docs: add GrepTard agentic memory report

reports/greptard/2026-04-06-agentic-memory-for-openclaw.md

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+# Agentic Memory for OpenClaw Builders
+
+A practical structure for memory that stays useful under load.
+
+Tag: #GrepTard
+Audience: 15Grepples / OpenClaw builders
+Date: 2026-04-06
+
+## Executive Summary
+
+If you are building an agent and asking “how should I structure memory?”, the shortest good answer is this:
+
+Do not build one giant memory blob.
+
+Split memory into layers with different lifetimes, different write rules, and different retrieval paths. Most memory systems become sludge because they mix live context, task scratchpad, durable facts, and long-term procedures into one bucket.
+
+A clean system uses:
+- working memory
+- session memory
+- durable memory
+- procedural memory
+- artifact memory
+
+And it follows one hard rule:
+
+Retrieval before generation.
+
+If the agent can look something up in a verified artifact, it should do that before it improvises.
+
+## The Five Layers
+
+### 1. Working Memory
+
+This is what the agent is actively holding right now.
+
+Examples:
+- current user prompt
+- current file under edit
+- last tool output
+- last few conversation turns
+- current objective and acceptance criteria
+
+Properties:
+- small
+- hot
+- disposable
+- aggressively pruned
+
+Failure mode:
+If working memory gets too large, the agent starts treating noise as priority and loses the thread.
+
+### 2. Session Memory
+
+This is what happened during the current task or run.
+
+Examples:
+- issue number
+- branch name
+- commands already tried
+- errors encountered
+- decisions made during the run
+- files already inspected
+
+Properties:
+- persists across turns inside the task
+- should compact periodically
+- should die when the task dies unless something deserves promotion
+
+Failure mode:
+If session memory is not compacted, every task drags a dead backpack of irrelevant state.
+
+### 3. Durable Memory
+
+This is what the system should remember across sessions.
+
+Examples:
+- user preferences
+- stable machine facts
+- repo conventions
+- important credentials paths
+- identity/role relationships
+- recurring operator instructions
+
+Properties:
+- sparse
+- curated
+- stable
+- high-value only
+
+Failure mode:
+If you write too much into durable memory, retrieval quality collapses. The agent starts remembering trivia instead of truth.
+
+### 4. Procedural Memory
+
+This is “how to do things.”
+
+Examples:
+- deployment playbooks
+- debugging workflows
+- recovery runbooks
+- test procedures
+- standard triage patterns
+
+Properties:
+- reusable
+- highly structured
+- often better as markdown skills or scripts than embeddings
+
+Failure mode:
+A weak system stores facts but forgets how to work. It knows things but cannot repeat success.
+
+### 5. Artifact Memory
+
+This is the memory outside the model.
+
+Examples:
+- issues
+- pull requests
+- docs
+- logs
+- transcripts
+- databases
+- config files
+- code
+
+This is the most important category because it is often the most truthful.
+
+If your agent ignores artifact memory and tries to “remember” everything in model context, it will eventually hallucinate operational facts.
+
+Repos are memory.
+Logs are memory.
+Gitea is memory.
+Files are memory.
+
+## A Good Write Policy
+
+Before writing memory, ask:
+- Will this matter later?
+- Is it stable?
+- Is it specific?
+- Can it be verified?
+- Does it belong in durable memory, or only in session scratchpad?
+
+A good agent writes less than a naive one.
+The difference is quality, not quantity.
+
+## A Good Retrieval Order
+
+When a new task arrives:
+
+1. check durable memory
+2. check task/session state
+3. retrieve relevant artifacts
+4. retrieve procedures/skills
+5. only then generate free-form reasoning
+
+That order matters.
+
+A lot of systems do it backwards:
+- think first
+- search later
+- rationalize the mismatch
+
+That is how you get fluent nonsense.
+
+## Recommended Data Shape
+
+If you want a practical implementation, use this split:
+
+### A. Exact State Store
+Use JSON or SQLite for:
+- current task state
+- issue/branch associations
+- event IDs
+- status flags
+- dedupe keys
+- replay protection
+
+This is for things that must be exact.
+
+### B. Human-Readable Knowledge Store
+Use markdown, docs, and issues for:
+- runbooks
+- KT docs
+- architecture decisions
+- user-facing reports
+- operating doctrine
+
+This is for things humans and agents both need to read.
+
+### C. Search Index
+Use full-text search for:
+- logs
+- transcripts
+- notes
+- issue bodies
+- docs
+
+This is for fast retrieval of exact phrases and operational facts.
+
+### D. Embedding Layer
+Use embeddings only as a helper for:
+- fuzzy recall
+- similarity search
+- thematic clustering
+- long-tail discovery
+
+Do not let embeddings become your only memory system.
+
+Semantic search is useful.
+It is not truth.
+
+## The Common Failure Modes
+
+### 1. One Giant Vector Bucket
+Everything gets embedded. Nothing gets filtered. Retrieval becomes mood-based instead of exact.
+
+### 2. No Separation of Lifetimes
+Temporary scratchpad gets treated like durable truth.
+
+### 3. No Promotion Rules
+Nothing decides what gets promoted from session memory into durable memory.
+
+### 4. No Compaction
+The system keeps dragging old state forward forever.
+
+### 5. No Artifact Priority
+The model trusts its own “memory” over the actual repo, issue tracker, logs, or config.
+
+That last failure is the ugliest one.
+
+## A Better Mental Model
+
+Think of memory as a city, not a lake.
+
+- Working memory is the desk.
+- Session memory is the room.
+- Durable memory is the house.
+- Procedural memory is the workshop.
+- Artifact memory is the town archive.
+
+Do not pour the whole town archive onto the desk.
+Retrieve what matters.
+Work.
+Write back only what deserves to survive.
+
+## Why This Matters for OpenClaw
+
+OpenClaw-style systems get useful quickly because they are flexible, channel-native, and easy to wire into real workflows.
+
+But the risk is that state, routing, identity, and memory start to blur together.
+That works at first. Then it becomes sludge.
+
+The clean pattern is to separate:
+- identity
+- routing
+- live task state
+- durable memory
+- reusable procedure
+- artifact truth
+
+This is also where Hermes quietly has the stronger pattern:
+not all memory is the same, and not all truth belongs inside the model.
+
+That does not mean “copy Hermes.”
+It means steal the right lesson:
+separate memory by role and by lifetime.
+
+## Minimum Viable Agentic Memory Stack
+
+If you want the simplest version that is still respectable, build this:
+
+1. small working context
+2. session-state SQLite file
+3. durable markdown notes + stable JSON facts
+4. issue/doc/log retrieval before generation
+5. skill/runbook store for recurring workflows
+6. compaction at the end of every serious task
+
+That already gets you most of the way there.
+
+## Final Recommendation
+
+If you are unsure where to start, start here:
+
+- Bucket 1: now
+- Bucket 2: this task
+- Bucket 3: durable facts
+- Bucket 4: procedures
+- Bucket 5: artifacts
+
+Then add three rules:
+- retrieval before generation
+- promotion by filter, not by default
+- compaction every cycle
+
+That structure is simple enough to build and strong enough to scale.
+
+## Closing
+
+The real goal of memory is not “remember more.”
+It is:
+- reduce rework
+- preserve truth
+- repeat successful behavior
+- stay honest under load
+
+A good memory system does not make the agent feel smart.
+It makes the agent less likely to lie.
+
+#GrepTard

reports/greptard/2026-04-06-agentic-memory-for-openclaw.pdf

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