Ai Memory Developer

AI Memory Developer

When to Use

• Building persistent memory for copilots, agents, or conversational AI
• Designing memory APIs (read/write/consolidate/forget)
• Choosing between vector stores, graph databases, or structured DBs for memory
• Implementing memory write/read policies and ACLs
• Debugging wrong, stale, or hallucinated memories
• Tuning what the model should remember across sessions (episodic vs semantic)
• Planning GDPR deletion paths and privacy retention for stored memories
• Evaluating memory quality (recall, precision, isolation)

When NOT to Use

• General RAG document search or indexing pipelines → ai-engineer
• Context window packing, token budgets, or compression → ai-context-engineer
• AI team operations, release governance, or SLOs → ai-lead-ops
• Org-wide token cost improvement roadmaps → ai-token-improvement-plan-engineer

Related skills

| Need | Skill | |---|---| | End-to-end LLM app, RAG, agents | ai-engineer | | Context assembly and compression | ai-context-engineer | | Prompt and tool message design | prompt-engineer | | PII retention and governance | ai-risk-governance | | Production monitoring and incidents | ai-lead-ops | | Token cost program and phased savings plan | ai-token-improvement-plan-engineer |

Core Workflows

1. Memory model design

Classify memory types:

| Type | Lifetime | Examples | Store | |---|---|---|---| | Working | Single turn / tool loop | Tool results, scratchpad | In-context only | | Session | Chat session | Current task state | Redis / thread store | | User long-term | Cross-session | Preferences, facts user stated | Vector + structured DB | | Organizational | Shared | Docs, policies | RAG index (see ai-engineer) |

Design decisions:

1. What may be written automatically vs requires user confirmation?
2. Per-tenant isolation and ACL on every read/write
3. TTL and deletion (GDPR erase path)
4. Conflict resolution when new fact contradicts old

See references/memory_architecture.md for patterns and anti-patterns.

2. Write path (ingestion to memory)

observe → extract candidates → score importance → dedupe → persist → index

Checklist:

• [ ] Extract only durable facts, not transient chit-chat
• [ ] Attach provenance (message ID, timestamp, source)
• [ ] Dedupe with embedding similarity + entity linking
• [ ] Never store secrets, raw payment data, or full medical records unless required and approved

See references/write_consolidation.md for extraction prompts and consolidation jobs.

3. Read path (retrieval for generation)

1. Build query from current user message + session summary
2. Retrieve top-k memories with metadata filters (user_id, tenant_id)
3. Rerank; drop below relevance threshold
4. Inject into context in structured block (see ai-context-engineer)
5. Cite memory IDs in logs for debugging

See references/read_retrieval.md for ranking and injection formats.

4. Forgetting and maintenance

| Trigger | Action | |---|---| | User delete request | Hard delete all user memories | | TTL expired | Archive or purge | | Low usefulness score | Decay or summarize away | | Contradiction | Supersede old record; keep audit trail |

Run nightly consolidation: merge episodic notes into semantic summaries.

See references/write_consolidation.md for consolidation algorithms.

5. Evaluation

| Test | Pass criteria | |---|---| | Write accuracy | Gold facts appear in store after session | | Recall | Question answerable from prior session | | Precision | Irrelevant memories not retrieved | | Isolation | Tenant A never sees tenant B | | Forgetting | Deleted user has zero retrievable memories |

See references/memory_eval.md for datasets and regression harness.

When to load references

• Architecture and stores → references/memory_architecture.md
• Write and consolidation → references/write_consolidation.md
• Read and ranking → references/read_retrieval.md
• Evaluation → references/memory_eval.md

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: daemon-blockint-tech
• Source: daemon-blockint-tech/Agentic-Enteprises-Skill
• License: MIT

Install and usage instructions live in the source repository linked above.