Design reference · Example records, approvals, measurements, identifiers, and outcomes are illustrative unless linked to accepted project artifacts or dated validation evidence.
AI-Native Engineering OS

System 02 · Evidence, specification & decision memory

The Knowledge System

The authoritative layer that converts approved strategy into what is known, assumed, decided, and required—while preserving why the team believes it.

Status · ExplorationVersion · 0.1Audience · Product, Architecture, Engineering, QAUpdated · August 7, 2026
01

Strategy

Defines what is worth building—and why.

02

Knowledge

Defines what is known, assumed, decided, and required.

03

Execution

Turns approved knowledge into tested software and hardware.

01 · Responsibilities

Nine questions before execution begins

The Knowledge System creates an authoritative description of what must be true—and prevents agents from silently converting plausible guesses into requirements.

1What is authorized?

Approved strategy version and constraints.

2What do we know?

Verified facts and supporting evidence.

3What are we assuming?

Assumptions, confidence, and validation plans.

4What was decided?

Decision, rationale, owner, and alternatives.

5What must it do?

Functional requirements and behaviors.

6How well must it work?

Quality attributes and measurable thresholds.

7What stays stable?

APIs, protocols, data formats, and hardware contracts.

8How is correctness proven?

Acceptance criteria and validation methods.

9What changed?

Versioned deltas and downstream impact.

02 · Artifacts

A connected Knowledge Package

Small, linked artifacts replace one oversized design document and become the authoritative input contract for Execution.

ArtifactPurposeRequired content
Context MapDefines the environmentActors, systems, hardware, dependencies, boundaries
Domain ModelCreates shared languageEntities, states, rules, relationships, glossary
Evidence RegisterRecords verified informationClaim, source, date, confidence, applicability
Assumption RegisterMakes uncertainty visibleAssumption, risk, owner, validation plan, status
Decision RecordsPreserves reasoningDecision, alternatives, rationale, consequences
Requirement SetDefines required behaviorRequirement, source, priority, acceptance criteria
Quality Attribute ModelDefines operational expectationsPerformance, reliability, memory, safety, usability
Interface ContractsProtects boundariesInputs, outputs, timing, errors, ownership, compatibility
OpenSpec ChangesDefines approved incrementsProposal, specification delta, tasks, approval
Traceability MapConnects the lifecycleStrategy → requirement → design → code → test → evidence
Knowledge DeltaCaptures learningNew fact, invalidated assumption, affected artifacts
03 · Classification

Every important statement declares what kind of truth it is

Epistemic status tells agents whether a statement can authorize implementation. Plausibility is never treated as proof.

StatusMeaningMay authorize implementation?
ObservedDirectly measured or reproducedYes, within stated conditions
VerifiedConfirmed through trusted evidenceYes
DecidedChosen by an authorized ownerYes
RequiredMandated by an approved sourceYes
AssumedBelieved but not yet validatedOnly when risk is accepted
ProposedSuggested but not approvedNo
UnknownInformation is missingNo, if correctness is affected
SupersededReplaced by a newer artifactNo

Common metadata

Minimum knowledge contract

Any claim that can affect implementation must expose its source, status, owner, authority, freshness, and validation path.

  • Identity, version, and approval state
  • Strategy lineage and applicability
  • Knowledge status, confidence, and risk
  • Acceptance criteria and validation method
  • Dependencies, evidence, and review history
artifact_id: REQ-LIFECYCLE-003
artifact_type: requirement
title: Resume restores paused state
version: 0.4
status: approved
owner: gameplay-system-owner
source_strategy: STRAT-RP2350-001@0.3
knowledge_status: required
confidence: high
risk_level: medium
dependencies: [ADR-007, IFACE-INPUT-002]
acceptance_criteria:
  - Restore within one rendered frame
  - No simulation time elapses while paused
validation_method:
  - automated-state-test
  - hardware-in-the-loop-test
04 · Lifecycle

Approved knowledge remains challengeable

Measurements and implementation discoveries can reveal that an assumption is false or a requirement is infeasible. They trigger controlled change; they never silently rewrite truth.

Captured
Classified
Proposed
Reviewed
Approved
Active
Challenged
Revalidated

Controlled learning loop: Revalidated knowledge returns to Active or becomes Superseded, with downstream impact recorded.

05 · OpenSpec

The change-control engine inside Knowledge

OpenSpec manages the path from investigation to approved, executable knowledge. Apply is the controlled bridge into Execution.

01

Explore

Investigate the system, identify unknowns, and gather evidence without authorizing implementation.

02

Propose

Describe the change, specification delta, platform consequences, and acceptance criteria.

03

Refine

Resolve ambiguity, validate feasibility, and separate platform from game behavior.

04

Approve

Humans authorize a specific knowledge package and version.

05

Apply

Convert approved knowledge into bounded work packages linked to implementation evidence.

06 · Validation

Evidence must match the claim

Authority comes from appropriate, repeatable evidence—not documentation volume.

Claim typePreferred evidence
Hardware capabilityDatasheet plus target-board measurement
Timing or performanceRepeatable benchmark on target hardware
User experiencePrototype review or user observation
API behaviorInterface contract and automated contract test
Architectural decisionDecision record and impacted-system review
Safety constraintAuthoritative source and qualified human approval
Game ruleApproved design specification and behavior test
AI recommendationIndependent verification appropriate to risk
For RP2350 development, target hardware outranks simulation and desktop-only results whenever they conflict.
07 · Quality

Requirements that agents can execute safely

Good requirements are atomic, testable, bounded, traceable, owned, versioned, implementation-neutral where possible, and explicit about timing and edge cases.

Quality rules

  • One observable obligation per requirement
  • Explicit pass/fail criteria
  • Scope and operating conditions stated
  • Link to an approved strategic source
  • Owner accountable for correctness
  • Version history preserved
  • Errors, timing, and edge cases included

From intent to measurable behavior

Weak

“Pause should feel immediate.”

Stronger

After valid pause input during Running, enter Paused before the next simulation update and render the paused presentation within one display frame.

08 · Governance

Humans own meaning, risk, and boundaries

AI can draft, classify, compare, and challenge knowledge. It cannot grant authority to its own output.

Human authority

Product OwnerUser behavior, priorities, and acceptance.
Chief ArchitectArchitectural coherence and technical constraints.
Engine StewardPlatform boundaries and interface stability.
Engineering LeadsGameplay, embedded, QA, and asset-pipeline truth.

AI-enabled work

ChatGPTExplore, structure knowledge, expose contradictions.
OpenSpecManage proposed and approved specification changes.
CodexMaintain traceability and coordinate approved execution.
AgentsConsume approved knowledge; report conflicts and discoveries.

Authorization checkpoint

Knowledge Gate

Execution remains blocked until the package is clear, measurable, traceable, reviewable, and safe to convert into bounded work.

Approved strategy version referenced

Affected product and platform capabilities identified

Requirements atomic, clear, and testable

Critical interfaces explicitly contracted

Quality thresholds measurable

Assumptions validated or consciously accepted

Blocking unknowns resolved

Platform impact reviewed by Engine Steward

Acceptance criteria and validation methods defined

Human approvals reference identical artifact versions

gate: knowledge-approval
decision: approved
authorized_next_stage: openspec-apply
change: CHANGE-GAME-LIFECYCLE-001@0.4
strategy_source: STRAT-RP2350-001@0.3
conditions:
  - verify frame timing on target board
  - capture 100 pause/resume cycles
accepted_risks:
  - audio resume latency not optimized
approved_by:
  - product-owner
  - chief-architect
  - engine-steward
09 · Reference case

RP2350 start, pause & resume

A concrete Knowledge Package defines the state model, valid transitions, pause/resume contracts, and evidence required before lifecycle behavior becomes platform truth.

Booting
Ready
Running
Paused
Game Over
Fault
Current stateEventResult
ReadyStartRunning
RunningPausePaused
PausedResumeRunning
RunningEnd conditionGame Over
Game OverRestartRunning
Any active stateUnrecoverable errorFault

Every unspecified transition is rejected and logged.

Pause contract

  • Simulation time stops
  • Entity, score, and streak remain unchanged
  • Input is limited to permitted paused actions
  • Pause overlay appears
  • Audio follows the approved state policy
  • Rendering may continue without gameplay advance

Resume contract

  • Prior gameplay state is restored
  • Paused duration does not affect simulation timers
  • No input event is duplicated
  • RNG continuity is preserved when required
  • Audio resumes by defined policy
  • Update begins at the captured simulation boundary

Required evidence

  • Automated state-transition tests
  • Invalid-transition tests
  • Deterministic state comparison
  • Target-board frame timing
  • 100 pause/resume cycles
  • Input and audio stability observations
10 · Repository

Git as the source of knowledge truth

Durable specifications remain separate from generated validation output, while immutable references preserve full traceability.

Knowledge lives with the system

Specifications, decisions, assumptions, and interface contracts are versioned beside the software they govern.

Generated output belongs under validation/evidence/; the Knowledge System retains immutable references to the applicable evidence and specification version.

Next design step: define the common knowledge schema and classification policy.
knowledge/
├── context/
│   ├── system-context.md
│   └── hardware-context.md
├── domain/
│   ├── glossary.md
│   └── state-models/
├── evidence/
│   └── evidence-register.yaml
├── assumptions/
│   └── assumption-register.yaml
├── decisions/adr/
├── requirements/
│   ├── product/
│   ├── platform/
│   └── quality/
├── interfaces/
├── openspec/
│   ├── changes/
│   └── approved/
├── traceability/
│   └── traceability-map.yaml
└── learning/
    └── knowledge-deltas/