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Alwin Mark
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Mechanic: Added more mechanics so we have mostly problem/usecase/mechanic-fit
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doc/02_language/glossary.md

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- or mechanics
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---
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## Learning Signal
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A Learning Signal is an explicit, observable outcome
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that reduces uncertainty and informs a decision.
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In Protopipe, a learning signal:
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- is tied to a hypothesis or experiment
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- is measurable or at least falsifiable
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- influences a decision or next step
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Activity, delivery, or effort alone
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do not constitute a learning signal.
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---
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## Business Ownership
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Business Ownership describes responsibility
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for hypotheses, experiments, and learning outcomes.
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In Protopipe, business ownership means:
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- defining the learning intent
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- owning the interpretation of results
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- being accountable for decisions based on learning
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Business ownership is independent of technical implementation
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and is typically held by:
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- stakeholders
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- product owners
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- product managers
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Ownership cannot be delegated without responsibility.
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---
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## Explicit Shared Meaning
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Explicit Shared Meaning refers to information
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that is intentionally expressed, referenceable,
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and understood consistently across roles.
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In Protopipe, shared meaning is:
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- written down
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- canonical or explicitly versioned
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- used as a reference instead of verbal alignment
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Meaning that exists only in conversations,
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presentations, or individual interpretation
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is considered implicit and non-canonical.
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---
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## Coordination
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Coordination is the act of aligning work,
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decisions, or responsibilities across people or teams.
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In Protopipe, coordination is considered a cost,
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not a goal.
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Coordination is only valid
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when it is based on explicit shared meaning.
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Implicit alignment increases coordination overhead
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and is treated as structural risk.
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---
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## Attribution Context
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Attribution Context is the minimal set of information
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required to relate signals to intent and outcome.
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In Protopipe, attribution context includes:
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- experiment context
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- process context
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- user context
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Attribution context must be attached
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at the point where events or telemetry are emitted
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and propagated unchanged downstream.
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Signals without attribution context
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cannot be evaluated meaningfully.
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---
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## Experiment Evaluation
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Experiment Evaluation is the act of interpreting
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experiment results to inform a decision.
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In Protopipe, experiment evaluation:
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- depends on complete attribution context
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- focuses on learning, not success or failure
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- results in a decision, continuation, or discard
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Evaluation is distinct from reporting or visualization.
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An experiment without evaluation is incomplete.
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## Protopipe Portfolio (ProtoPortfolio)
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- clear Definition of Done at merge time
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- reproducible experiment results
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---
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## Reverse Feedback Loop
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The Reverse Feedback Loop describes the inversion
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of the classic **Build–Measure–Learn** cycle
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during planning and decision-making.
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While execution follows:
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Build → Measure → Learn
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planning follows the reverse direction:
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Learn → Measure → Build
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---
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In the Reverse Feedback Loop, work does not start from features
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or solutions, but from learning intent.
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Decisions are planned by defining:
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- what needs to be learned
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- how learning will be measured
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- what must be built to generate that learning
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The concept originates from **Lean Startup**
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and is used in Protopipe
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to enforce learning-first planning
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and prevent solution-driven execution.
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## Atomic Design (Reference Model)
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# Mechanic: No Experiment without Explicit Testgroup Assignment
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## Intent
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Prevent implicit exposure and unverifiable experiments
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by enforcing explicit user group assignment.
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---
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## Problems Addressed
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- Decisions Without Feedback
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- Learning Is Optional
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- Feature Pressure Over Innovation
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---
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## Use-Cases Enabled
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- CPO validates outcomes during delivery
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- Teams run interpretable experiments
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- Management reasons about causality
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---
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## Enforced Behavior
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This mechanic enforces that:
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- every experiment defines explicit test groups
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- group assignment is intentional and visible
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- assignment may be randomized or equalized
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- experiments without assignment are invalid
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If no explicit assignment exists,
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the experiment must not run.
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---
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## Structural Constraints
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- “silent rollout” experiments are forbidden
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- attribution without grouping is impossible
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- learning requires deliberate exposure design
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---
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## Mechanic Boundary
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This mechanic:
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- enforces explicit exposure semantics
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This mechanic does **not**:
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- prescribe assignment techniques
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- define persistence or tracking mechanisms
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---
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## Failure Modes
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- experiments rely on implicit traffic splitting
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- assignment exists but is not enforced
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- groups are defined but not respected
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# Mechanic: No Backend-Controlled Client State without Domain-Owned State
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## Intent
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Prevent hidden coupling and opaque behavior
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by enforcing explicit ownership of client-related state.
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---
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## Problems Addressed
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- High Coupling, Low Fault Locality
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- Untestable Architecture
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- Implicit Knowledge and Fragmented Contexts
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---
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## Use-Cases Enabled
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- Teams reason about client behavior deterministically
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- Failures are attributable and reproducible
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- State becomes inspectable and auditable
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---
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## Enforced Behavior
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This mechanic enforces that:
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- backend systems must not control client state implicitly
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- client-relevant state must belong to an explicit domain object
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- state transitions are observable and owned
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Backend-controlled implicit state is forbidden.
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---
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## Structural Constraints
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- convenience-based state hacks are prevented
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- hidden behavioral coupling is removed
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- debugging shifts from inference to inspection
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---
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## Mechanic Boundary
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This mechanic:
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- governs ownership of client-relevant state
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This mechanic does **not**:
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- define storage technology
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- mandate frontend architecture
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---
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## Failure Modes
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- state is hidden in transport or infrastructure layers
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- ownership is unclear
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- behavior depends on invisible state
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# Mechanic: Polling over Push Sockets
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## Intent
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Avoid hidden coupling and scaling complexity
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by enforcing pull-based state synchronization.
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---
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## Problems Addressed
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- High Coupling, Low Fault Locality
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- Untestable Architecture
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- Integration Layer Lock-In
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---
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## Use-Cases Enabled
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- Systems scale predictably
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- Failure modes are observable
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- Clients remain loosely coupled
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---
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## Enforced Behavior
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This mechanic enforces that:
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- clients retrieve state via polling
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- push-based socket communication is not the default
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- synchronization remains explicit and observable
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Push-based coupling requires explicit justification.
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---
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## Structural Constraints
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- real-time convenience is traded for robustness
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- implicit server-to-client coupling is avoided
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---
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## Mechanic Boundary
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This mechanic:
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- governs default synchronization semantics
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This mechanic does **not**:
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- forbid push communication categorically
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- define polling intervals or protocols
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---
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## Failure Modes
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- push channels reintroduced implicitly
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- polling treated as implementation detail
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# Mechanic: Explicit Exit Events over Implicit Process Transitions
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## Intent
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Increase testability and observability
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by making process boundaries explicit.
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---
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## Problems Addressed
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- Untestable Architecture
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- Analysis as a Side Effect
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- High Coupling, Low Fault Locality
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---
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## Use-Cases Enabled
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- Synthetic process testing
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- Deterministic failure analysis
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- Explicit quality gates
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---
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## Enforced Behavior
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This mechanic enforces that:
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- every process transition has explicit exit events
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- success and failure paths are modeled
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- implicit transitions are forbidden
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A transition without an exit event is invalid.
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---
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## Structural Constraints
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- process modeling effort increases
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- implicit control flow is eliminated
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---
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## Mechanic Boundary
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This mechanic:
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- governs process boundary semantics
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This mechanic does **not**:
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- prescribe process granularity
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- define event payload structure
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---
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## Failure Modes
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- exit events exist but are ignored
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- failure paths are modeled but not handled
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