can-you-assist/MemoryVision.md

Memory Vision for can-you-assist (cya)

Status: Initial vision (post CYA-WP-0001)
Date: 2026-05-26
Related Work: CYA-WP-0001 T05 (minimal ports), phase-memory architecture, INTENT.md

Guiding Principle

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
  • rigid — high-confidence, long-term, rarely changing (core identity, strong conventions)
• 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).

Primary Memory Kinds Relevant to cya

• Conversation / Interaction History — primarily fluid/ephemeral
• Learned Preferences & Conventions — stabilized over time (command style, safety tolerance, explanation depth, shell aliases, etc.)
• Project / Directory Memory — stabilized or rigid context specific to a working directory or repository
• Workflow Recipes & Patterns — stabilized reusable sequences the user has approved or refined
• Safety & Trust Signals — rigid or stabilized (user-defined risk thresholds, trusted command patterns)
• 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.”

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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.