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95 lines
3.1 KiB
Markdown
95 lines
3.1 KiB
Markdown
# Cognition Lab Plan v1 (privacy-first, SSOT, CI-gated)
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Tracked in GitLab: `#2344`.
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This plan defines how LeanCTX evolves learned cognition drivers (layout/attention/budgeting) safely, reproducibly, and without compromising local-first trust.
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## 1) Goals
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- Improve *effective reasoning* via deterministic steering and learned drivers.
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- Keep production (API-LLM) behavior stable via caps, proofs, and CI gates.
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- Provide a research harness for open-weights models (optional) using the same interfaces.
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## 2) Non-goals
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- No weight modification for proprietary models.
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- No telemetry by default.
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- No “silent” behavior changes without versioning and gates.
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## 3) Existing building blocks (evidence)
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- Attention/layout primitives:
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- `rust/src/core/litm.rs`
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- `rust/src/core/neural/context_reorder.rs`
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- `rust/src/core/neural/token_optimizer.rs`
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- `rust/src/core/attention_model.rs`
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- Adaptive policies:
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- `rust/src/core/mode_predictor.rs`
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- `rust/src/core/adaptive_thresholds.rs`
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- `rust/src/core/budget_tracker.rs`
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- Verification:
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- `rust/src/core/output_verification.rs`
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- `rust/tests/scientific_verification.rs`
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## 4) Data sources & privacy (opt-in only)
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### Allowed data (local by default)
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- tool call metadata (tool name, mode, sizes, timings)
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- verification warnings counters (types + counts)
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- non-sensitive outcome signals (e.g. “tests passed”, “lint failed”) when explicitly invoked by the user/tool
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### Disallowed data (never collected)
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- file contents
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- shell stdout/stderr content
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- secrets/tokens/credentials
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### Opt-in model
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- default: **off**
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- configuration: `~/.lean-ctx/config.toml` (new section to be proposed in a follow-up ticket)
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- redaction: must run before any export (reuse existing redaction pipeline)
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## 5) Evaluation methodology (CI-gated)
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### Offline evals
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- Replayability: stable inputs → stable outputs
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- Compression quality: verification warnings must not regress
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- Token/cost impact: compare before/after with `ctx_benchmark` and `ctx_gain` metrics
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### CI gates (proposal)
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- Golden fixtures for critical transformations (ordering/layout where deterministic)
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- Regression thresholds: no increase in verifier loss score above bound for benchmark suite
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- “Safety gates”: redaction + PathJail tests must remain green
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## 6) ONNX training/calibration loop (versioned)
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- Model artifacts versioned by:
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- semantic version (major/minor/patch)
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- training dataset hash (metadata only)
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- calibration config hash
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- Storage:
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- local cache directory under `~/.lean-ctx/models/` (proposed)
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- Loading:
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- feature-flagged and bounded (never block tool execution)
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## 7) Rollout strategy
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- feature flags per driver:
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- `LEAN_CTX_NEURAL_LAYOUT=1` (example; final naming via follow-up ticket)
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- staged rollout:
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- off → opt-in local → opt-in team (team server) → default-on only after long CI evidence
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- rollback:
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- immediate disable via env/config
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- keep last-known-good model artifact
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## 8) Next subtickets (to create)
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- Telemetry opt-in + redaction contract (no content)
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- Eval suite expansion (goldens + thresholds)
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- Model artifact versioning + loader contracts
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