Implements the 4-phase documentation reorganization master plan. - Consolidation: Merged brief/, handoff/, planning/, and decisions/ into briefs/, handoffs/, plans/, and adr/ respectively (101 ADRs relocated) - Root Cleanup: Relocated HANDOFF-gpt55-*.md and key top-level docs (runtime_contracts.md, etc.) to canonical folders. Added superseded alerts. - Indices & Navigation: Created docs/README.md navigation document, docs/sessions/README.md index, docs/adr/README.md index - Note: Also includes prior commit adding ADR-0200+ corpus hygiene governance (ADR-0225, dependency map, backfilled cross-references)
119 lines
5.2 KiB
Markdown
119 lines
5.2 KiB
Markdown
# ADR-0017 — Agency Scope: Responsive-with-Axiology
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**Status:** Accepted
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**Date:** 2026-05-16
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**Authors:** Joshua Shay
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**Supersedes:** Open Scope Decisions row "Agency (responsive vs. goal-directed)"
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in `docs/PROGRESS.md`.
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## Context
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The capability roadmap (ADR-0016) flagged *agency* as an open scope
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decision required before Phase 3 engineering begins. Two extreme
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positions are available:
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- **Pure responsive.** The system processes one input per turn and
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produces one output. No internal aims, no autonomous initiative.
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This is what `CognitiveTurnPipeline.run(text)` is today.
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- **Pure agentic.** The system maintains internal goals, plans
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trajectories that pursue those goals across many turns, and may
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initiate actions outside of user-triggered input. Each goal-step
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can in principle invoke the system without external prompting.
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A choice between these endpoints shapes how Phase 3 reasoning-depth
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work is structured. The transitive-walk and path-recall operators
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the inference-closure lane requires can be implemented either way,
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but their semantics differ: the agentic reading makes them part of
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an internal planner that runs across turns; the responsive reading
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makes them per-turn deterministic functions invoked by the
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articulator.
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## Decision
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CORE is **responsive-with-axiology**:
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1. **Responsive turn boundary preserved.** Every cognitive turn is
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triggered by an external input: a user utterance, a CLI invocation,
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or an explicit replay command. The system never initiates a turn
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autonomously. No background agent loop runs between turns.
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2. **Axiology is first-class within the turn.** The
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`IdentityManifold` and its `ValueAxis` set are not decorative
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identity-decoration; they are the value gradient against which
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the articulator chooses among candidate articulation surfaces.
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When the proposition-graph planner produces multiple valid
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completions, the choice is the one that scores highest against
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the manifold's value axes. This is goal-directedness *within* a
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single responsive turn, not across turns.
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3. **No autonomous initiative.** The system has no `loop()` or
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`pursue(goal)` entry point. Anything that looks like long-horizon
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pursuit is a sequence of responsive turns chained by the calling
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layer, not an internal process.
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4. **Replay determinism is the load-bearing constraint.** The
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responsive-with-axiology shape is preserved partly because pure
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agentic loops break deterministic replay: the trace_hash contract
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in `core/cognition/trace.py` assumes a turn is a deterministic
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function of (input, prior-state). Adding non-input-triggered
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internal actions would put state changes between turns that
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replay cannot reconstruct.
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## Consequences
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- **Phase 3 v2 engineering shape.** The transitive-walk and path-
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recall operators (Gap 1 and Gap 2 in
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`evals/inference_closure/gaps.md`) are **per-turn deterministic
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functions**, not background processes. They are invoked
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synchronously by the articulator during a single turn. No turn-
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spanning planner is required to close the Phase 3 inference-depth
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lanes.
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- **IdentityManifold axes become load-bearing.** Today the axes are
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partially decorative (the empirical investigation in commit
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`86ef117` showed `identity_score.alignment = 1.0` universally
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because no candidate-selection step actually consults them).
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Under this ADR, the next refinement of articulator candidate
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selection should consult the axes. This is also the
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load-bearing path to making fix #3 of the adversarial-identity
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defense work geometrically.
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- **No goal-stack data structure.** CORE will not gain a
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`Goal`, `Plan`, or `Pursuit` typed object as part of Phase 3.
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Anything that looks like a multi-step goal is the user explicitly
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asking for multiple responsive turns.
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- **Self-explanation remains responsive.** The forthcoming
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`core/cognition/explain.py` module (Gap 3 in
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`evals/introspection/gaps.md`) is invoked on a turn-id; it does
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not introspect autonomously.
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- **Persona / character work is axiology-side, not agency-side.**
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`persona/motor.py` shapes articulation output within the
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responsive turn. It does not run between turns.
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## Rejected alternatives
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- **Pure responsive (no axiology).** Rejected because the
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`IdentityManifold` already exists as an architectural commitment
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(ADR-0010) and the adversarial-identity defense work explicitly
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depends on axes being able to *shape* behaviour, not just be
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measured. Pure responsive would relegate identity to read-only
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evidence, which conflicts with ADR-0010's "identity is
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inalienable" claim.
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- **Pure agentic.** Rejected because it breaks the deterministic
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replay contract. CORE's value proposition over frontier models is
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partly that any turn can be replayed bit-for-bit; an autonomous
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inter-turn process makes that contract unenforceable. Also
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rejected on philosophical grounds: agency as autonomous pursuit
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is not what CORE claims to be. CORE is a deterministic cognitive
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engine, not an autonomous agent.
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## Verification
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- Phase 3 v2 work on Gaps 1+2 is scoped as per-turn deterministic
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operators (see ADR-0018).
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- No new turn-spanning processes are introduced in Phase 3.
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- Replay determinism contracts in `tests/test_determinism_proofs.py`
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continue to pass for all multi-turn scenarios.
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