> The user’s working memory must belong to the user — not to any assistant interface, vendor, or opaque system.
`cya` must never become a memory silo. All memory, history, preferences, and adaptation behavior must flow through explicit, inspectable ports provided by `phase-memory`.
## Relationship to phase-memory
`phase-memory` is the **profile-driven memory operating layer** for the broader ecosystem. It is responsible for:
- Interpreting **Markitect memory profiles** as executable runtime plans.
- Modeling memory in distinct **phases**:
-`ephemeral` — short-lived, high-turnover (e.g., current conversation window)
-`fluid` — recent but still malleable context
-`stabilized` — reviewed and relatively durable knowledge/preferences
- Planning and executing (or dry-running) **lifecycle actions**:
- Retention
- Refresh
- Compaction
- Stabilization
- Activation (under token/item budgets)
- Policy, audit, and review gates around memory changes.
`cya` is a **consumer** of this layer. It does **not** own memory semantics, storage, or lifecycle policy.
## How cya Will Use Memory
`cya` will treat memory as a first-class, explainable input to every assistance cycle, while keeping ownership and control firmly with the user (via phase-memory).
- **Source Provenance** — metadata about where knowledge came from (files, git history, previous sessions)
### Integration Model (Building on T05 Ports)
The four explicit ports defined in T05 (`cya/memory/__init__.py`) are the permanent integration surface:
-`remember_preference(key, value, scope)`
-`recall_preferences(scope, task_class)`
-`forget(scope, keys)`
-`export_memory(scope)`
Over time these will be wired to real `phase-memory` capabilities. `cya` will additionally:
1.**Produce structured memory events** (conversation turns, accepted suggestions, explicit user feedback, safety decisions) that phase-memory can ingest as fluid memory.
2.**Request context packages** via phase-memory’s activation planning (respecting user-defined profiles and token budgets).
3.**Surface memory influence** in responses — users should be able to see “this suggestion was shaped by your saved preference for concise git output + recent project conventions.”
4.**Honor user-initiated lifecycle actions** (export, reset, compact, stabilize) exposed through the ports or dedicated `cya memory ...` subcommands in the future.
### Profile-Driven Behavior
In the longer term, users (or the system) will be able to supply or generate **Markitect-compatible memory profiles** that tell phase-memory how `cya` should behave regarding their memory. Examples of profile intent that matter to cya:
- “Keep my last 30 days of shell interactions fluid, but stabilize any workflow I have used more than 5 times.”
- “Treat everything in `~/notes/projects/` as stabilized by default, but require review before anything becomes rigid.”
- “Aggressively compact conversational memory after 48 hours unless I mark it important.”
- “Never let total activated context for a single `cya` request exceed 8k tokens without explicit approval.”
`cya` will request activation plans and context packages that respect these profiles.
## Safety and Explainability Requirements
Because memory directly influences suggestions:
- Every response that used non-ephemeral memory must be able to explain **which** memory items influenced it and why.
- Memory-driven suggestions must still pass through the T03 risk classifier.
- Users must be able to temporarily or permanently disable memory influence for a session or scope (`cya --no-memory ...` or equivalent).
- Export and inspection of memory must be first-class and low-friction.
## Current State (Post MVP)
As of the end of CYA-WP-0001:
- Only the four thin no-op ports exist (T05).
- No actual memory is persisted or recalled by `cya`.
- The orchestrator and safety layer are ready to consume memory signals when they become available.
- The architecture deliberately avoids any hidden or local-JSON fallback memory (per explicit operator direction).
This is the correct starting point. Real integration will be done as a subsequent slice, using the ports as the stable contract.
## Open Questions & Future Work
- How will `cya` generate or help users author memory profiles?
- What is the right granularity for “project memory” vs global memory?
- How should safety decisions and user overrides themselves become first-class memory citizens?
- Can/should `cya` participate in compaction and stabilization planning, or should it only consume the results?
- What observability (cost, token usage, memory influence) should be exposed at the CLI level?
## Success Criteria (Longer Term)
`cya` + `phase-memory` together are successful when a user can say:
- “This assistant actually knows my preferences and project conventions, but I can see exactly what it knows and change it whenever I want.”
- “I switched LLM providers and my assistant still feels like *mine*.”
- “I asked it to forget everything about project X last month, and it actually did.”
- Non-goals (this slice): full 9 kinds, embeddings/SemanticIndex, durable kontextual graph, voice, full profile authoring.
### Refined Port Signatures (cya seam)
These replace/extend the T05 no-op signatures. Implementations in T02+ will delegate to `phase_memory` (ports, planner, lifecycle, runtime or high-level sugar).
```python
def remember_preference(
key: str,
value: Any,
scope: str = "cwd",
*,
profile: str | None = None, # e.g. "cya-assistant-v1" or user profile id
ttl: str | None = None, # e.g. "30d" or phase hint
) -> None: ...
def recall_preferences(
scope: str = "cwd",
task_class: str | None = None,
*,
kinds: list[str] | None = None, # ["preference", "task"] etc.
# Includes status, phase info, provenance summary, policy notes for explain.
...
```
All calls must be non-blocking for the assistance path; failures → graceful empty + stderr warn (current behavior preserved).
### Ownership & Responsibilities
- **cya owns**: the seam (these 4 functions + wiring in orchestrator/cli for context + explain), safety integration (memory signals feed rule-based RiskClassifier but never bypass confirmation), user-visible explainability (provenance rendered in --explain-context and final output), graceful degradation.
This document is distinct from the Intent-vs-Scope gap analysis. It is the forward-looking vision for how memory will evolve in `cya` once real `phase-memory` integration begins. It should be updated as integration work progresses and as phase-memory itself matures.