    |
+-------------------------------------------------------------+
|                                                             |
|  +-------------------+       +-------------------+          |
|  |   Economy         |       |   Cumulative      |          |
|  |   -> Balancing    |       |   Culture         |          |
|  |   Complexity      |       |                   |          |
|  +-------------------+       +-------------------+          |
|           |                           ^                     |
|           v                           |                     |
|  +-------------------+       +-------------------+          |
|  |   Knowledge Flow  |       |   Cognitive       |          |
|  |   (Shared Causal  |       |   Scaffolding     |          |
|  |   Models)         |       |   (Above/Below    |          |
|  +-------------------+       |   the Line)       |          |
|           |                           |                     |
|           v                           |                     |
|  +-------------------+       +-------------------+          |
|  |   Observability   |       |   Developer       |          |
|  |   (Contextual     |       |   Experience      |          |
|  |   Clarity)        |       |   (Relevance      |          |
|  +-------------------+       |   Realization)    |          |
|           |                           |                     |
|           v                           |                     |
|  +-------------------+       +-------------------+          |
|  |   Decision-Making |       |   Coordination    |          |
|  |  Under Uncertainty|       |   (Promise Theory)|          |
|  +-------------------+       +-------------------+          |
|           |                           |                     |
|           v                           |                     |
|  +-------------------+       +-------------------+          |
|  |   Execution Engine|       |   Validation      |          |
|  |   (Flow Support)  |       |   & Verification  |          |
|  +-------------------+       +-------------------+          |
|                                                             |
+-------------------------------------------------------------+
    

Concept breakdown: #