# ai-memory | Fabio Akita | Knowledge Base | Instagit

Solution for long term memory for agent coding CLIs and to facilitate handoff between different agent vendors

GitHub Stars: 2.7k

Repository: https://github.com/akitaonrails/ai-memory

---

## Articles

### [How ai-memory Manages SQLite Database Writes: Single-Writer Actor Pattern](/akitaonrails/ai-memory/how-ai-memory-manage-sqlite-database-writes)

Discover how ai-memory ensures thread-safe SQLite writes using a single writer actor pattern and async channels for efficient, serialized database operations. Learn about its unique approach.

- Tags: internals
- Published: 2026-09-09

### [Understanding Cross-Cutting Invariants in ai-memory's Architecture](/akitaonrails/ai-memory/what-cross-cutting-invariants-ai-memory-architecture)

Discover the fifteen cross-cutting invariants in ai-memory's architecture. Learn how SQLite channels and typed sanitization ensure data integrity, thread safety, and predictable behavior.

- Tags: architecture
- Published: 2026-09-09

### [How ai-memory Ensures Atomicity in File Writes: The Temp-Rename Pattern Explained](/akitaonrails/ai-memory/how-ai-memory-ensure-atomicity-file-writes)

Discover how ai-memory ensures atomic file writes using the temp-rename pattern. Learn how this technique prevents corrupted data even during system crashes.

- Tags: deep-dive
- Published: 2026-09-09

### [What Does `project_strategy = "repo-root"` Mean in `.ai-memory.toml`?](/akitaonrails/ai-memory/what-project-strategy-repo-root-mean-ai-memory-toml)

Understand project_strategy = "repo-root" in .ai-memory.toml. Learn how this setting defines your repository's top-level directory as the project root for ai-memory indexing.

- Tags: getting-started
- Published: 2026-09-09

### [How the `.ai-memory.toml` File Supports Multi-Client Consultancies](/akitaonrails/ai-memory/how-ai-memory-toml-support-multi-client-consultancies)

Discover how the .ai-memory.toml file empowers multi-client consultancies by defining workspace and project scopes for AI agents and clients. Learn about deterministic directory tree resolution.

- Tags: how-to-guide
- Published: 2026-09-09

### [What Is the Purpose of the `.ai-memory.toml` Marker File?](/akitaonrails/ai-memory/purpose-ai-memory-toml-marker-file)

Understand the purpose of the .ai-memory.toml marker file. Learn how it defines your project's logical workspace and enables the ai-memory system to discover your repository.

- Tags: how-to-guide
- Published: 2026-09-09

### [How Pinned Pages Are Handled in ai‑memory's Decay System](/akitaonrails/ai-memory/how-pinned-pages-handled-ai-memory-decay)

Discover how ai-memory's decay system protects pinned pages from eviction. Learn how the pinned flag and front-matter ensure your important content remains accessible.

- Tags: internals
- Published: 2026-09-09

### [How the Episodic Memory Decay Formula Works in ai-memory](/akitaonrails/ai-memory/how-episodic-memory-decay-formula-work-ai-memory)

Understand the episodic memory decay formula in ai-memory. Learn how age and access frequency combine to manage content salience and eviction.

- Tags: deep-dive
- Published: 2026-09-09

### [Understanding the Four Memory Tiers in ai-memory: Working, Episodic, Semantic, and Procedural](/akitaonrails/ai-memory/what-are-ai-memory-memory-tiers)

Explore the four memory tiers in ai-memory: Working, Episodic, Semantic, and Procedural. Learn how each tier impacts retention, search, and lifecycle management for your AI content.

- Tags: deep-dive
- Published: 2026-09-09

### [How ai-memory Handles Memory Decay Across Tiers](/akitaonrails/ai-memory/how-ai-memory-handle-memory-decay-tiers)

Discover how ai-memory manages memory decay across tiers. Learn about its nightly retention sweep, scoring, and tier-specific rules for optimal data management.

- Tags: deep-dive
- Published: 2026-09-09

### [How to Write Durable Wiki Knowledge with ai-memory: A Complete Guide](/akitaonrails/ai-memory/how-write-durable-wiki-knowledge-ai-memory)

Learn to write durable wiki knowledge with ai-memory. This guide details how ai-memory ensures data integrity through version control, atomic writes, and indexing for reliable knowledge management.

- Tags: how-to-guide
- Published: 2026-09-09

### [How the memory_query Tool Works in ai-memory: Hybrid Search Architecture Explained](/akitaonrails/ai-memory/how-memory-query-tool-work-ai-memory)

Explore the memory_query tool in ai-memory. Learn how its hybrid search architecture combines lexical, entity, and graph search for efficient historical data retrieval.

- Tags: deep-dive
- Published: 2026-09-09

### [Understanding the Purpose of Each Crate in the ai-memory Repository](/akitaonrails/ai-memory/purpose-of-each-crate-ai-memory-repository)

Explore the ai-memory repository and understand the purpose of each Rust crate. Discover how they manage domain types, persistence, LLM integration, and more.

- Tags: internals
- Published: 2026-09-09

### [How ai-memory Facilitates Cross-Agent Handoffs: Architecture and Implementation](/akitaonrails/ai-memory/how-ai-memory-facilitate-cross-agent-handoffs)

Discover how ai-memory securely enables cross-agent handoffs using a centralized table and API access. Learn about its architecture and implementation for seamless agent communication.

- Tags: architecture
- Published: 2026-09-09

### [How ai-memory Performs Memory Recall and Search: Architecture and Implementation](/akitaonrails/ai-memory/how-ai-memory-perform-memory-recall-search)

Discover how ai-memory performs memory recall and search using a dual-storage architecture. Learn about Git-backed markdown storage and fast SQLite FTS5 full-text retrieval with optional semantic reranking.

- Tags: architecture
- Published: 2026-09-09

### [How ai-memory Consolidates Session Data into Wiki Pages: A 5-Stage Pipeline](/akitaonrails/ai-memory/how-ai-memory-consolidate-session-data-wiki-pages)

Discover how ai-memory consolidates session data into wiki pages. Explore its 5-stage pipeline for structured, version-controlled knowledge management.

- Tags: how-to-guide
- Published: 2026-09-09

### [How ai-memory Captures Agent Lifecycle Hooks: Hook Installation, Sanitization, and Storage](/akitaonrails/ai-memory/how-ai-memory-capture-agent-lifecycle-hooks)

Discover how ai-memory captures agent lifecycle hooks. Learn about hook installation, sanitization, and storage for seamless AI agent behavior tracking.

- Tags: how-to-guide
- Published: 2026-09-09

### [How Data Flows Through ai-memory: A Complete Architecture Guide](/akitaonrails/ai-memory/how-data-flow-through-ai-memory)

Understand ai-memory data flow. Explore its two-layer pipeline, lifecycle hooks, SQLite serialization, LLM consolidation, and immutable markdown wiki source of truth.

- Tags: architecture
- Published: 2026-09-09

### [What Is the Source of Truth in the ai-memory Storage Architecture?](/akitaonrails/ai-memory/what-source-truth-ai-memory-storage-architecture)

Discover the source of truth in ai-memory storage architecture. Learn how the markdown wiki acts as the definitive source, while SQLite provides a rebuildable search index.

- Tags: architecture
- Published: 2026-09-09

### [How ai-memory Data Storage Works: SQLite and File System Architecture](/akitaonrails/ai-memory/how-ai-memory-data-stored)

Discover how ai-memory data storage works using SQLite and file system architecture. Learn about runtime state, atomic markdown files, and ACID compliance with a single-writer actor pattern.

- Tags: internals
- Published: 2026-09-09

### [Core Architecture of ai-memory: A Dual-Layer Memory System for AI Agents](/akitaonrails/ai-memory/what-is-ai-memory-core-architecture)

Explore the core architecture of ai-memory, a dual-layer system using markdown files as truth and SQLite for fast retrieval. Understand its eight-crate design.

- Tags: architecture
- Published: 2026-09-09

### [How to Configure Memory Decay and Retention Policies in ai-memory](/akitaonrails/ai-memory/configure-ai-memory-decay-retention-policies)

Learn to configure memory decay and retention policies in ai-memory using the .ai-memory.toml file. Control salience reduction and set fine-grained TTL overrides.

- Tags: how-to-guide
- Published: 2026-09-06

### [How Raw Observations are Handled by the Memory Decay System in ai-memory](/akitaonrails/ai-memory/ai-memory-raw-observations-memory-decay)

Discover how ai-memory's memory decay system handles raw observations. Learn about the pruning process and observation retention for efficient AI memory management.

- Tags: internals
- Published: 2026-09-06

### [When Does the ai‑memory Forget Sweep Run and What Does It Do?](/akitaonrails/ai-memory/ai-memory-forget-sweep-schedule-function)

Discover when the ai-memory forget sweep runs daily and what it accomplishes. This maintenance job removes stale pages, purges expired content, and cleans up tombstones for optimal performance.

- Tags: how-to-guide
- Published: 2026-09-06

### [How the Breadth Term in ai-memory's Decay Formula Works](/akitaonrails/ai-memory/ai-memory-breadth-term-decay-formula)

Understand the breadth term in ai-memory's decay formula. Learn how it uses distinct operator access to retain team-wide knowledge and enhance retention scores.

- Tags: deep-dive
- Published: 2026-09-06

### [How Memory Decay Is Calculated in ai-memory: A Deep Dive into the Retention Score Algorithm](/akitaonrails/ai-memory/ai-memory-memory-decay-calculation)

Discover how ai-memory calculates memory decay with the retention score algorithm. Learn about exponential decay, access frequency, and feedback adjustments for efficient memory management.

- Tags: deep-dive
- Published: 2026-09-06

### [ai‑memory M8 Retention Policy: The 4 Memory Tiers Explained](/akitaonrails/ai-memory/ai-memory-m8-retention-policy-tiers)

Explore ai-memory's M8 retention policy and its four memory tiers: Working, Episodic, Semantic, and Procedural. Understand page eviction and preservation rules.

- Tags: deep-dive
- Published: 2026-09-06

### [Bounded Authority Multiplier in ai-memory: How It Affects Retrieval Relevance](/akitaonrails/ai-memory/ai-memory-bounded-authority-multiplier-retrieval-relevance)

Discover the bounded authority multiplier in ai-memory. Learn how it re-weights search results using canonical metadata to boost authoritative knowledge and improve retrieval relevance.

- Tags: deep-dive
- Published: 2026-09-06

### [How Vector Embeddings Are Integrated Into the ai-memory Retrieval Pipeline](/akitaonrails/ai-memory/ai-memory-vector-embeddings-retrieval-pipeline)

Discover how vector embeddings enhance the ai-memory retrieval pipeline by generating dense vectors and fusing them with multiple signals for semantically ranked results.

- Tags: deep-dive
- Published: 2026-09-06

### [How ai-memory's Hybrid Retrieval System Combines FTS5, Entity-Match, and Graph RRF](/akitaonrails/ai-memory/ai-memory-hybrid-retrieval-fts5-entity-match-rrf)

Discover how ai-memory's hybrid retrieval system uniquely combines FTS5, entity-match, and graph RRF for transparent relevance scores. Learn more about this powerful search fusion.

- Tags: deep-dive
- Published: 2026-09-06

### [Content Limits for Different Observation Types in ai-memory: A Complete Technical Guide](/akitaonrails/ai-memory/ai-memory-content-limits-observation-types)

Discover ai-memory content limits for raw inputs UI excerpts consolidation projections and auto-improvement outputs. Understand size restrictions from 1500 characters to 16 KB in this technical guide.

- Tags: deep-dive
- Published: 2026-09-06

### [How Hook Events Are Sent to the ai-memory Server and Response Codes Explained](/akitaonrails/ai-memory/ai-memory-hook-event-sending-response-codes)

Learn how ai-memory sends hook events to its server and understand the HTTP 202 Accepted response code. Discover the details of the ai-memory POST request.

- Tags: how-to-guide
- Published: 2026-09-06

### [Complete Guide to ObservationKind Values for ai-memory Lifecycle Hooks](/akitaonrails/ai-memory/ai-memory-observationkind-values-lifecycle-hooks)

Explore the ten ObservationKind values like SessionStart UserPrompt PreToolUse and SessionEnd available for ai-memory lifecycle hooks in this comprehensive guide.

- Tags: api-reference
- Published: 2026-09-06

### [Understanding Lifecycle Hooks in ai-memory: How Agent Events Are Captured](/akitaonrails/ai-memory/ai-memory-lifecycle-hooks-agent-event-capture)

Explore ai-memory lifecycle hooks to capture agent events via HTTP endpoints. Learn about policy enforcement, rate limiting, and async storage in SQLite and wiki pages.

- Tags: deep-dive
- Published: 2026-09-06

### [How ai-memory Handles LLM Consolidation and Embedding Provider Retries](/akitaonrails/ai-memory/ai-memory-llm-consolidation-embedding-retries)

Learn how ai-memory consolidates LLM data and handles embedding provider retries with token-aware budgets and selective error logic for improved reliability.

- Tags: internals
- Published: 2026-09-06

### [What Messages Does the ai-memory Writer Actor Process?](/akitaonrails/ai-memory/ai-memory-writer-actor-message-processing)

Discover what messages the ai-memory writer actor processes. Learn about WriteCmd for database writes and MaintenanceJob for optimizations handled asynchronously.

- Tags: internals
- Published: 2026-09-06

### [How ai-memory Handles Read Operations Under Its Single-Writer Architecture](/akitaonrails/ai-memory/ai-memory-read-operations-single-writer)

Discover how ai-memory's single-writer architecture achieves high-throughput concurrent reads using a dedicated reader pool and SQLite WAL mode. Learn how writes remain serialized without blocking reads.

- Tags: internals
- Published: 2026-09-06

### [How ai-memory Prevents Concurrent Write Conflicts in Its SQLite Database](/akitaonrails/ai-memory/prevent-concurrent-write-conflicts-ai-memory-sqlite)

Learn how ai-memory prevents SQLite write conflicts. Discover its single-writer actor thread strategy for safe concurrent database operations.

- Tags: internals
- Published: 2026-09-06

### [What Is the Single-Writer SQLite Actor Pattern in ai-memory and Why Is It Used?](/akitaonrails/ai-memory/single-writer-sqlite-actor-pattern-ai-memory)

Discover the single-writer SQLite actor pattern in akitaonrails/ai-memory. Learn how it isolates DB mutations on a thread to eliminate write contention and enable concurrent reads.

- Tags: deep-dive
- Published: 2026-09-06

### [How ai-memory Ensures Transactional Consistency Between Markdown Files and the SQLite Index](/akitaonrails/ai-memory/ai-memory-transactional-consistency-markdown-sqlite)

Learn how ai-memory ensures transactional consistency between Markdown files and SQLite index using atomic filesystem operations and single-writer pipeline.

- Tags: internals
- Published: 2026-09-06

### [Understanding the ai-memory SQLite Database Structure: Schema, Tables, and Relationships](/akitaonrails/ai-memory/ai-memory-sqlite-database-structure)

Explore the ai-memory SQLite database structure. Learn about its migration-driven schema, hierarchical workspace-project-entity model, versioned wiki pages, and full-text search capabilities.

- Tags: architecture
- Published: 2026-09-06

### [How to Manually Edit ai‑memory Markdown Files and Reconcile Changes](/akitaonrails/ai-memory/manually-edit-ai-memory-markdown-files-reconciliation)

Learn to manually edit ai-memory Markdown files in the wiki tree. Reconcile changes automatically with the file watcher or force a reindex via CLI.

- Tags: how-to-guide
- Published: 2026-09-06

### [Why ai-memory Treats Its Markdown Wiki as the Source of Truth](/akitaonrails/ai-memory/role-of-markdown-wiki-as-source-of-truth-in-ai-memory)

Discover how ai-memory uses its Markdown wiki as the single source of truth for all persistent data. Learn why this git-versioned approach ensures reliable knowledge management.

- Tags: architecture
- Published: 2026-09-06

### [How ai-memory Uses SQLite and a Git‑Backed Markdown Wiki for Storage](/akitaonrails/ai-memory/how-ai-memory-uses-sqlite-and-git-markdown-wiki-storage)

Discover how ai-memory uses SQLite and a Git-backed Markdown wiki for dual storage. Explore efficient access to human-readable content and query-optimized metadata.

- Tags: how-to-guide
- Published: 2026-09-06

### [How to Use the ai-memory CLI for HTTP Subcommands: A Complete Guide](/akitaonrails/ai-memory/how-to-use-the-ai-memory-cli-for-http-subcommands)

Learn to use the ai-memory CLI for HTTP subcommands. Interact directly with ai-memory servers via the terminal using standard HTTP verbs in this complete guide.

- Tags: how-to-guide
- Published: 2026-09-05

### [How to Import External Conversations into ai-memory: Complete Guide with CLI Examples](/akitaonrails/ai-memory/how-can-i-import-external-conversations-into-ai-memory)

Learn how to import external conversations into ai-memory using the ai-memory-importer CLI. Follow our guide with examples to easily add your chat history.

- Tags: how-to-guide
- Published: 2026-09-05

### [What Are `_slots/` Pages in ai-memory? A Complete Guide to Contextual Wiki Slots](/akitaonrails/ai-memory/what-are-_slots-pages-in-ai-memory)

Discover ai-memory's _slots/ pages. Learn how these mutable wiki pages store per-session contextual data, enhancing your project briefs with "what you are working on" for improved AI sessions.

- Tags: how-to-guide
- Published: 2026-09-05

### [How Pinned Pages Are Handled in ai-memory: Complete Technical Guide](/akitaonrails/ai-memory/how-are-pinned-pages-handled-in-ai-memory)

Discover how ai-memory handles pinned pages. Learn about immutable, decay-immune records that bypass the retention system for essential data.

- Tags: deep-dive
- Published: 2026-09-05

### [How Does Episodic Memory Tier Decay Work in ai-memory?](/akitaonrails/ai-memory/how-does-the-episodic-memory-tier-decay)

Discover how ai-memory's episodic memory tier decay works. Learn about exponential time decay, access frequency, and actor breadth's role in evicting session pages.

- Tags: deep-dive
- Published: 2026-09-05

### [The Four Memory Tiers in ai-memory: Working, Episodic, Semantic, and Procedural](/akitaonrails/ai-memory/what-are-the-different-memory-tiers-in-ai-memory)

Explore the four memory tiers in ai-memory Working Episodic Semantic and Procedural. Learn how they manage retention search ranking and lifecycle for your markdown pages.

- Tags: deep-dive
- Published: 2026-09-05

### [How ai-memory Versions Pages and Maintains Their Links: A Technical Deep Dive](/akitaonrails/ai-memory/how-are-pages-versioned-and-linked-in-ai-memory)

Discover how ai-memory versions pages using append-only edits and supersedes pointers. Learn how it automatically maintains links to the latest page versions.

- Tags: deep-dive
- Published: 2026-09-05

### [ai‑memory Database Schema: Complete Guide to Tables, Indexes, and Migration Files](/akitaonrails/ai-memory/what-is-the-schema-for-the-ai-memory-database)

Explore the ai-memory database schema. Understand its nine tables, indexes, and migration files for efficient data management and advanced AI capabilities.

- Tags: api-reference
- Published: 2026-09-05

### [How ai-memory Handles Multi-Session and Multi-User Access: Isolation Modes Explained](/akitaonrails/ai-memory/how-does-ai-memory-handle-multi-session-and-multi-user-access)

Discover how ai-memory isolation modes manage multi-session and multi-user access safely. Learn about Single, PerSession, and PerActor modes for secure data handling.

- Tags: deep-dive
- Published: 2026-09-05

### [How ai-memory Ensures a Single Configuration Read Path at Startup](/akitaonrails/ai-memory/how-does-ai-memory-ensure-a-single-configuration-read-path)

Learn how ai-memory ensures a single configuration read path by loading settings once into an immutable Arc<Config> for consistent access across your codebase.

- Tags: internals
- Published: 2026-09-05

### [Cross‑Cutting Invariants in ai‑memory's Architecture: A Complete Technical Guide](/akitaonrails/ai-memory/what-are-the-cross-cutting-invariants-in-ai-memorys-architecture)

Explore ai-memory's cross-cutting invariants for robust data integrity and predictable behavior. Understand configuration loading, DB access, file ops, and LLM integrations in this technical guide.

- Tags: architecture
- Published: 2026-09-05

### [How LLM Providers Are Managed in ai-memory: A Complete Technical Guide](/akitaonrails/ai-memory/how-are-llm-providers-managed-in-ai-memory)

Discover how ai-memory manages LLM providers with a technical deep dive. Explore the LlmProvider trait, factory pattern, and eight implementations like OpenAI and Gemini.

- Tags: deep-dive
- Published: 2026-09-05

### [What Is the ai-memory-wiki Crate? Responsibilities, Architecture, and Code Examples](/akitaonrails/ai-memory/what-is-the-responsibility-of-the-ai-memory-wiki-crate)

Discover the ai-memory-wiki crate's role in synchronizing your markdown filesystem with SQLite for efficient indexing and search. Learn its core responsibilities and architecture.

- Tags: deep-dive
- Published: 2026-09-05

### [How the `ai-memory-store` Crate Functions: A Deep Dive into the SQLite Persistence Layer](/akitaonrails/ai-memory/how-does-the-ai-memory-store-crate-function)

Discover how the ai-memory-store crate works. Learn about its SQLite persistence, single-writer thread, and connection pool for efficient, concurrent data management.

- Tags: deep-dive
- Published: 2026-09-05

### [What Is the Purpose of the ai-memory-core Crate in the ai-memory Project?](/akitaonrails/ai-memory/what-is-the-purpose-of-the-ai-memory-core-crate)

Discover the purpose of the ai-memory-core crate, the stable I/O-free foundation for the ai-memory project, offering essential types and utilities.

- Tags: deep-dive
- Published: 2026-09-05

### [How LLM Consolidations Are Handled in ai-memory: Complete Technical Guide](/akitaonrails/ai-memory/how-are-llm-consolidations-handled-in-ai-memory)

Discover how ai-memory consolidates LLMs. Learn about the Consolidator component, batching, LLM provider interaction, and atomic wiki writes in this technical guide.

- Tags: deep-dive
- Published: 2026-09-05

### [What Is the Data Flow in the ai-memory System? A 3-Phase Pipeline Explained](/akitaonrails/ai-memory/what-is-the-data-flow-within-the-ai-memory-system)

Understand the ai-memory data flow with our 3-phase pipeline explanation: ingest hooks, SQLite/markdown persistence, and read-only query pools. Learn more today!

- Tags: architecture
- Published: 2026-09-05

### [How ai-memory Manages SQLite Read and Write Operations: A Single-Writer Actor Model](/akitaonrails/ai-memory/how-does-ai-memory-manage-sqlite-read-and-write-operations)

Discover how ai-memory prevents SQLite locked errors using a single-writer actor model. It separates reads and writes for efficient, concurrent database operations.

- Tags: internals
- Published: 2026-09-05

### [How ai-memory Handles Atomic Markdown Writes: The tmp-rename-fsync Pattern Explained](/akitaonrails/ai-memory/how-does-ai-memory-handle-atomic-markdown-writes)

Discover how ai-memory ensures crash-safe Markdown writes with the tmp-rename-fsync pattern and automatic rollback for database failures. Learn about this robust atomic write protocol.

- Tags: deep-dive
- Published: 2026-09-05

### [How ai-memory Stores Persistent Data: SQLite Architecture and Single-Writer Concurrency](/akitaonrails/ai-memory/how-does-ai-memory-store-persistent-data)

Discover how ai-memory stores persistent data using SQLite architecture and single-writer concurrency. Learn about its WAL-mode database and actor thread for efficient data management.

- Tags: architecture
- Published: 2026-09-05

### [How to Run AI Agents with ai-memory CLI Commands](/akitaonrails/ai-memory/how-to-run-ai-agents-with-ai-memory-cli-commands)

Learn to run AI agents like Claude and Codex using ai-memory CLI commands. Start the server with `ai-memory serve` and launch agents with `ai-memory run <agent>` for seamless orchestration and interaction persistence.

- Tags: how-to-guide
- Published: 2026-09-01

### [How to Perform a Forget Sweep in ai-memory: 3 Methods Explained](/akitaonrails/ai-memory/how-to-perform-a-forget-sweep-in-ai-memory)

Learn how to perform a forget sweep in ai-memory with 3 methods. Prevent unbounded SQLite growth by tombstoning old pages via CLI, API, or automation.

- Tags: how-to-guide
- Published: 2026-09-01

### [How to Manage Cross-Agent Handoffs in ai-memory: A Complete Implementation Guide](/akitaonrails/ai-memory/how-to-manage-cross-agent-handoffs-in-ai-memory)

Master cross-agent handoffs in ai-memory with our guide. Learn to implement a three-state machine and REST API for seamless project context transfer.

- Tags: how-to-guide
- Published: 2026-09-01

### [How LLM-Driven Page Rewrite Works with `memory_consolidate`](/akitaonrails/ai-memory/how-does-llm-driven-page-rewrite-work-with-memory_consolidate)

Discover how LLM-driven page rewrite works with memory_consolidate. This subsystem transforms raw observations into markdown, preserving history through Git-backed versioning.

- Tags: how-to-guide
- Published: 2026-09-01

### [How to Use the `memory_query` Tool in ai-memory: Complete CLI Guide](/akitaonrails/ai-memory/how-to-use-the-memory_query-tool-in-ai-memory)

Master the ai-memory CLI with our complete guide to `memory_query`. Run ad-hoc natural-language queries against your vector store effortlessly.

- Tags: how-to-guide
- Published: 2026-09-01

### [How Pinned Pages Affect Retention in ai-memory: A Complete Technical Guide](/akitaonrails/ai-memory/how-do-pinned-pages-affect-retention-in-ai-memory)

Discover how pinned pages in ai-memory ensure permanent data retention by bypassing the forget sweep. Learn the technical details for guaranteed data persistence in this complete guide.

- Tags: deep-dive
- Published: 2026-09-01

### [How ai-memory Calculates Memory Decay: Retention Scores, Decay Parameters & Eviction Logic](/akitaonrails/ai-memory/how-is-memory-decay-calculated-in-ai-memory)

Discover how ai-memory calculates memory decay. Explore retention scores, decay parameters, and eviction logic to understand how your AI remembers and forgets.

- Tags: deep-dive
- Published: 2026-09-01

### [ai-Memory Four Tiers Explained: Working, Episodic, Semantic, and Procedural](/akitaonrails/ai-memory/what-are-the-four-memory-tiers-in-ai-memory)

Explore the four memory tiers in ai-memory: Working, Episodic, Semantic, and Procedural. Understand how they mimic human cognition for advanced AI.

- Tags: deep-dive
- Published: 2026-09-01

### [ai-Memory Observation Limits: File Size, Character Counts, and Pagination Bounds Explained](/akitaonrails/ai-memory/what-are-the-content-limits-for-ai-memory-observations)

Understand ai-memory observation limits including file size, character counts, and pagination bounds. Learn how to optimize your data for AI memory with this essential guide.

- Tags: deep-dive
- Published: 2026-09-01

### [How the Sanitization Boundary Protects ai-memory Data: A Type-Safe Security Architecture](/akitaonrails/ai-memory/how-does-the-sanitization-boundary-protect-ai-memory-data)

Discover how the ai-memory Sanitization Boundary shields your knowledge base. Learn how type-safe sanitization prevents malicious data from reaching your SQLite store or LLMs.

- Tags: architecture
- Published: 2026-09-01

### [How ai-memory Handles Hook Event Timeouts: Per-Webhook Configuration and Failure Policies](/akitaonrails/ai-memory/how-does-ai-memory-handle-hook-event-timeouts)

Learn how ai-memory manages hook event timeouts with per-webhook settings, default timeouts, and failure policies for robust error handling within your AdmissionChain.

- Tags: how-to-guide
- Published: 2026-09-01

### [Complete Guide to ObservationKind Events in ai-memory: 7 Types Explained](/akitaonrails/ai-memory/what-are-the-available-observationkind-events-in-ai-memory)

Explore the 7 ObservationKind events in ai-memory: UserPrompt, PreToolUse, PostToolUse, Stop, SessionStart, SessionEnd, and Other. Understand every agent interaction with this comprehensive guide.

- Tags: deep-dive
- Published: 2026-09-01

### [How ai-memory Handles Scope Resolution: A Deep Dive Into the ScopeResolver Architecture](/akitaonrails/ai-memory/how-does-ai-memory-handle-scope-resolution)

Discover how ai-memory handles scope resolution with its ScopeResolver architecture. Learn about workspace and project isolation and strict data policies for efficient management.

- Tags: deep-dive
- Published: 2026-09-01

### [How ai-memory Prevents Write Contention in Its SQLite Database: Single-Writer Architecture Explained](/akitaonrails/ai-memory/how-does-ai-memory-prevent-write-contention-in-its-database)

Learn how ai-memory prevents SQLite write contention using a single-writer architecture. Discover how a dedicated writer thread ensures database integrity and performance.

- Tags: internals
- Published: 2026-09-01

### [How ai-memory Handles Time-Travel and Revision History: A Deep Dive into Supersession Chains](/akitaonrails/ai-memory/how-does-ai-memory-handle-time-travel-and-revision-history)

Explore how ai-memory's immutable supersession chains enable time-travel and revision history. Learn how new versions link to older revisions for seamless data management.

- Tags: deep-dive
- Published: 2026-09-01

### [ai-memory Data Directory Structure: A Complete Guide to `<data_dir>` Layout and Organization](/akitaonrails/ai-memory/what-is-the-file-structure-of-the-ai-memory-data-directory)

Understand the ai-memory data directory structure. Explore the six-folder layout including wiki, db, raw, logs, models, and client projects for efficient organization and data management.

- Tags: how-to-guide
- Published: 2026-09-01

### [How SQLite is Used as a Derived Index in ai‑memory: Architecture Explained](/akitaonrails/ai-memory/how-is-sqlite-used-as-a-derived-index-in-ai-memory)

Discover how SQLite functions as a derived index in ai-memory. Learn how it leverages external-content FTS5 tables for rapid full-text search on Markdown files.

- Tags: architecture
- Published: 2026-09-01

### [How ai-memory Ensures Markdown Is the Source of Truth: File-First Architecture Explained](/akitaonrails/ai-memory/how-does-ai-memory-ensure-markdown-is-the-source-of-truth)

Discover how ai-memory's file-first architecture keeps Markdown as your source of truth. Learn how plain md files in Git ensure data integrity and easy rebuilding of indexes.

- Tags: architecture
- Published: 2026-09-01

### [Understanding the Dual‑Layer Architecture of ai‑memory: SQLite + Markdown Design Explained](/akitaonrails/ai-memory/what-is-the-dual-layer-architecture-of-ai-memory)

Discover ai-memory's dual-layer architecture. It uses SQLite for structured data and Markdown for human-readable, version-controlled knowledge. Learn more!

- Tags: architecture
- Published: 2026-09-01

### [How to Set Up ai-memory for AI Coding Agents: A Complete Installation Guide](/akitaonrails/ai-memory/how-to-set-up-ai-memory-for-ai-coding-agents)

Install ai-memory for AI coding agents and give them long-term, cross-session memory. This Rust binary is easy to build, configure, and deploy in minutes. Get started now.

- Tags: getting-started
- Published: 2026-09-01

### [How ai-memory Handles Global Preferences and Context: Understanding the `_global` Scope](/akitaonrails/ai-memory/how-does-ai-memory-handle-global-preferences-and-context)

Learn how ai-memory manages global preferences using the _global scope. Discover automatic merging for cross-project settings with lookup_global_scope and create_global_scope.

- Tags: deep-dive
- Published: 2026-08-31

### [How ai-memory Handles Auto-Scoping on Shared Servers: Isolation by Design](/akitaonrails/ai-memory/how-does-ai-memory-handle-auto-scoping-on-shared-servers)

Discover how ai-memory ensures isolation on shared servers. Learn how auto-scoping prevents cross-session interference by using unique scope identifiers for each workspace-project-path tuple.

- Tags: internals
- Published: 2026-08-31

### [How to Override Project Scope in ai-memory Using a .ai-memory.toml Marker File](/akitaonrails/ai-memory/how-can-i-override-project-scope-in-ai-memory-using-a-marker-file)

Override ai-memory project scope with a .ai-memory.toml marker file. Learn how this simple file controls project detection for accurate scope management.

- Tags: how-to-guide
- Published: 2026-08-31

### [How Project Scope Is Determined in ai-memory: The ScopeResolver Mechanism](/akitaonrails/ai-memory/how-is-the-project-scope-determined-in-ai-memory)

Discover how ai-memory determines project scope using the ScopeResolver mechanism. Learn about explicit parameters, project markers, and default fallbacks.

- Tags: internals
- Published: 2026-08-31

### [How ai-memory Implements Cross-Project Isolation in Rust](/akitaonrails/ai-memory/how-does-ai-memory-implement-cross-project-isolation)

Learn how ai-memory ensures cross-project isolation in Rust by embedding unique identities into SQLite rows and enforcing access through a ScopeResolver. Protect your data with robust isolation.

- Tags: internals
- Published: 2026-08-31

### [How to View Recent Wiki Commits in ai‑memory using git log](/akitaonrails/ai-memory/how-can-i-view-recent-wiki-commits-in-ai-memory-using-git-log)

Easily view recent wiki commits in ai-memory with git log. Learn how to check markdown file changes in the docs directory. Fast and efficient Git commands.

- Tags: how-to-guide
- Published: 2026-08-31

### [How to Restore an ai-memory SQLite Database from a Backup: Complete CLI Guide](/akitaonrails/ai-memory/how-do-i-restore-an-ai-memory-sqlite-database-from-a-backup)

Learn to restore your ai-memory SQLite database from a backup. This CLI guide shows you how to use the ai-memory restore command to quickly recover your data. Stop the server and run the restore command.

- Tags: how-to-guide
- Published: 2026-08-31

### [How to Back Up the ai-memory SQLite Database: CLI, HTTP, and Programmatic Methods](/akitaonrails/ai-memory/how-can-i-back-up-the-ai-memory-sqlite-database)

Learn how to back up your ai-memory SQLite database safely using CLI, HTTP, or programmatic methods. Create a gzipped tarball with a live server backup.

- Tags: how-to-guide
- Published: 2026-08-31

### [How ai-memory Handles Embedding Configuration Changes and Stale Vectors](/akitaonrails/ai-memory/how-does-ai-memory-handle-embedding-configuration-changes-and-stale-vectors)

Learn how ai-memory manages embedding configuration changes and stale vectors. Discover automatic detection, filtering, and cleanup for consistent search results. Read more!

- Tags: internals
- Published: 2026-08-31

### [How ai-memory Manages Database Indexes: FTS5 Virtual Tables and Hybrid Retrieval](/akitaonrails/ai-memory/how-does-ai-memory-manage-database-indexes)

Discover how ai-memory leverages SQLite FTS5 virtual tables and graph traversal for efficient database indexing and hybrid retrieval, powered by Reciprocal Rank Fusion.

- Tags: internals
- Published: 2026-08-31

### [What Tables Are Included in the ai-memory SQLite Schema? Complete Reference Guide](/akitaonrails/ai-memory/what-tables-are-included-in-the-ai-memory-sqlite-schema)

Explore the ai-memory SQLite schema, detailing over 25 tables across core entities, pipelines, auto-improvement, and vector search. Find your complete reference guide here.

- Tags: api-reference
- Published: 2026-08-31

### [How ai-memory Handles Concurrent Reads and Writes to Its SQLite Database](/akitaonrails/ai-memory/how-does-ai-memory-handle-concurrent-reads-and-writes-to-its-sqlite-database)

Discover how ai-memory prevents SQLite locking issues. Learn about its single-writer actor for mutations and unlimited concurrent reads using WAL mode and a connection pool.

- Tags: internals
- Published: 2026-08-31

### [SQLite Architecture in ai-memory: Derived Index Pattern for AI Knowledge Bases](/akitaonrails/ai-memory/what-is-the-sqlite-architecture-used-by-ai-memory)

Explore the SQLite architecture in ai-memory. Discover how the derived index pattern and single-writer actor model ensure transactional consistency for your AI knowledge base.

- Tags: architecture
- Published: 2026-08-31

### [How to Manually Write a Permanent Decision Page in ai-memory](/akitaonrails/ai-memory/how-do-i-manually-write-a-permanent-decision-page-in-ai-memory)

Learn to manually write a permanent decision page in ai-memory. Create a markdown file in wiki/decisions/ with tier permanent frontmatter for lasting records.

- Tags: how-to-guide
- Published: 2026-08-31

### [How to Preview the Effects of the ai-memory Forget Sweep Without Deleting Data](/akitaonrails/ai-memory/how-can-i-preview-the-effects-of-the-ai-memory-forget-sweep)

Preview ai-memory forget sweep effects without data loss. Use dry run flags to see what would be deleted. Learn how to safeguard your data.

- Tags: how-to-guide
- Published: 2026-08-31

### [How to Force Consolidation of a Specific Session in ai-memory](/akitaonrails/ai-memory/how-do-i-force-a-consolidation-of-a-specific-session-in-ai-memory)

Force consolidation of a specific ai-memory session using the CLI command ai-memory consolidate --session <SESSION_ID>. Trigger the LLM pipeline to convert logs into a markdown wiki.

- Tags: how-to-guide
- Published: 2026-08-31

### [How to Query the Compiled ai-memory Wiki for Specific Information](/akitaonrails/ai-memory/how-can-i-query-the-compiled-ai-memory-wiki-for-specific-information)

Learn how to query the compiled ai-memory wiki using HTTP GET, the CLI, or the Rust API. Leverage FTS5 full-text search in SQLite for efficient information retrieval.

- Tags: how-to-guide
- Published: 2026-08-31

### [Understanding the 4 Retention Tiers for Data in ai-memory](/akitaonrails/ai-memory/what-are-the-different-retention-tiers-for-data-in-ai-memory)

Explore the 4 retention tiers for data in ai-memory: Working, Episodic, Semantic, and Procedural. Learn how each tier manages data persistence and relevance decay.

- Tags: deep-dive
- Published: 2026-08-31

### [How ai-memory Handles Data Retention and Page Decay: Exponential Decay in a SQLite Wiki](/akitaonrails/ai-memory/how-does-ai-memory-handle-data-retention-and-page-decay)

Discover how ai-memory handles data retention and page decay using exponential decay in SQLite. Learn about soft-deletion and purging for efficient data management.

- Tags: deep-dive
- Published: 2026-08-31

### [How to Use Obsidian to Edit the ai-memory Wiki: A Complete Guide](/akitaonrails/ai-memory/can-i-use-obsidian-to-edit-the-ai-memory-wiki)

Learn how to use Obsidian to edit the ai-memory wiki. This guide covers the simple process of using your favorite Markdown editor for project contributions.

- Tags: how-to-guide
- Published: 2026-08-31

### [How ai-memory Compiles Session Summaries into Markdown Wiki Pages: A Deep Dive into the Consolidation Pipeline](/akitaonrails/ai-memory/how-does-ai-memory-compile-session-summaries-into-markdown-wiki-pages)

Discover how ai-memory compiles session summaries into markdown wiki pages using a three stage pipeline that gathers observations, constructs LLM prompts and writes structured git versioned markdown.

- Tags: deep-dive
- Published: 2026-08-31

### [How AI Agent Session Observations Are Sanitized Before Storage in ai-memory](/akitaonrails/ai-memory/how-are-ai-agent-session-observations-sanitized-before-storage-in-ai-memory)

Discover how ai-memory sanitizes AI agent session observations using a multi-layer pipeline. Learn about regex compilation, credential scrubbing, type safety, and size limits before data storage.

- Tags: how-to-guide
- Published: 2026-08-31

### [The Lifecycle of an Observation in ai-memory: 8 Stages from Capture to Retrieval](/akitaonrails/ai-memory/what-is-the-lifecycle-of-an-observation-in-ai-memory)

Explore the 8 stages of an observation lifecycle in ai-memory. Understand capture, ingestion, consolidation, pruning, and retrieval for effective AI data management.

- Tags: internals
- Published: 2026-08-31

### [How ai-memory Stores AI Agent Session Observations: SQLite Persistence Architecture](/akitaonrails/ai-memory/how-does-ai-memory-store-ai-agent-session-observations)

Discover how ai-memory stores AI agent session observations using SQLite persistence and a type-safe sanitization boundary for secure data handling. Learn about its robust architecture.

- Tags: architecture
- Published: 2026-08-31

### [How ai-memory Distinguishes Between TTL Expires-At, Pinned Pages, and Feedback Signals in Retention](/akitaonrails/ai-memory/ai-memory-distinguish-expires-at-ttl-pinned-pages-feedback-retention)

Learn how ai-memory differentiates TTL expires-at, pinned pages, and feedback signals for effective retention. Understand the priority in page deletion and salience scoring.

- Tags: deep-dive
- Published: 2026-08-30

### [How ai-memory Implements SQLite Backup and Restore via Tar Archives Without Corrupting WAL-Mode Databases](/akitaonrails/ai-memory/ai-memory-backup-restore-tar-archives-sqlite-db-corruption)

Learn how ai-memory creates atomic, corruption-free tar.gz backups of live WAL-mode SQLite databases using the online backup API for reliable restore.

- Tags: how-to-guide
- Published: 2026-08-30

### [How the ai-memory-consolidate Recall-Eval Framework Scores Retrieval Relevance](/akitaonrails/ai-memory/ai-memory-consolidate-recall-eval-framework-score-retrieval-relevance)

Discover how the ai-memory-consolidate framework scores retrieval relevance using Recall@5. Compare FTS5 keyword search against hybrid search with Reciprocal Rank Fusion.

- Tags: deep-dive
- Published: 2026-08-30

### [How ai-memory's Clippy Workspace Lints Enforce unsafe_code and missing_docs](/akitaonrails/ai-memory/ai-memory-clippy-workspace-lints-unsafe-code-missing-docs)

Learn how ai-memory's clippy workspace lints enforce unsafe_code and missing_docs. Discover how Cargo lints and CI ensure a zero-unsafe, fully-documented codebase.

- Tags: how-to-guide
- Published: 2026-08-30

### [How ai-memory Implements MCP Client Activity Tracking via Bounded UTC-Day Buckets](/akitaonrails/ai-memory/ai-memory-mcp-client-activity-tracking-utc-day-buckets)

Discover how ai-memory tracks MCP client activity using bounded UTC-day buckets. Learn about buffering, background flushing, and memory-bounded overflow handling.

- Tags: deep-dive
- Published: 2026-08-30

### [How ai-memory Audit Log Attributes Writes to Specific DB Users vs Root Operators](/akitaonrails/ai-memory/ai-memory-audit-log-attribute-writes-db-users-root-operators)

Learn how the ai-memory audit log attributes writes to specific DB users versus root operators by examining author_id column entries. Understand your database activity.

- Tags: how-to-guide
- Published: 2026-08-30

### [How ai-memory Implements Forgot-Sweep TTL Deletion of Expired Wiki Pages](/akitaonrails/ai-memory/ai-memory-forgot-sweep-ttl-deletion-expired-wiki-pages)

Discover how ai-memory implements forgot-sweep TTL deletion for expired wiki pages. Learn about its two-phase expiration system for efficient page management.

- Tags: internals
- Published: 2026-08-30

### [How ai-memory Implements Decay Math and Salience-Scaled Retention for Forget-Sweep](/akitaonrails/ai-memory/ai-memory-decay-math-salience-scaled-retention-forget-sweep)

Discover how ai-memory uses decay math and salience-scaled retention to optimize forget-sweep. Learn how episodic pages survive based on age, access, feedback, and readership.

- Tags: internals
- Published: 2026-08-30

### [ai‑memory Authentication Ladder: From Static Bearer Tokens to OIDC Device‑Flow Tokens](/akitaonrails/ai-memory/ai-memory-auth-ladder-bearer-tokens-oidc-device-tokens)

Explore the ai-memory auth ladder, evolving from static bearer tokens to OIDC device-flow tokens for robust authentication. Learn how it maps requests to capability tiers.

- Tags: deep-dive
- Published: 2026-08-30

### [How ai-memory Implements Per-Session Auto-Scope Routing with the Session-Aware Bridge](/akitaonrails/ai-memory/ai-memory-per-session-auto-scope-routing-session-aware-bridge)

Learn how ai-memory implements per-session auto-scope routing. Discover how the session-aware bridge isolates sessions for efficient workspace and project management.

- Tags: deep-dive
- Published: 2026-08-30

### [ai-memory-cli Config::load() Path: Why Single-Pass Configuration Loading Matters](/akitaonrails/ai-memory/ai-memory-cli-config-load-path-no-second-read-path)

Understand the ai-memory-cli's single config::Config::load path. Discover how this method prevents environment desynchronization bugs by merging settings efficiently.

- Tags: internals
- Published: 2026-08-30

### [How the `ai-memory bootstrap` Command Collects Git Log, README, and Docs into Seed Wiki Pages](/akitaonrails/ai-memory/ai-memory-bootstrap-command-collect-git-log-readme-docs-seed-wiki)

Learn how the ai-memory bootstrap command gathers Git logs README and docs into seed wiki pages using a two-stage LLM pipeline. Discover the process for building your AI memory.

- Tags: how-to-guide
- Published: 2026-08-30

### [How ai-memory Implements the Karpathy-Style Consolidation Pipeline for Observations to Wiki Pages](/akitaonrails/ai-memory/ai-memory-karpathy-style-consolidation-pipeline-observations-wiki-pages)

Discover how ai-memory implements the Karpathy-style consolidation pipeline. Transform observations into version-controlled wiki pages with a three-stage LLM process.

- Tags: deep-dive
- Published: 2026-08-30

### [What the ai-memory Curator Maintenance Command Detects and Reports: A Complete Guide](/akitaonrails/ai-memory/ai-memory-curator-maintenance-command-detection-reporting)

Discover what the ai-memory curator maintenance command detects: cold pages, stale slots, duplicate titles, and dangling links. Get a complete health report for your project.

- Tags: how-to-guide
- Published: 2026-08-30

### [How ai-memory's Atomic Wiki Write Pipeline Interacts with the Git2 Watcher](/akitaonrails/ai-memory/ai-memory-atomic-wiki-write-pipeline-git2-watcher-interaction)

Learn how ai-memory's atomic wiki write pipeline uses temp files and atomic renames to interact with the Git2 watcher, ensuring only complete pages are committed.

- Tags: internals
- Published: 2026-08-30

### [How the Capture Allowlist Mode in ai-memory Inverts the Default Blocklist Behavior](/akitaonrails/ai-memory/ai-memory-capture-allowlist-mode-invert-blocklist-behavior)

Discover how ai-memory's capture allowlist mode inverts default blocklist behavior, recording only explicitly opted-in repositories for targeted memory capture. Learn more.

- Tags: how-to-guide
- Published: 2026-08-30

### [How ai‑memory's Per‑Operator Memory Slots Isolate Context Injection Between Shared‑Server Users](/akitaonrails/ai-memory/ai-memory-per-operator-memory-slots-isolate-context-injection)

Learn how ai-memory's per-operator memory slots isolate context injection for shared-server users. Discover deterministic namespace derivation, visibility filtering, and placement guards preventing cross-user slot injection.

- Tags: internals
- Published: 2026-08-30

### [How ai-memory's Managed Workstream Resumes Cross-Harness Sessions Transparently](/akitaonrails/ai-memory/how-does-ai-memory-managed-workstream-resume-cross-harness-sessions)

Learn how ai-memory's managed workstream transparently resumes cross-harness sessions using a server-side ledger and preparation protocol, preserving context and settings.

- Tags: how-to-guide
- Published: 2026-08-30

### [How the ai-memory Auto-Improvement Scheduler Approves Wiki Edits Without Human Review](/akitaonrails/ai-memory/ai-memory-auto-improvement-scheduler-approve-wiki-edits-without-human-review)

Discover how the ai-memory auto-improvement scheduler approves wiki edits automatically. Learn how to bypass human review and streamline your content updates.

- Tags: deep-dive
- Published: 2026-08-30

### [ai‑memory Retrieval Pipeline: FTS5 + Entity‑Match RRF + Graph‑Neighbor RRF Explained](/akitaonrails/ai-memory/ai-memory-fts5-entity-match-rrf-graph-neighbor-rrf-retrieval-pipeline)

Explore the ai-memory retrieval pipeline combining FTS5, entity-match RRF, and graph-neighbor RRF. Discover how this powerful system surfaces your most relevant wiki pages.

- Tags: deep-dive
- Published: 2026-08-30

### [How ai-memory Implements Per-Project Isolation Using `workspace_id`, `project_id`, `path` Tuples](/akitaonrails/ai-memory/how-does-ai-memory-implement-per-project-isolation-workspace-project-path)

Learn how ai-memory ensures per-project isolation. It uses workspace_id, project_id, path tuples as a canonical primary key for data and filesystem access.

- Tags: internals
- Published: 2026-08-30

### [How ai-memory's Sanitize Boundary Prevents Secrets from Entering the Store](/akitaonrails/ai-memory/how-does-ai-memory-sanitize-boundary-prevent-secrets-entering-store)

Discover how ai-memory's Sanitize Boundary prevents secrets from entering storage. Learn how its compile-time guarantee and wrapper scrub credentials with regex patterns, ensuring secure data persistence.

- Tags: security-guide
- Published: 2026-08-30

### [How ai-memory's SQLite Actor Enforces Write Ordering and Prevents Race Conditions](/akitaonrails/ai-memory/how-does-ai-memory-sqlite-actor-enforce-write-ordering-prevent-race-conditions)

Discover how ai-memory's SQLite actor serializes database writes using a single OS thread and rusqlite connection. Learn how this prevents race conditions and ensures data integrity.

- Tags: internals
- Published: 2026-08-30

### [How to Start the ai-memory HTTP+MCP Server: 3 Deployment Methods](/akitaonrails/ai-memory/how-to-start-ai-memory-http-mcp-server)

Easily start the ai-memory HTTP+MCP server with `ai-memory serve` or explore systemd and Docker deployment options. Get your AI memory project running quickly and efficiently.

- Tags: how-to-guide
- Published: 2026-08-28

### [How to Initialize a New ai-memory Data Directory: Complete Setup Guide](/akitaonrails/ai-memory/how-to-initialize-ai-memory-data-directory)

Initialize a new ai-memory data directory effortlessly. Run ai-memory init to set up Git version control, generate a cryptographic pepper, and create a default config file.

- Tags: how-to-guide
- Published: 2026-08-28

### [Complete Guide to ai-memory CLI Subcommands for Server, Wiki, and Session Management](/akitaonrails/ai-memory/ai-memory-cli-subcommands-operations)

Master ai-memory CLI subcommands for server, wiki, and session management. Explore 28+ modules for efficient operation and integration. Get the complete guide now.

- Tags: how-to-guide
- Published: 2026-08-28

### [How to Use `memory_lint` to Find Contradictions in AI Memory Wikis](/akitaonrails/ai-memory/ai-memory-using-memory-lint-for-contradictions)

Discover how to use memory_lint to find contradictions in AI memory wikis. This tool scans wiki pages for errors using rule-based checks and LLM analysis.

- Tags: how-to-guide
- Published: 2026-08-28

### [What Is the `memory_feedback` Tool and How Does It Work?](/akitaonrails/ai-memory/ai-memory-memory-feedback-tool-purpose)

Discover the memory_feedback tool a write-only MCP tool used by AI agents to record quality judgments on wiki pages, adjust salience scores, and flag stale content.

- Tags: how-to-guide
- Published: 2026-08-28

### [How the `memory_handoff` Tool Facilitates Agent Communication in AI-Memory](/akitaonrails/ai-memory/ai-memory-memory-handoff-tool-functionality)

Discover how the memory_handoff tool enables AI agent communication by persisting structured context snapshots in SQLite. Seamlessly pass working states between AI-coding agents.

- Tags: how-to-guide
- Published: 2026-08-28

### [ai-memory MCP Tools: Complete Guide to All 18 Available Tools](/akitaonrails/ai-memory/ai-memory-mcp-tool-surface-overview)

Explore all 18 ai-memory MCP tools for query, retrieval, session management, and more. This complete guide details every available single-call tool for your technical needs.

- Tags: how-to-guide
- Published: 2026-08-28

### [How ai‑memory Handles Pinned Pages and Their Exemption from Decay](/akitaonrails/ai-memory/ai-memory-pinned-pages-decay-exemption)

Discover how ai-memory protects pinned pages from decay. Learn how to exempt vital content from automatic sweeps using pinned: true in front-matter.

- Tags: deep-dive
- Published: 2026-08-28

### [Understanding the Memory Tiers in ai-memory: The M8 Policy Explained](/akitaonrails/ai-memory/ai-memory-memory-tiers-m8-policy)

Explore the four memory tiers in ai-memory Working Episodic Semantic and Procedural. Understand how the M8 policy dictates retention rules for efficient AI knowledge management.

- Tags: deep-dive
- Published: 2026-08-28

### [How Versioned Wiki Pages Are Managed in ai-memory: A Deep Dive](/akitaonrails/ai-memory/ai-memory-versioned-wiki-pages-management)

Discover how ai-memory manages versioned wiki pages using immutable versioning, SQLite, and Git. Explore atomic operations and automatic commits for a complete history.

- Tags: deep-dive
- Published: 2026-08-28

### [What Are the Key Tables in the ai-memory SQLite Schema? A Complete Architectural Guide](/akitaonrails/ai-memory/ai-memory-sqlite-schema-tables)

Explore the ai-memory SQLite schema architecture. Understand foundational tables like workspaces, projects, and sessions, plus auxiliary tables for advanced features.

- Tags: architecture
- Published: 2026-08-28

### [ai-Memory Data Directory Structure: Complete Guide to File Layout and Storage Subsystems](/akitaonrails/ai-memory/ai-memory-data-directory-structure)

Explore the ai-memory data directory structure. Understand the file layout and storage subsystems including wiki raw db models logs hook-spool and config files.

- Tags: deep-dive
- Published: 2026-08-28

### [How ai-memory Handles Memory Decay and Eviction: A Deep Dive into Salience-Based Forgetting](/akitaonrails/ai-memory/ai-memory-memory-decay-eviction-policy)

Discover how ai-memory manages memory decay and eviction using salience-based forgetting. Learn about exponential decay, tombstones, and data eviction for optimal knowledge management.

- Tags: deep-dive
- Published: 2026-08-28

### [How the Auto-Improvement Scheduler Works in ai-memory: A Deep Dive into Automated Session Review](/akitaonrails/ai-memory/ai-memory-auto-improvement-scheduler-workflow)

Discover how the ai-memory auto-improvement scheduler autonomously reviews sessions and suggests wiki edits. Learn more about this powerful background worker.

- Tags: deep-dive
- Published: 2026-08-28

### [The Role of LLM Consolidation in ai-memory: Transforming Observations Into Structured Knowledge](/akitaonrails/ai-memory/ai-memory-llm-consolidation-role)

Discover how LLM consolidation in ai-memory transforms raw session observations into structured, searchable wiki pages. Learn about the pipeline for persisting output as atomic wiki updates.

- Tags: deep-dive
- Published: 2026-08-28

### [How Session Summaries Are Generated in ai-memory: A Deep Dive into the Summary.json Lifecycle](/akitaonrails/ai-memory/ai-memory-session-summary-generation)

Discover how ai-memory generates session summaries. Learn about the atomic JSON writes to summary.json and their lifecycle in the transcript module.

- Tags: deep-dive
- Published: 2026-08-28

### [How ai-memory Sanitizes Incoming Hook Payloads: A Complete Technical Guide](/akitaonrails/ai-memory/ai-memory-hook-payload-sanitization)

Discover how ai-memory sanitizes incoming hook payloads. Learn about its Sanitizer struct for stripping secrets, removing control characters, truncating inputs, and enforcing type safety.

- Tags: how-to-guide
- Published: 2026-08-28

### [Data Flow for Lifecycle Hooks in ai-memory: HTTP Ingestion to Persistence Pipeline](/akitaonrails/ai-memory/ai-memory-lifecycle-hook-data-flow)

Explore the ai-memory data flow pipeline for lifecycle hooks Understand HTTP ingestion Axum routing policy filters rate limiting async persistence and session handoff

- Tags: architecture
- Published: 2026-08-28

### [How ai-memory Prevents Circular Dependencies Between Its Crates](/akitaonrails/ai-memory/ai-memory-crate-dependency-enforcement)

Learn how ai-memory prevents circular dependencies with a strict hierarchical architecture and automatic `cargo check` validation. Ensure robust crate relationships.

- Tags: internals
- Published: 2026-08-28

### [ai‑memory Crates Explained: A Complete Guide to the 9 Rust Crate Architecture](/akitaonrails/ai-memory/ai-memory-crate-layout-explained)

Explore the ai-memory Rust workspace and its 9 crates. Understand the architecture behind this long-term memory service for coding agents.

- Tags: deep-dive
- Published: 2026-08-28

### [How ai‑memory Handles Atomic Writes to the Markdown Wiki and SQLite Database](/akitaonrails/ai-memory/ai-memory-atomic-writes-wiki-sqlite)

Discover how ai-memory ensures atomic writes to Markdown and SQLite using a write-once-commit pattern. Learn about its tmp-rename-fsync and single-writer actor techniques for data integrity.

- Tags: internals
- Published: 2026-08-28

### [How ai-memory Uses a Two-Layer Model for Storing Data](/akitaonrails/ai-memory/ai-memory-two-layer-data-model)

Discover how ai-memory uses a two-layer model for data storage. Explore its raw markdown and SQLite layers for durability, portability, and fast retrieval. Learn more!

- Tags: deep-dive
- Published: 2026-08-28

### [How ai-memory Provides Persistent Cross-Session Memory for AI Coding Agents](/akitaonrails/ai-memory/how-ai-memory-provides-persistent-cross-session-memory)

Discover how ai-memory creates persistent cross-session memory for AI coding agents using a local markdown wiki and SQLite index. Keep your AI context across sessions.

- Tags: how-to-guide
- Published: 2026-08-28

### [How to Run the Recall-Eval Framework to Benchmark Retrieval Quality in AI-Memory](/akitaonrails/ai-memory/how-to-run-recall-eval-framework-benchmark-retrieval-quality)

Benchmark retrieval quality with the recall-eval framework. Install Rust, clone the AI-Memory repo, and run the command to test FTS5 and hybrid pipelines.

- Tags: how-to-guide
- Published: 2026-08-27

### [How to Tune LLM Consolidation Prompt Sizing for Maximum Context Utilization in ai-memory](/akitaonrails/ai-memory/how-to-tune-llm-consolidation-prompt-sizing-maximum-context-utilization)

Learn to tune LLM consolidation prompt sizing in ai-memory. Adjust DEFAULT_AUTO_IMPROVE_MAX_INPUT_TOKENS to maximize context utilization and fit more observations per request. Prevent overflows with careful limits.

- Tags: performance
- Published: 2026-08-27

### [Atomic Wiki Writes in ai-memory: How tmp+rename+fsync and Git Checkpoints Ensure Data Integrity](/akitaonrails/ai-memory/how-atomic-wiki-writes-use-tmp-rename-fsync-git-checkpoints)

Learn how atomic wiki writes in ai-memory leverage tmp+rename+fsync and Git checkpoints for crash-resistant file persistence and easy version history recovery.

- Tags: internals
- Published: 2026-08-27

### [Understanding the ai-memory Four-Rung Auth Ladder: From Root to DB-User Tokens](/akitaonrails/ai-memory/what-is-ai-memory-four-rung-auth-ladder-root-db-user-tokens)

Explore the ai-memory four-rung auth ladder, a hierarchical system from Anonymous to DB User tokens, ensuring secure request resolution. Learn how it works.

- Tags: deep-dive
- Published: 2026-08-27

### [How to Configure the Auto-Scope Resolver for Dynamic Workspace/Project Routing in ai-memory](/akitaonrails/ai-memory/how-to-configure-auto-scope-resolver-dynamic-workspace-project-routing)

Learn to configure the auto-scope resolver in ai-memory for dynamic workspace project routing. Use CLI flags, env variables, or a TOML file for easy setup.

- Tags: how-to-guide
- Published: 2026-08-27

### [How to Migrate Existing Projects Using ai-memory Bootstrap](/akitaonrails/ai-memory/how-to-migrate-existing-projects-using-ai-memory-bootstrap)

Migrate existing projects with ai-memory bootstrap. Scan your codebase, extract context from git history and docs, and build a searchable wiki without altering original files. Run ai-memory bootstrap now.

- Tags: migration-guide
- Published: 2026-08-27

### [How memory_feedback Signals Influence Page Salience and Decay Thresholds](/akitaonrails/ai-memory/how-memory_feedback-signal-influence-page-salience-decay-thresholds)

Discover how memory_feedback signals control page salience and decay thresholds in akitaonrails/ai-memory. Learn to manage agent memory retention and prevent data eviction.

- Tags: deep-dive
- Published: 2026-08-27

### [How to Set Up Per-Operator Memory Slots on Shared Servers](/akitaonrails/ai-memory/how-to-set-up-per-operator-memory-slots-shared-servers)

Learn how to set up per operator memory slots on shared servers with ai-memory. Enable private namespaces for each operator while maintaining shared access to common slots.

- Tags: how-to-guide
- Published: 2026-08-27

### [How to Debug the Managed-Workstream Ledger for Cross-Harness Continuity](/akitaonrails/ai-memory/how-to-debug-managed-workstream-ledger-cross-harness-continuity)

Debug the managed-workstream ledger for cross-harness continuity. Learn how this append-only SQLite log enables seamless session resumption and consistent transcripts across tool invocations.

- Tags: how-to-guide
- Published: 2026-08-27

### [How to Configure OpenAI, Voyage, and Ollama Embedding Providers for Vector Search in ai-memory](/akitaonrails/ai-memory/how-to-configure-embedding-providers-openai-voyage-ollama-vector-search-ai-memory)

Easily configure OpenAI, Voyage, or Ollama embedding providers for vector search in ai-memory. Set the AI_MEMORY_EMBEDDER variable, add API keys, and restart.

- Tags: how-to-guide
- Published: 2026-08-27

### [How to Set Up Per-Session MCP Routing for Concurrent Claude Code Sessions](/akitaonrails/ai-memory/how-to-set-up-per-session-mcp-routing-concurrent-claude-code-sessions)

Master per-session MCP routing for concurrent Claude Code sessions. Configure ai-memory with auto_scope.mode per_session and the MCP bridge to isolate each Claude Code window using CLAUDE_CODE_SESSION_ID.

- Tags: how-to-guide
- Published: 2026-08-27

### [How to Use memory_consolidate for Karpathy-Style LLM Wiki Compilation](/akitaonrails/ai-memory/how-to-use-memory_consolidate-karpathy-style-llm-wiki-compilation)

Learn to use memory_consolidate for Karpathy-style LLM wiki compilation. This tool compiles session observations into a structured markdown wiki, following Andrej Karpathy's LLM Wiki pattern.

- Tags: how-to-guide
- Published: 2026-08-27

### [How to Enable and Tune the Auto-Improvement Scheduler for Wiki Learning in ai-memory](/akitaonrails/ai-memory/how-to-enable-tune-auto-improvement-scheduler-wiki-learning-ai-memory)

Learn to enable and tune the auto-improvement scheduler for wiki learning in ai-memory. Configure scheduler settings to optimize LLM load and review responsiveness effectively.

- Tags: how-to-guide
- Published: 2026-08-27

### [How to Deploy ai-memory Behind a Caddy or Cloudflare TLS Reverse Proxy](/akitaonrails/ai-memory/how-to-deploy-ai-memory-behind-caddy-cloudflare-tls-reverse-proxy)

Easily deploy ai-memory behind Caddy or Cloudflare TLS reverse proxies. Follow our guide to secure your deployment with Docker Compose and essential environment variables.

- Tags: how-to-guide
- Published: 2026-08-27

### [How to Troubleshoot Hook Backpressure and HTTP 429 Saturation in ai-memory](/akitaonrails/ai-memory/how-to-troubleshoot-hook-backpressure-http-429-saturation-ai-memory)

Troubleshoot hook backpressure and HTTP 429 errors in akitaonrails/ai-memory. Learn how to prevent server saturation and unbounded memory growth. Optimize your ai-memory integration.

- Tags: troubleshooting-guide
- Published: 2026-08-27

### [Understanding the FTS5 + Entity-Match + Link-Neighbour RRF Retrieval Pipeline in ai-memory](/akitaonrails/ai-memory/what-is-fts5-entity-match-link-neighbor-rrf-retrieval-pipeline-ai-memory)

Explore the ai-memory retrieval pipeline combining FTS5, entity-match, and link-neighbor RRF for unified search ranking. Learn how these techniques create a deterministic result.

- Tags: deep-dive
- Published: 2026-08-27

### [How to Implement Cross-Agent Handoffs Between Claude Code and Codex in ai-memory](/akitaonrails/ai-memory/how-to-implement-cross-agent-handoffs-claude-code-codex-ai-memory)

Implement cross-agent handoffs between Claude Code and Codex in ai-memory using MCP tools. Seamlessly transfer context and maintain continuity across AI sessions.

- Tags: how-to-guide
- Published: 2026-08-27

### [How to Set Up Multi-User Authentication with OIDC Device Tokens in ai-memory](/akitaonrails/ai-memory/how-to-set-up-multi-user-authentication-oidc-device-tokens-ai-memory)

Set up multi-user authentication in ai-memory using OIDC device tokens. Securely isolate user data with a simple login command for enhanced privacy and access control.

- Tags: how-to-guide
- Published: 2026-08-27

### [How to Configure Capture Exclusions Using .ai-memory.toml Marker Files](/akitaonrails/ai-memory/how-to-configure-capture-exclusions-ai-memory-toml-marker-files)

Learn how to configure capture exclusions using .ai-memory.toml marker files. Exclude specific files from observation logging by defining ignore paths in your TOML configuration.

- Tags: how-to-guide
- Published: 2026-08-27

### [How to Customize Decay and Retention Policies for ai-memory Episodic Memory](/akitaonrails/ai-memory/how-to-customize-decay-retention-policies-ai-memory-episodic-memory-tiers)

Customize ai-memory episodic memory decay and retention policies by configuring DecayParams. Tune exponential decay, access reinforcement, and eviction thresholds for optimal performance.

- Tags: how-to-guide
- Published: 2026-08-27

### [How Capture Exclusions Work in ai‑memory Using `.ai‑memory.toml`](/akitaonrails/ai-memory/how-do-capture-exclusions-work-in-ai-memory-with-.ai-memory.toml)

Learn how to use capture exclusions in ai-memory with .ai-memory.toml. Configure ignore_paths to prevent specific files from being captured by the ai-memory pipeline.

- Tags: how-to-guide
- Published: 2026-08-26

### [What Is the MCP Tool Surface in ai‑memory?](/akitaonrails/ai-memory/what-is-the-purpose-of-the-mcp-tool-surface-in-ai-memory)

Discover the MCP Tool Surface in ai-memory, a public API that grants AI agents access to read, write, and manage long-term memory via 17 typed tools for efficient data interaction.

- Tags: internals
- Published: 2026-08-26

### [How the `ai-memory run` Command Manages Workstreams: A Deep Dive into the 11-Phase Lifecycle](/akitaonrails/ai-memory/how-does-the-ai-memory-run-command-manage-workstreams)

Discover how the ai-memory run command manages workstreams through its 11-phase lifecycle. Learn about repository fingerprinting, transcript import, and harness process orchestration.

- Tags: deep-dive
- Published: 2026-08-26

### [Automatic vs Manual Handoffs in ai-memory: Key Differences Explained](/akitaonrails/ai-memory/what-is-the-difference-between-automatic-and-manual-handoffs-in-ai-memory)

Understand automatic vs manual handoffs in ai-memory. Discover how SessionEnd hooks differ from the memory_handoff_begin MCP tool for directory level and project-wide handoffs.

- Tags: deep-dive
- Published: 2026-08-26

### [How the ai-memory Handoff System Facilitates Cross-Agent Communication](/akitaonrails/ai-memory/how-does-the-ai-memory-handoff-system-facilitate-cross-agent-communication)

Learn how the ai-memory handoff system enables seamless cross-agent communication by persisting and retrieving structured context. Maintain workflow continuity effortlessly.

- Tags: how-to-guide
- Published: 2026-08-26

### [How to Enable LLM Reranking for ai-memory Queries: Complete Configuration Guide](/akitaonrails/ai-memory/how-can-i-enable-llm-reranking-for-ai-memory-queries)

Easily enable LLM reranking for ai-memory queries by setting environment variables. This complete guide shows you how to configure your LLM provider for automatic activation without code changes.

- Tags: how-to-guide
- Published: 2026-08-26

### [How Reciprocal Rank Fusion Works in ai-memory: Multi-Stream Retrieval Explained](/akitaonrails/ai-memory/how-does-reciprocal-rank-fusion-work-in-ai-memory-retrieval)

Understand how Reciprocal Rank Fusion in ai-memory blends multiple retrieval streams for superior relevance. Learn the RRF formula and its application.

- Tags: deep-dive
- Published: 2026-08-26

### [Ai‑memory Query Pipeline Retrieval Methods: Hybrid Search with FTS5, Entities, and Graph Expansion](/akitaonrails/ai-memory/what-retrieval-methods-does-the-ai-memory-query-pipeline-use)

Discover the ai-memory query pipeline retrieval methods. Learn about FTS5 search, entity matching, graph expansion, and vector similarity fused with RRF and LLM reranking.

- Tags: deep-dive
- Published: 2026-08-26

### [How Pinned Pages Are Handled by the ai-memory Decay Policy: Complete Immunity Guide](/akitaonrails/ai-memory/how-are-pinned-pages-handled-by-the-ai-memory-decay-policy)

Discover how pinned pages in akitaonrails ai-memory bypass decay policies. Learn how to ensure your important data remains accessible and immune to automatic deletion.

- Tags: deep-dive
- Published: 2026-08-26

### [How to Configure Decay Parameters in ai-memory: A Complete Guide](/akitaonrails/ai-memory/how-can-i-configure-the-decay-parameters-in-ai-memory)

Learn to configure decay parameters in ai-memory using TOML, environment variables, CLI flags, or programmatically. Control content retention and forgetting rates effectively.

- Tags: how-to-guide
- Published: 2026-08-26

### [How ai-memory Implements Its Memory Tier Decay Model: A Technical Deep Dive](/akitaonrails/ai-memory/how-does-ai-memory-implement-its-memory-tier-decay-model)

Discover how ai-memory implements its memory tier decay model. Explore the deterministic mathematical function using exponential decay and logarithmic reinforcement for retention scores. Learn more.

- Tags: deep-dive
- Published: 2026-08-26

### [Content Limits for Different Types of Hook Events in ai-memory](/akitaonrails/ai-memory/what-are-the-content-limits-for-different-types-of-hook-events-in-ai-memory)

Discover content limits for ai-memory hook events. Learn payload size caps for session start/end (2 MiB) and user prompt/post-tool-use (4 MiB) to optimize your AI applications.

- Tags: api-reference
- Published: 2026-08-26

### [How ai-memory Handles Agent Lifecycle Events and Observations: A Technical Deep Dive](/akitaonrails/ai-memory/how-does-ai-memory-handle-agent-lifecycle-events-and-observations)

Explore how ai-memory manages agent lifecycle events and observations. Learn about its unique approach to capturing every execution step for complete session reconstruction.

- Tags: deep-dive
- Published: 2026-08-26

### [What Is the Handoffs Table in ai-memory? Purpose and Implementation](/akitaonrails/ai-memory/what-is-the-purpose-of-the-handoffs-table-in-ai-memory)

Discover the ai-memory handoffs table, the core SQLite structure for cross-agent continuity. Learn how it stores session snapshots for seamless collaboration.

- Tags: internals
- Published: 2026-08-26

### [How ai-memory Manages Links and Cross-References: The Rust Wiki Engine Architecture](/akitaonrails/ai-memory/how-are-links-and-cross-references-managed-in-ai-memory)

Learn how ai-memory manages links and cross-references by converting Markdown into canonical LinkTarget structs, supporting workspace and project boundaries.

- Tags: architecture
- Published: 2026-08-26

### [What Information Is Stored in the `pages` Table of the ai‑memory SQLite Database?](/akitaonrails/ai-memory/what-information-is-stored-in-the-pages-table-of-the-ai-memory-sqlite-database)

Discover what information the ai-memory SQLite pages table stores including content metadata tier classification vector embeddings and full version history.

- Tags: api-reference
- Published: 2026-08-26

### [How ai-memory Prevents Read-After-Write Inconsistency: A Deep Dive into its SQLite Architecture](/akitaonrails/ai-memory/how-does-ai-memory-prevent-read-after-write-inconsistency)

Learn how ai-memory prevents read-after-write inconsistency. Discover its single-writer SQLite architecture and mpsc channel for guaranteed data integrity.

- Tags: deep-dive
- Published: 2026-08-26

### [How ai-memory Keeps Its SQLite Index Consistent with the Markdown Wiki](/akitaonrails/ai-memory/how-is-the-sqlite-index-kept-consistent-with-the-markdown-wiki-in-ai-memory)

Discover how ai-memory maintains SQLite index consistency with its Markdown wiki using atomic writes, automatic rollbacks, and startup re-indexing. Learn about its robust data integrity approach.

- Tags: internals
- Published: 2026-08-26

### [What Are the Two Layers in the ai-memory Storage Model?](/akitaonrails/ai-memory/what-are-the-two-layers-in-the-ai-memory-storage-model)

Discover the two layers in the ai-memory storage model: a Wiki layer for source of truth and a SQLite layer for efficient search and indexing. Learn how this dual-architecture works.

- Tags: internals
- Published: 2026-08-26

### [How ai-memory Implements Long-Term Memory for AI Coding Agents](/akitaonrails/ai-memory/how-does-ai-memory-handle-long-term-memory-for-ai-coding-agents)

Discover how ai-memory builds long-term memory for AI coding agents using tiered Markdown files, SQLite FTS5, and semantic indexing for durable, retrievable knowledge.

- Tags: how-to-guide
- Published: 2026-08-26

### [Structure of the LLM Wiki in ai-memory: Directory Layout, API, and Safety Guarantees](/akitaonrails/ai-memory/what-is-the-structure-of-the-llm-wiki-in-ai-memory)

Explore the LLM wiki structure in ai-memory. Discover its hierarchical directory layout, APIs for atomic writes, and robust safety guarantees for your data.

- Tags: architecture
- Published: 2026-08-26

### [How to Set Up ai-memory as a Self-Contained Rust Binary: Complete Native Installation](/akitaonrails/ai-memory/how-to-set-up-ai-memory-as-a-self-contained-rust-binary)

Install ai-memory as a self-contained Rust binary. Compile from source and run commands to create a native SQLite memory server for coding agents. Full native installation guide.

- Tags: how-to-guide
- Published: 2026-08-26

### [Understanding the ai-memory Bootstrap Command Flow for Importing Existing Project History](/akitaonrails/ai-memory/what-bootstrap-command-flow-importing-existing-project-history)

Learn the ai-memory bootstrap command flow for importing project history. Discover how it prioritizes sources, summarizes with LLMs, and creates a manifest for efficient data integration.

- Tags: how-to-guide
- Published: 2026-08-25

### [How the MCP /hook Endpoint Handles Rate Limiting and Backpressure in ai-memory](/akitaonrails/ai-memory/how-mcp-hook-endpoint-handles-rate-limiting-backpressure)

Learn how the ai-memory MCP /hook endpoint manages rate limiting and backpressure using an IngestRateLimiter and tokio Semaphore to prevent overload and ensure smooth processing.

- Tags: how-to-guide
- Published: 2026-08-25

### [Understanding the Config Load Path in ai-memory: Why a Single Source of Truth Matters](/akitaonrails/ai-memory/what-config-load-path-why-only-one-config-read-path)

Discover the ai-memory config load path and why a single source of truth streamlines your application. Learn how immutable config ensures consistency.

- Tags: internals
- Published: 2026-08-25

### [How Cross-Project Links Work in AI Memory: Syntax, Resolution, and the Dangling Link Curator Check](/akitaonrails/ai-memory/how-cross-project-links-work-dangling-link-curator-check)

Understand cross-project links in AI Memory. Learn the `[[project:path.md]]` syntax and how the dangling link curator check finds broken references to ensure your AI Memory remains organized and accurate.

- Tags: deep-dive
- Published: 2026-08-25

### [How Embedding Backfill Works for Existing Wiki Pages in ai-memory](/akitaonrails/ai-memory/how-embedding-backfill-work-existing-wiki-pages)

Discover how ai-memory's embedding backfill efficiently updates wiki pages. Learn about scanning, deduplication, batch generation, and atomic writes for seamless vector management.

- Tags: deep-dive
- Published: 2026-08-25

### [Authority-Aware Recall System: Tier-Pinned Pages and Front-Matter Tags in ai-memory](/akitaonrails/ai-memory/what-authority-aware-recall-system-tier-pinned-frontmatter-tags)

Discover the authority-aware recall system in ai-memory. Learn how tier-pinned pages and front-matter tags boost high-authority content retrieval.

- Tags: deep-dive
- Published: 2026-08-25

### [How the MCP Client Activity Endpoint Tracks Usage by Client Type in ai-memory](/akitaonrails/ai-memory/how-mcp-client-activity-endpoint-track-usage-client-type)

Discover how the MCP client activity endpoint in ai-memory tracks tool usage by client type using an in-memory buffer flushing to SQLite. Access 7-day and 30-day rollups.

- Tags: how-to-guide
- Published: 2026-08-25

### [SessionEnd Hook Synthesis vs finalize-session Command: Key Differences in ai-memory](/akitaonrails/ai-memory/difference-sessionend-hook-synthesis-finalize-session-command)

Discover the key differences between SessionEnd hook synthesis and finalize-session command in ai-memory. Understand their distinct trigger methods and agent compatibility for optimal use.

- Tags: deep-dive
- Published: 2026-08-25

### [How the ai-memory Server Sanitizes Untrusted Hook Payloads Before Storage](/akitaonrails/ai-memory/how-server-sanitizes-untrusted-hook-payloads-before-storage)

Learn how the ai-memory server sanitizes untrusted hook payloads. It scrubs control characters, redacts secrets, limits length, and uses allow-lists before storing data.

- Tags: how-to-guide
- Published: 2026-08-25

### [How the LLM Reranker Integrates with ai-memory’s Retrieval Pipeline](/akitaonrails/ai-memory/how-reranker-llm-pass-integrates-retrieval-pipeline)

Discover how the LLM reranker integrates into akitaonrails/ai-memory's retrieval pipeline as a final relevance scoring layer to semantically reorder results for improved accuracy.

- Tags: internals
- Published: 2026-08-25

### [Data Flow from Lifecycle Hooks to Wiki Page Compilation in ai-memory](/akitaonrails/ai-memory/data-flow-lifecycle-hooks-wiki-page-compilation)

Understand the ai-memory data flow from lifecycle hooks to wiki page compilation. See how shell hooks, Rust router, and SQLite actor create atomic HTML pages.

- Tags: deep-dive
- Published: 2026-08-25

### [How the Forget Sweep Handles TTL Expiration Versus Cold Threshold Eviction in ai-memory](/akitaonrails/ai-memory/how-forget-sweep-handles-ttl-expiration-cold-threshold-eviction)

Understand how the forget sweep handles TTL expiration versus cold threshold eviction in ai-memory. Discover the differences in deletion processes and their impact on data.

- Tags: internals
- Published: 2026-08-25

### [Understanding Per-Operator Memory Slots and Per-User Isolation in ai-memory](/akitaonrails/ai-memory/what-per-operator-memory-slots-feature-how-per-user-isolation-work)

Learn how ai-memory's per-operator memory slots and per-user isolation provide private, namespaced workspaces for authenticated users. Discover effective data isolation techniques.

- Tags: deep-dive
- Published: 2026-08-25

### [How the MCP Server Routes Requests to the Correct Workspace and Project Scope](/akitaonrails/ai-memory/how-mcp-server-routes-requests-correct-workspace-project-scope)

Understand how the MCP server routes requests to the correct workspace and project scope using a strict precedence chain of ScopeResolver helpers. Learn more.

- Tags: architecture
- Published: 2026-08-25

### [How Managed Workstreams Enable Cross-Harness Continuity in ai-memory](/akitaonrails/ai-memory/how-managed-workstreams-implemented-cross-harness-continuity)

Discover how managed workstreams in akitaonrails/ai-memory ensure cross-harness continuity. Learn how these workstreams enable seamless migration between diverse AI coding agents with an immutable event ledger.

- Tags: internals
- Published: 2026-08-25

### [Memory Consolidate vs Memory Auto-Improve in ai-memory: Key Differences Explained](/akitaonrails/ai-memory/difference-between-memory-consolidate-memory-auto-improve)

Understand memory consolidate vs memory auto-improve in ai-memory. Discover how consolidate updates session narratives and auto-improve builds reusable knowledge for your project wiki.

- Tags: deep-dive
- Published: 2026-08-25

### [How OIDC Device Authentication Works for Native Hook Commands in AI-Memory](/akitaonrails/ai-memory/how-oidc-device-authentication-work-native-hook-commands)

Learn how AI-Memory CLI secures native hook commands with OIDC device authentication. Discover token storage and bearer token attachment for robust identity management.

- Tags: deep-dive
- Published: 2026-08-25

### [How the AI-Memory Wiki Handles Atomic Writes and Git Version Control](/akitaonrails/ai-memory/how-wiki-handles-atomic-writes-git-version-control)

Discover how the ai-memory wiki ensures crash-safe persistence and audit history using atomic writes and Git version control for every markdown page.

- Tags: internals
- Published: 2026-08-25

### [How the Decay Math Formula and Retention Scoring Work in ai-memory](/akitaonrails/ai-memory/what-decay-math-formula-how-retention-scoring-work)

Understand the decay math formula and retention scoring in ai-memory. Discover how exponential time decay and access reinforcement determine episodic page eviction.

- Tags: internals
- Published: 2026-08-25

### [How Capture Exclusions Work with .ai-memory.toml Marker Files](/akitaonrails/ai-memory/how-capture-exclusions-work-ai-memory-toml-marker-files)

Learn how .ai-memory.toml marker files enable capture exclusions using glob patterns in the ignore_paths array. Control what gets captured efficiently.

- Tags: how-to-guide
- Published: 2026-08-25

### [How the Auto-Improvement Scheduler Handles Concurrent Projects Without Blocking in ai-memory](/akitaonrails/ai-memory/how-auto-improvement-scheduler-handles-concurrent-projects-without-blocking)

Discover how the auto-improvement scheduler handles concurrent projects without blocking in ai-memory. Learn about state scoping and atomic claim tables for efficient session processing.

- Tags: internals
- Published: 2026-08-25

### [How FTS5, Entity-Match RRF, and Vector Similarity Work Together in ai-memory's memory_query](/akitaonrails/ai-memory/relationship-fts5-entity-match-rrf-vector-similarity-memory-query)

Discover how FTS5, entity-match RRF, and vector similarity combine in ai-memory's memory_query for powerful hybrid retrieval and unified relevance scoring.

- Tags: deep-dive
- Published: 2026-08-25

### [How the Single-Writer SQLite Actor Pattern Works in ai-memory-store](/akitaonrails/ai-memory/how-does-single-writer-sqlite-actor-pattern-work-ai-memory-store)

Discover how the single-writer SQLite actor pattern in ai-memory-store serializes mutations via an OS thread and uses a reader pool for concurrent queries. Learn efficient SQLite management.

- Tags: internals
- Published: 2026-08-25

### [memory_lint Tool in ai-memory: Detecting Stale Pages and Dangling Cross-Project Links](/akitaonrails/ai-memory/memory-lint-tool-stale-pages-dangling-links)

ai-memory's memory_lint tool finds stale pages via front-matter and content checks. It also detects dangling cross-project links by validating markdown targets against the SQLite index.

- Tags: how-to-guide
- Published: 2026-08-23

### [How the `[slots] per_user = true` Option Limits Prompt Injection Without Changing Page Access](/akitaonrails/ai-memory/ai-memory-slots-per-user-prompt-injection)

Discover how the `slots` per_user = true option in ai-memory secures against prompt injection by namespacing slot writes privately without altering page access.

- Tags: security
- Published: 2026-08-23

### [ai-Memory Multi-User Authentication: Understanding the Bearer Token Ladder and DB User System](/akitaonrails/ai-memory/ai-memory-multi-user-auth-bearer-tokens-db-users)

Explore ai-memory's multi-user authentication: bearer tokens, DB users, and its four-rung ladder with fallbacks. Secure your AI applications effectively.

- Tags: deep-dive
- Published: 2026-08-23

### [How the ai-memory Hook Command Spools Events with Idempotency Keys](/akitaonrails/ai-memory/ai-memory-hook-command-idempotency-keys)

Discover how the ai-memory hook command spools events with unique UUID ingest keys. Learn how servers deduplicate observations during network retries using idempotency keys.

- Tags: how-to-guide
- Published: 2026-08-23

### [How the Optional Per-User Slot System Isolates Memory Slots per Operator in ai-memory](/akitaonrails/ai-memory/ai-memory-per-user-slot-system-isolation)

Learn how the optional per user slot system in akitaonrails ai-memory isolates memory slots per operator. Discover how to manage individual operator memory access.

- Tags: internals
- Published: 2026-08-23

### [How the ai-memory Scope Resolution System Handles Missing Workspaces and Projects](/akitaonrails/ai-memory/ai-memory-scope-resolution-missing-workspaces-projects)

Discover how the ai-memory scope resolution system manages missing workspaces and projects with a fail-closed, create-on-write policy. Learn about error handling and silent creation for authorized writes.

- Tags: how-to-guide
- Published: 2026-08-23

### [How the memory_feedback Tool Impacts Page Retention and Salience in ai-memory](/akitaonrails/ai-memory/memory-feedback-tool-impact-page-retention-salience)

Discover how the memory_feedback tool in ai-memory enhances page retention and salience by adjusting scores based on user input. Learn how helpful content gets prioritized and stale content is managed.

- Tags: performance
- Published: 2026-08-23

### [Decay Retention Formula in ai-memory-store: How It Calculates Page Eviction Scores](/akitaonrails/ai-memory/ai-memory-store-decay-retention-formula)

Understand the decay retention formula in ai-memory-store. Learn how it calculates page eviction scores using salience and access frequency to optimize memory.

- Tags: deep-dive
- Published: 2026-08-23

### [How the Auto-Improvement Scheduler Reviews Newly Completed Sessions in ai-memory](/akitaonrails/ai-memory/how-auto-improvement-scheduler-reviews-sessions)

Discover how the auto-improvement scheduler in akitaonrails/ai-memory reviews completed sessions. Learn about LLM-driven review and wiki proposal staging.

- Tags: internals
- Published: 2026-08-23

### [Cross-Agent Handoffs in ai-memory: How Claude Code, Codex, and Other Agents Transfer Context Seamlessly](/akitaonrails/ai-memory/how-does-ai-memory-handle-cross-agent-handoffs)

Discover how ai-memory enables seamless cross-agent handoffs. Claude Code, Codex, and other agents automatically resume conversational context using handoff MCP tools and SwessionStart hooks.

- Tags: how-to-guide
- Published: 2026-08-23

### [Understanding ai-memory Workstream Storage: The workstream_events Table and raw/workstreams JSONL Segments](/akitaonrails/ai-memory/purpose-of-workstream-events-table-and-raw-workstreams-jsonl-segments)

Explore the workstream_events table for searchable transcript logs and raw/workstreams JSONL for immutable payload archives in akitaonrails/ai-memory. Understand your data flow.

- Tags: internals
- Published: 2026-08-22

### [How ai-Memory Ensures Session Continuity Across Different Harnesses](/akitaonrails/ai-memory/how-ai-memory-ensures-session-continuity-across-harnesses)

Learn how ai-memory ensures session continuity across Claude Code and Codex by using a unified launch plan and managed workstream ledger to preserve session IDs.

- Tags: deep-dive
- Published: 2026-08-22

### [How ai-memory `run <harness>` Manages Workstream Sessions and Visible Events](/akitaonrails/ai-memory/how-ai-memory-run-harness-manages-workstream-sessions)

Discover how ai-memory run <harness> manages workstream sessions by acquiring leases, preparing event deltas, and orchestrating cross-harness context via environment variables and an immutable SQLite ledger.

- Tags: how-to-guide
- Published: 2026-08-22

### [How Feedback Signals Are Attached to Page Versions in ai-memory](/akitaonrails/ai-memory/how-feedback-signals-attached-to-page-versions)

Learn how ai-memory attaches feedback signals like helpful or stale to specific page versions using immutable rows in the page_feedback table. Understand versioned feedback.

- Tags: internals
- Published: 2026-08-22

### [How `memory_consolidate` with `multi_page: true` Rewrites Sessions into Atomic Multi-Page Updates in ai-memory](/akitaonrails/ai-memory/effect-of-memory-consolidate-multi-page-true)

Learn how memory_consolidate with multi_page true transforms sessions into atomic multi-page updates in ai-memory via a single LLM request and SQLite transaction.

- Tags: internals
- Published: 2026-08-22

### [Destructive MCP Tools in ai-memory: Administrative Operations Reference](/akitaonrails/ai-memory/available-destructive-category-mcp-tools-in-ai-memory)

Discover destructive MCP tools in ai-memory like purge project, delete workspace, and reset. These admin endpoints modify or delete wiki data. Learn more!

- Tags: api-reference
- Published: 2026-08-22

### [Complete Guide to Read Category MCP Tools in ai-memory](/akitaonrails/ai-memory/available-read-category-mcp-tools-in-ai-memory)

Explore 17 read-only MCP tools in akitaonrails/ai-memory. Safely query the SQLite store via the /mcp endpoint without data mutation for efficient agent interactions.

- Tags: how-to-guide
- Published: 2026-08-22

### [How to List and Understand the 18 MCP Tools in ai-memory](/akitaonrails/ai-memory/how-to-list-and-understand-ai-memory-mcp-tools)

Discover how to list and understand the 18 MCP tools in akitaonrails/ai-memory. Enhance AI agent capabilities with full-text search, wiki management, and long-term memory.

- Tags: how-to-guide
- Published: 2026-08-22

### [What Happens When the Scope Is Missing During Read, Search, or Embed Operations in ai-memory](/akitaonrails/ai-memory/what-happens-during-read-search-embed-missing-scope)

Learn what happens when the scope is missing in ai-memory read search or embed operations. Discover the StoreError::MissingScope error and why database access is prevented.

- Tags: how-to-guide
- Published: 2026-08-22

### [How ai-memory Resolves Scope Using the 3-Tuple Identity Model (workspace_id, project_id, path)](/akitaonrails/ai-memory/how-ai-memory-resolves-scope-using-3-tuple-identity-model)

Learn how ai-memory resolves scope using its 3-tuple identity model (workspace_id, project_id, path). Discover how the ScopeResolver converts names to UUID identifiers for precise operations.

- Tags: how-to-guide
- Published: 2026-08-22

### [What Is the Default Value for `breadth_weight` in ai-memory's Decay Configuration?](/akitaonrails/ai-memory/default-value-for-breadth-weight-in-ai-memory-decay-configuration)

Discover the default breadth_weight value in ai-memory's decay configuration. Learn how its 0.0 setting impacts retention scores and when to adjust it for better reinforcement.

- Tags: api-reference
- Published: 2026-08-22

### [How Pinned Pages in ai-memory Are Exempt from Memory Decay](/akitaonrails/ai-memory/how-are-pinned-pages-exempt-from-memory-decay)

Discover how pinned pages in ai-memory bypass memory decay. Learn how the is_decayable function protects these crucial pages from the consolidation sweep.

- Tags: internals
- Published: 2026-08-22

### [What Happens When an Episodic Page’s Retention Falls Below the Cold Threshold in ai-memory](/akitaonrails/ai-memory/what-happens-when-episodic-page-retention-below-cold-threshold)

Discover what happens when an episodic page's retention falls below the cold threshold in ai-memory. Learn how the system evicts cold pages, deleting files and writing decay tombstones.

- Tags: internals
- Published: 2026-08-22

### [Understanding the Exponential Retention Formula for Memory Decay in ai-memory](/akitaonrails/ai-memory/explain-exponential-retention-formula-for-memory-decay)

Explore the exponential retention formula in ai-memory. Learn how it calculates memory salience, discounts scores by age and access, and uses breadth weight and user feedback to boost retention.

- Tags: deep-dive
- Published: 2026-08-22

### [How ai-memory Enforces Hard Content Limits for Different Observation Types](/akitaonrails/ai-memory/how-ai-memory-handles-hard-content-limits-for-observations)

Discover how ai-memory enforces hard content limits for observations. Learn about byte, count, and token thresholds to manage your data effectively.

- Tags: how-to-guide
- Published: 2026-08-22

### [Understanding the `Sanitized<NewObservation>` Type in ai‑memory's Security Model](/akitaonrails/ai-memory/role-of-sanitized-newobservation-type-in-ai-memory-security-model)

Discover how ai-memory's Sanitized<NewObservation> type uses Rust's compile-time checks to secure your data, preventing accidental credential leaks before storage.

- Tags: internals
- Published: 2026-08-22

### [How ai-memory's Privacy Strip Boundary Sanitizes Untrusted Hook Payloads](/akitaonrails/ai-memory/how-ai-memory-privacy-strip-boundary-sanitizes-untrusted-hook-payload-text)

Learn how ai-memory's privacy strip boundary sanitizes untrusted hook payloads using regex redaction, an allow-list, and an opaque type system to protect secrets from storage.

- Tags: internals
- Published: 2026-08-22

### [Maximum Byte Size for User Prompts and Post‑Compaction Summaries in ai‑memory: The 16 KiB Limit](/akitaonrails/ai-memory/max-byte-size-for-user-prompts-and-post-compaction-summaries)

Discover the 16 KiB byte size limit for user prompts and post-compaction summaries in akitaonrails/ai-memory. Learn why this limit ensures safe observation storage.

- Tags: deep-dive
- Published: 2026-08-22

### [How ai-memory Ensures Transactional Consistency for Index Updates](/akitaonrails/ai-memory/how-ai-memory-ensures-transactional-consistency-for-index-updates)

ai-memory guarantees transactional consistency for index updates by routing all writes through a single-writer actor, ensuring atomic SQLite commits and automatic rollbacks.

- Tags: internals
- Published: 2026-08-22

### [How Foreign Keys Are Enforced in ai-memory's SQLite Database](/akitaonrails/ai-memory/how-are-foreign-keys-enforced-in-ai-memory-sqlite-database)

Discover how ai-memory enforces foreign key constraints in SQLite using PRAGMA foreign_keys. Learn about its strategic disabling during migrations and re-enabling for robust data integrity.

- Tags: how-to-guide
- Published: 2026-08-22

### [What Is WAL Mode in ai‑memory’s Storage Engine?](/akitaonrails/ai-memory/purpose-of-wal-mode-in-ai-memory-storage-engine)

Discover WAL mode in ai-memory's storage engine. It offers unlimited concurrent readers and crash-safe atomicity for high-throughput reads and serialized mutations.

- Tags: internals
- Published: 2026-08-22

### [How the Single-Writer SQLite Actor in ai-memory Prevents Write Races](/akitaonrails/ai-memory/how-does-single-writer-sqlite-actor-prevent-write-races)

Learn how the ai-memory crate's single-writer SQLite actor prevents write races. It serializes commands via an async mpsc channel for safe, single-transaction execution.

- Tags: internals
- Published: 2026-08-22

### [Understanding the ai-memory Crate Layout: A Complete Guide to the 9-Crate Workspace](/akitaonrails/ai-memory/what-is-the-crate-layout-of-the-ai-memory-project-and-the-purpose-of-each-crate)

Explore the ai-memory Rust workspace and its 9-crate layout. Understand each crate's purpose from domain types to LLM abstractions and learn about its SQLite actor and atomic wiki write guarantees.

- Tags: deep-dive
- Published: 2026-08-21

### [How to Perform a Backup of ai-memory Data Using the CLI](/akitaonrails/ai-memory/how-can-i-perform-a-backup-of-the-ai-memory-data-using-the-cli)

Easily backup ai-memory data with the CLI. Learn to create a gzipped tarball of your SQLite snapshot and wiki directory by accessing the /admin/backup endpoint.

- Tags: how-to-guide
- Published: 2026-08-21

### [What Is a Decay Tombstone in ai‑memory’s Eviction Process?](/akitaonrails/ai-memory/what-is-the-decay-tombstone-in-ai-memorys-eviction-process)

Understand decay tombstones in ai-memory's eviction process. Learn how these soft-delete markers enable safe ancestry tracking and delayed deletion for memory management.

- Tags: deep-dive
- Published: 2026-08-21

### [How the Forget Sweep Mechanism Works in ai-memory for Expiring Pages](/akitaonrails/ai-memory/how-does-the-forget-sweep-mechanism-work-in-ai-memory-for-expiring-pages)

Understand the forget sweep mechanism in ai-memory for expiring pages. Learn how TTL expiration, decay eviction, and tombstone deletion remove obsolete wiki content.

- Tags: internals
- Published: 2026-08-21

### [How ai‑memory Handles Authority Adjustment in Retrieval for Different Content Types](/akitaonrails/ai-memory/how-does-ai-memorys-retrieval-handle-authority-adjustment-for-different-content-types)

Discover how ai-memory adjusts retrieval authority for diverse content types. Learn how high-authority content outranks lower-credibility matches using a bounded page-authority multiplier.

- Tags: deep-dive
- Published: 2026-08-21

### [Retrieval Methods in ai-memory: Full-Text, Graph, Entity, and Optional Vector Search](/akitaonrails/ai-memory/what-retrieval-methods-does-ai-memory-use-including-optional-vector-support)

Explore akitaonrails/ai-memory retrieval methods: FTS5 full-text search, entity matching, graph traversal, and optional vector semantic search. Get ranked results with RRF.

- Tags: deep-dive
- Published: 2026-08-21

### [How ai-memory Manages Auto-Improvement Proposals and Approval](/akitaonrails/ai-memory/how-does-ai-memory-manage-auto-improvement-proposals-and-their-approval)

Discover how ai-memory streamlines auto-improvement proposals with a three-stage pipeline for automated application or manual review. Learn about generation, validation, and approval gates.

- Tags: internals
- Published: 2026-08-21

### [What Is LLM Consolidation in ai‑memory? A Technical Guide to Persistent Knowledge](/akitaonrails/ai-memory/what-is-the-purpose-of-llm-consolidation-in-ai-memory)

Discover LLM consolidation in ai-memory. This technical guide explains how ephemeral data becomes durable wiki pages, transforming your AI's knowledge with persistent learning.

- Tags: deep-dive
- Published: 2026-08-21

### [How ai-memory Handles Session Finalization Without a Reliable Session-End Hook](/akitaonrails/ai-memory/how-does-ai-memory-handle-session-finalization-without-a-reliable-session-end-hook)

Learn how ai-memory finalizes sessions without a reliable hook using a durable SQLite job queue for CLI triggers and recovery, preventing data loss.

- Tags: how-to-guide
- Published: 2026-08-21

### [Understanding the Handoff Row in ai-memory Session Synthesis](/akitaonrails/ai-memory/what-is-a-handoff-row-in-ai-memorys-session-synthesis)

Discover the Handoff row in ai-memory session synthesis. Learn how this SQLite snapshot resumes agent work, saving time by avoiding log re-parsing and capturing key session data.

- Tags: deep-dive
- Published: 2026-08-21

### [How Session Summaries Are Generated in ai-memory Without an LLM](/akitaonrails/ai-memory/how-are-session-summaries-generated-in-ai-memory-without-an-llm)

Discover how ai-memory generates session summaries as JSON without an LLM. Learn about deterministic aggregation of pre-sanitized observation records from SQLite for efficient processing.

- Tags: internals
- Published: 2026-08-21

### [How ai-memory Ensures At-Least-Once Delivery of Downstream Effects](/akitaonrails/ai-memory/how-does-ai-memory-ensure-at-least-once-delivery-of-downstream-effects)

Learn how ai-memory ensures at-least-once delivery of downstream effects using SQLite, cursors, acknowledgments, leases, and router gating for reliable processing even during failures.

- Tags: how-to-guide
- Published: 2026-08-21

### [WriteCmd and the SQLite Actor: Single-Writer Command Pattern in ai-memory](/akitaonrails/ai-memory/what-is-the-writecmd-and-its-role-in-the-sqlite-actor)

Discover WriteCmd and its crucial role within the SQLite actor in ai-memory. Learn how it serializes operations for sequential writes and prevents race conditions.

- Tags: internals
- Published: 2026-08-21

### [How ai-memory Sanitizes Incoming Data from Untrusted Sources](/akitaonrails/ai-memory/how-does-ai-memory-sanitize-incoming-data-from-untrusted-sources)

Discover how ai-memory sanitizes untrusted data by redacting credentials before storage. Learn how this stateful sanitizer protects your secrets from SQLite and downstream systems. Enhance your data security today.

- Tags: security
- Published: 2026-08-21

### [What Is the Nearest-Marker Capture Policy in ai-memory?](/akitaonrails/ai-memory/what-is-the-nearest-marker-capture-policy-in-ai-memory)

Discover the nearest marker capture policy in ai-memory. Learn how this client-side filter efficiently ignores files using .ai-memory.toml rules, optimizing your AI memory operations.

- Tags: deep-dive
- Published: 2026-08-21

### [How ai-memory Handles Local Spooling of Events for Native Commands](/akitaonrails/ai-memory/how-does-ai-memory-handle-local-spooling-of-events-for-native-commands)

Discover how ai-memory ensures uninterrupted native command execution by locally spooling events, preventing network blocks and improving performance.

- Tags: internals
- Published: 2026-08-21

### [What Is the Timeout for Shell-Script Hooks Sending Data to ai-memory?](/akitaonrails/ai-memory/what-is-the-timeout-for-shell-script-hooks-sending-data-to-ai-memory)

Discover the one-second curl timeout for shell-script hooks sending data to ai-memory. Learn how this limit impacts client disconnections and server response times.

- Tags: how-to-guide
- Published: 2026-08-21

### [How ai-memory Captures Automatic Lifecycle Hooks from Agent CLIs](/akitaonrails/ai-memory/how-does-ai-memory-capture-automatic-lifecycle-hooks-from-agent-clis)

Discover how ai-memory captures automatic lifecycle hooks from agent CLIs. Learn about its fire-and-forget pipeline, typed privacy boundary, and atomic persistence for efficient AI-coding session recording.

- Tags: how-to-guide
- Published: 2026-08-21

### [What LLM Providers Are Supported by ai-memory? A Complete Guide to the 8 Backends](/akitaonrails/ai-memory/what-llm-providers-are-supported-by-ai-memory)

Discover which LLM providers ai-memory supports. Explore integrations with OpenAI GPT, Gemini, Claude, Ollama, vLLM, and more. Enhance your AI applications today.

- Tags: deep-dive
- Published: 2026-08-21

### [Can ai-memory Function Without an LLM Provider Configured? Understanding Zero-LLM Mode](/akitaonrails/ai-memory/can-ai-memory-function-without-an-llm-provider-configured)

Discover how ai-memory operates without an LLM provider in Zero-LLM mode. Explore core FTS5 search and wiki storage features that remain active even without LLM integration.

- Tags: how-to-guide
- Published: 2026-08-21

### [What Is the Role of SQLite in ai-memory's Architecture? A Deep Dive into the Derived Index](/akitaonrails/ai-memory/what-is-the-role-of-sqlite-in-ai-memorys-architecture)

Discover how ai-memory leverages SQLite as a high-performance derived index for fast full-text search, vector similarity, and graph traversal, all while preserving your markdown files as the source of truth.

- Tags: deep-dive
- Published: 2026-08-21

### [How ai-memory Versions Markdown Pages: SQLite and Git Hybrid Architecture](/akitaonrails/ai-memory/how-does-ai-memory-handle-versioning-of-markdown-pages)

Discover how ai-memory versions Markdown pages using a hybrid SQLite and Git architecture. Learn about its unique approach to immutable version history and source of truth management.

- Tags: architecture
- Published: 2026-08-21

### [Understanding the Core Data Structure of ai-memory: A Karpathy-Style LLM Wiki Implementation](/akitaonrails/ai-memory/what-is-the-core-data-structure-of-ai-memory-like-karpathys-llm-wiki)

Explore the core data structure of ai-memory, the Page struct. Discover its typed markdown records, immutable versioning, and content-addressed storage for efficient LLM wiki implementation.

- Tags: deep-dive
- Published: 2026-08-21

### [How to Set Up ai-memory for Cross-Session AI Agent Memory](/akitaonrails/ai-memory/how-to-set-up-ai-memory-for-cross-session-ai-agent-memory)

Learn to set up ai-memory for cross-session AI agent memory. This Rust service provides persistent, searchable wiki with SQLite for seamless memory continuity across CLI sessions and machines.

- Tags: how-to-guide
- Published: 2026-08-21

### [How the `/api/v1` JSON API Differs from the `/web` Browser UI in ai-memory](/akitaonrails/ai-memory/ai-memory-api-v1-vs-web-ui)

Discover the differences between ai-memory's /api/v1 JSON API and its /web browser UI. Understand distinct response formats, CORS handling, and client interaction patterns for programmatic vs. human access.

- Tags: api-reference
- Published: 2026-08-20

### [Understanding `WorkstreamCheckpoint` and `MANAGED_WORKSTREAM_PACKET_MARKER` in ai-memory](/akitaonrails/ai-memory/ai-memory-workstreamcheckpoint-packet-marker-role)

Understand WorkstreamCheckpoint and MANAGED_WORKSTREAM_PACKET_MARKER in ai-memory. Learn how WorkstreamCheckpoint persists state and MANAGED_WORKSTREAM_PACKET_MARKER routes UI packets.

- Tags: deep-dive
- Published: 2026-08-20

### [How `ai-memory install-hooks --session-aware` Enables Per-Session Auto-Scope Isolation](/akitaonrails/ai-memory/ai-memory-install-hooks-session-aware-isolation)

Discover how ai-memory install-hooks --session-aware creates isolated workspaces for each Claude Code session using a stdio-to-HTTP bridge and custom headers.

- Tags: how-to-guide
- Published: 2026-08-20

### [Curator vs Lint in ai‑memory: Two Stages of the Auto‑Improvement Loop Explained](/akitaonrails/ai-memory/ai-memory-curator-vs-lint)

Understand Curator vs Lint in ai-memory. Lint checks structural correctness and Curator finds recall gaps to improve your AI knowledge base. Learn when to use each.

- Tags: deep-dive
- Published: 2026-08-20

### [How `memory_write_page` with `expires_at` Interacts with the Forget Sweep in ai-memory](/akitaonrails/ai-memory/memory-write-page-expires-at-forget-sweep)

Learn how memory_write_page with expires_at interacts with the forget sweep. Understand how AI-memory automatically purges expired pages and their ancestry.

- Tags: internals
- Published: 2026-08-20

### [How the AI-Memory Wiki's Atomic Write System Interacts with the Git Checkpoint Watcher](/akitaonrails/ai-memory/ai-memory-wiki-atomic-write-git-checkpoint)

Discover how the AI-Memory wiki's atomic write system and Git checkpoint watcher ensure durable, consistent storage for every page mutation. Learn how re-indexing is triggered.

- Tags: internals
- Published: 2026-08-20

### [How ai-memory move-project Handles Merging vs. True Moves Between Workspaces](/akitaonrails/ai-memory/ai-memory-move-project-merge-vs-move)

Understand how ai-memory move-project handles true moves or merges between workspaces. Learn about the copy-purge strategy and lossless true-move options.

- Tags: how-to-guide
- Published: 2026-08-20

### [`memory_feedback` with Stale/Wrong Signals vs. Deletion: How ai-memory Handles Quality Control](/akitaonrails/ai-memory/memory-feedback-stale-wrong-vs-deletion)

Discover how ai-memory's memory_feedback handles stale or wrong signals differently from deletion. Learn about quality control and signal preservation.

- Tags: deep-dive
- Published: 2026-08-20

### [How the Authority-Aware Recall System Weights Rules, Decisions, and Procedures in ai-memory](/akitaonrails/ai-memory/ai-memory-authority-recall-page-weighting)

Discover how the ai-memory recall system weights rules decisions and procedures using a bounded authority multiplier for accurate information retrieval.

- Tags: deep-dive
- Published: 2026-08-20

### [ai-memory Bootstrap vs Reindex: What's the Difference and When to Use Each](/akitaonrails/ai-memory/ai-memory-bootstrap-vs-reindex)

Understand the difference between ai-memory bootstrap and ai-memory reindex. Learn when to use bootstrap for initial setup and reindex for rebuilding your search index.

- Tags: how-to-guide
- Published: 2026-08-20

### [How OIDC Device Authentication Flow Works for Native Hook Auth in ai-memory](/akitaonrails/ai-memory/ai-memory-oidc-device-auth-native-hooks)

Discover how the ai-memory CLI leverages OIDC device authentication flow for native hook auth, enabling browserless login via a separate device. Learn more.

- Tags: deep-dive
- Published: 2026-08-20

### [How the Entity-Assisted Recall System Stores Canonical Entities in Page Frontmatter](/akitaonrails/ai-memory/ai-memory-entity-recall-frontmatter-storage)

Learn how the entity-assisted recall system stores canonical entities in page frontmatter using structured EntityRef objects for powerful entity-aware search and graph expansion.

- Tags: how-to-guide
- Published: 2026-08-20

### [Global Scope vs Project Scope in AI-Memory `memory_query`: A Complete Comparison](/akitaonrails/ai-memory/memory-query-global-vs-project-scope)

Understand global scope vs project scope in AI-Memory memory_query. Learn how project scope searches your workspace and global scope searches all projects for efficient FTS5 queries.

- Tags: deep-dive
- Published: 2026-08-20

### [How ai-memory's Decay/Salience Model Works and What Memory Feedback Controls](/akitaonrails/ai-memory/ai-memory-decay-salience-model-memory-feedback)

Discover how ai-memory's decay salience model uses exponential decay and tunable parameters to manage memory retention. Learn how memory feedback controls salience and memory loss speed.

- Tags: deep-dive
- Published: 2026-08-20

### [Architecture of Managed Cross-Harness Workstreams in ai-memory](/akitaonrails/ai-memory/ai-memory-managed-workstreams-architecture)

Explore the architecture of managed cross-harness workstreams in ai-memory. Learn how this three-layer system facilitates seamless agent CLI migration for a unified coding experience.

- Tags: architecture
- Published: 2026-08-20

### [Project-Level Scope Resolution vs Global Scope Preferences in ai-memory: Key Differences Explained](/akitaonrails/ai-memory/ai-memory-project-vs-global-scope-resolution)

Understand project-level scope resolution versus global scope preferences in ai-memory. Learn how they enforce data isolation and set installation-wide defaults for your projects.

- Tags: deep-dive
- Published: 2026-08-20

### [How to Audit Contamination and Resolve Duplicate or Conflicting Page Entries in ai-memory](/akitaonrails/ai-memory/audit-resolve-ai-memory-page-conflicts)

Audit contamination in ai-memory with `ai-memory audit-contamination` to find duplicate or conflicting pages. Resolve issues by deleting duplicates using `delete-page <path>`.

- Tags: how-to-guide
- Published: 2026-08-20

### [How the ai-memory Bootstrap Command Initializes a New Project with Existing Git History](/akitaonrails/ai-memory/ai-memory-bootstrap-command-init-git)

Learn how the ai-memory bootstrap command initializes new projects by ingesting Git history and files to seed your AI knowledge base. Get started with existing code.

- Tags: how-to-guide
- Published: 2026-08-20

### [Security Model for Bearer Tokens and HTTP Basic Auth in ai-memory](/akitaonrails/ai-memory/ai-memory-web-ui-security-tokens-auth)

Learn how ai-memory secures its web UI with bearer tokens and HTTP Basic auth. Discover layered authentication for protected access.

- Tags: how-to-guide
- Published: 2026-08-20

### [How to Integrate ai-memory with Claude Code's Session-Aware Routing: A Complete MCP Guide](/akitaonrails/ai-memory/integrate-ai-memory-claude-code-routing)

Integrate ai-memory with Claude Code's session-aware routing. Install managed skills, configure MCP URL, and leverage automatic X-Session-Id header propagation for isolated memory operations per session.

- Tags: how-to-guide
- Published: 2026-08-20

### [How the ai-memory MCP Tool Surface Works: A Complete Guide to the 18 Available Tools](/akitaonrails/ai-memory/ai-memory-mcp-tool-surface-agents)

Explore the ai-memory MCP tool surface: learn how 18 stateless HTTP RPC tools enable agents to manage persistent knowledge with automatic project scoping via standardized calls.

- Tags: how-to-guide
- Published: 2026-08-20

### [How to Backup and Restore ai-memory Data Including SQLite and Wiki Git Repository](/akitaonrails/ai-memory/backup-restore-ai-memory-data)

Learn to backup and restore ai-memory data. The ai-memory backup command creates a gzipped tarball of your SQLite database and wiki Git repository for easy restoration.

- Tags: how-to-guide
- Published: 2026-08-20

### [How the ai-memory Decay and Sweep Mechanism Works for Automatic Memory Pruning](/akitaonrails/ai-memory/ai-memory-decay-sweep-mechanism)

Understand the ai-memory decay and sweep mechanism. Learn how exponential decay and access frequency prune cold pages automatically, optimizing memory usage.

- Tags: internals
- Published: 2026-08-20

### [How to Implement OIDC Device Authentication for ai-memory Shared Server Hook Writes](/akitaonrails/ai-memory/implement-oidc-device-auth-ai-memory-hooks)

Learn to implement OIDC device authentication for ai-memory server hook writes. Securely obtain JWTs with mcp:read realm role using the Device Authorization Grant. Avoid static tokens.

- Tags: how-to-guide
- Published: 2026-08-20

### [Data Model for Workspaces, Projects, and Page Hierarchies in ai-memory Wiki](/akitaonrails/ai-memory/ai-memory-wiki-data-model)

Discover the ai-memory wiki data model for workspaces projects and page hierarchies. Learn how SQLite and foreign-key constraints ensure referential integrity in this three-tier structure.

- Tags: data-model
- Published: 2026-08-20

### [How to Troubleshoot Handoffs Not Appearing in the Next Agent Session with ai-memory](/akitaonrails/ai-memory/troubleshoot-ai-memory-handoffs-not-appearing)

Troubleshoot why handoffs aren't appearing in the next agent session with akitaonrails/ai-memory. Learn to fix common workspace, project, ownership, and state issues.

- Tags: how-to-guide
- Published: 2026-08-20

### [How ai-memory's Zero-LLM Mode Works: Complete Feature Set Without an LLM](/akitaonrails/ai-memory/ai-memory-zero-llm-mode-features)

Discover how ai-memory's zero-LLM mode works using synthetic compression, BM25/FTS5 search, and SQL briefings. Access all core features offline and cost-free without an LLM.

- Tags: deep-dive
- Published: 2026-08-20

### [How to Configure Embedding Providers for Vector Similarity Search in ai-memory](/akitaonrails/ai-memory/configure-ai-memory-embedding-providers)

Configure embedding providers in ai-memory by editing config.toml. Learn to set up providers, models, and credentials for efficient vector similarity search and automatic vector generation.

- Tags: how-to-guide
- Published: 2026-08-20

### [AI-Memory Capture Exclusion Patterns: How to Ignore Sensitive File Operations](/akitaonrails/ai-memory/ai-memory-capture-exclusion-patterns)

Learn how AI-memory capture exclusion patterns help you ignore sensitive file operations by configuring the ignore_paths list in your .ai-memory.toml marker file.

- Tags: how-to-guide
- Published: 2026-08-20

### [How the ai-memory Managed Workstream Enables Cross-Harness Session Continuity](/akitaonrails/ai-memory/ai-memory-managed-workstream-session-continuity)

Learn how the ai-memory managed workstream enables cross-harness session continuity by persisting a global identifier and using cursor-based event replay for seamless LLM session resumption.

- Tags: deep-dive
- Published: 2026-08-20

### [How to Deploy ai-memory Behind a Reverse Proxy with HTTPS/TLS Termination](/akitaonrails/ai-memory/deploy-ai-memory-reverse-proxy-https)

Learn to deploy ai-memory behind a reverse proxy for secure HTTPS TLS termination. Configure Nginx Caddy or Traefik for robust protection and easy management.

- Tags: how-to-guide
- Published: 2026-08-20

### [How the .ai-memory.toml Marker File Enables Per-Project Isolation and Custom Routing](/akitaonrails/ai-memory/ai-memory-toml-marker-file-usage)

Discover how the .ai-memory.toml marker file in akitaonrails/ai-memory creates per-project isolation and custom routing by establishing workspace boundaries and namespaces for your AI memory.

- Tags: how-to-guide
- Published: 2026-08-20

### [How the ai-memory Auto-Improvement Scheduler Works: Complete Guide to Configuration and Approval Workflows](/akitaonrails/ai-memory/ai-memory-auto-improvement-scheduler-config)

Discover how the ai-memory auto-improvement scheduler works. Learn to configure approval workflows for wiki edits with this complete guide. Streamline your AI's knowledge base.

- Tags: deep-dive
- Published: 2026-08-20

### [How to Set Up ai-memory with Anthropic, OpenAI, and Gemini LLM Providers](/akitaonrails/ai-memory/setup-ai-memory-llm-providers)

Easily set up ai-memory with Anthropic, OpenAI, or Gemini LLM providers. Configure the AI_MEMORY_LLM_PROVIDER environment variable and export your API key for seamless integration.

- Tags: how-to-guide
- Published: 2026-08-20

### [How ai-memory Lifecycle Hooks Capture and Sanitize Agent Observations](/akitaonrails/ai-memory/ai-memory-lifecycle-hooks-capture-sanitize)

Discover how ai-memory lifecycle hooks capture and sanitize agent observations using Axum, pure capture policies, and SQLite persistence. Protect sensitive data efficiently.

- Tags: how-to-guide
- Published: 2026-08-20

### [How to Configure ai-memory for Multi-User Shared Server Deployments with Authentication](/akitaonrails/ai-memory/configure-ai-memory-multi-user-server)

Configure ai-memory for multi-user shared servers. Enable tiered authentication via config.toml and manage users with the CLI for secure deployments.

- Tags: how-to-guide
- Published: 2026-08-20

### [How ai-memory's Cross-Agent Handoff Mechanism Works Between AI Coding Agents](/akitaonrails/ai-memory/how-does-ai-memory-cross-agent-handoff-work)

Discover how ai-memory's cross-agent handoff seamlessly transfers context between AI coding agents using MCP tools and session snapshots for efficient collaboration.

- Tags: deep-dive
- Published: 2026-08-20

### [How the /api/v1 Web API Provides Read-Only Access to Memory Data in AI Memory](/akitaonrails/ai-memory/how-does-the-web-api-api-v1-provide-read-only-access-to-memory-data)

Explore how the /api/v1 Web API in akitaonrails/ai-memory offers secure read-only access to memory data for third-party front-ends using token authentication and ETags.

- Tags: api-reference
- Published: 2026-08-19

### [How to Identify Decay Candidates and Trigger Forget Sweeps in ai-memory](/akitaonrails/ai-memory/how-do-decay-candidates-get-identified-and-what-triggers-forget-sweeps)

Learn how ai-memory identifies decay candidates using retention scores and triggers forget sweeps via CLI, scheduled jobs, or adaptive tombstone limits. Optimize your memory management.

- Tags: how-to-guide
- Published: 2026-08-19

### [Understanding the Single-Writer SQLite Actor Pattern in ai-memory](/akitaonrails/ai-memory/what-is-the-single-writer-sqlite-actor-pattern-and-why-is-it-used)

Discover the single-writer SQLite actor pattern for guaranteed serialized writes and atomic transactions. Learn how ai-memory enables parallel reads with ReaderPool for efficient database access.

- Tags: deep-dive
- Published: 2026-08-19

### [How the ai-memory Scope Resolver Handles .ai-memory.toml Marker Files](/akitaonrails/ai-memory/how-does-the-scope-resolver-handle-ai-memory-toml-marker-files)

Learn how the ScopeResolver in akitaonrails/ai-memory finds and parses .ai-memory.toml marker files, prioritizing workspace, project, and strategy settings for your AI memory.

- Tags: how-to-guide
- Published: 2026-08-19

### [Understanding the ai-memory Feedback System: How It Controls Page Salience and Linting](/akitaonrails/ai-memory/what-is-the-feedback-system-and-how-does-it-affect-page-salience-and-linting)

Discover the ai-memory feedback system. Learn how it uses explicit judgments to control page salience for retrieval ranking and surfaces unresolved signals as lint findings.

- Tags: deep-dive
- Published: 2026-08-19

### [How ai-memory Backs Up and Restores Wiki and SQLite Data](/akitaonrails/ai-memory/how-are-backup-and-restore-operations-performed-for-wiki-and-sqlite-data)

Learn how ai-memory backs up wiki and SQLite data via POST /admin/backup and restores it using the ai-memory restore CLI command. Ensure data integrity and portability.

- Tags: how-to-guide
- Published: 2026-08-19

### [How the ai-memory Bootstrap Command Imports Existing Project History](/akitaonrails/ai-memory/how-does-the-bootstrap-command-import-existing-project-history)

Learn how the ai-memory bootstrap command imports existing project history. It collects git commits and docs, prunes them for LLM token limits, and generates wiki pages.

- Tags: how-to-guide
- Published: 2026-08-19

### [Admission Webhook System and Content Filtering in ai-memory: A Complete Guide](/akitaonrails/ai-memory/what-is-the-admission-webhook-system-and-how-does-content-filtering-work)

Learn about ai-memory's admission webhook system and content filtering. Intercept wiki mutations, filter content, enrich metadata, or reject writes before storage.

- Tags: how-to-guide
- Published: 2026-08-19

### [How Supersession Tracking Preserves Page Version History in ai-memory](/akitaonrails/ai-memory/how-does-supersession-tracking-preserve-page-version-history)

Learn how supersession tracking in akitaonrails/ai-memory preserves page version history. Discover the immutable, backwards-traversable chain created by SQLite row linking for every edit.

- Tags: internals
- Published: 2026-08-19

### [Vector Embedding Integration with OpenAI, Voyage, and Gemini in ai-memory](/akitaonrails/ai-memory/how-does-vector-embedding-integration-work-with-openai-voyage-and-gemini-providers)

Learn how ai-memory unifies vector embedding integration with OpenAI, Voyage, and Gemini using a single async Embedder trait for provider-agnostic semantic search.

- Tags: deep-dive
- Published: 2026-08-19

### [Capture Exclusion Policy in ai-memory: How It Filters File-Tool Events](/akitaonrails/ai-memory/what-is-the-capture-exclusion-policy-and-how-does-it-filter-file-tool-events)

Learn how the capture exclusion policy in ai-memory filters file tool events by matching paths against glob patterns in your marker file. Prevent unwanted event recording.

- Tags: how-to-guide
- Published: 2026-08-19

### [How Memory Slots Provide Per-Operator Context Isolation in AI-Memory](/akitaonrails/ai-memory/how-do-memory-slots-provide-per-operator-context-isolation)

Discover how AI-Memory's memory slots isolate per-operator context using a _slots namespace and path segmentation. Keep private slots secure while maintaining global visibility for shared data.

- Tags: internals
- Published: 2026-08-19

### [How the Session Consolidation Process Compiles Observations into Wiki Pages in ai-memory](/akitaonrails/ai-memory/what-is-the-session-consolidation-process-that-compiles-observations-into-wiki-pages)

Understand ai-memory's session consolidation process. Learn how observations are compiled into wiki pages via capture, rule-based summarization, and LLM-driven consolidation.

- Tags: internals
- Published: 2026-08-19

### [How MCP Tools Are Implemented in ai-memory: Request Routing Flow Explained](/akitaonrails/ai-memory/how-are-mcp-tools-implemented-and-what-is-the-request-routing-flow)

Learn how MCP tools are implemented in ai-memory using the rmcp crate and #[tool_handler] macro. Explore the request routing flow through ToolRouter and ServerHandler::call_tool.

- Tags: internals
- Published: 2026-08-19

### [How the ai-memory Wiki Handles Atomic File Writes and Git Versioning](/akitaonrails/ai-memory/how-does-the-wiki-system-handle-atomic-writes-and-git-versioning)

Discover how the ai-memory wiki ensures crash-safe updates with atomic file writes and leverages Git versioning for reliable change tracking. Learn about its unique GitAdapter implementation.

- Tags: internals
- Published: 2026-08-19

### [Authentication and Authorization Model for Multi-User Deployments in ai-memory](/akitaonrails/ai-memory/what-is-the-authentication-and-authorization-model-for-multi-user-deployments)

Explore the ai-memory authentication and authorization model for multi-user deployments. Learn about its four-tier system and attribution-only approach for secure data management.

- Tags: architecture
- Published: 2026-08-19

### [How Entity Extraction and Entity-Assisted Recall Improve Search Relevance in ai-memory](/akitaonrails/ai-memory/how-does-entity-extraction-and-entity-assisted-recall-improve-search-relevance)

Enhance search relevance with entity extraction and entity-assisted recall in ai-memory. Improve results by fusing salient nouns with full-text search.

- Tags: deep-dive
- Published: 2026-08-19

### [How the Managed Workstream Launcher (`ai-memory run`) Provides Cross-Harness Continuity](/akitaonrails/ai-memory/how-does-the-managed-workstream-launcher-ai-memory-run-enable-cross-harness-continuity)

Learn how ai-memory run provides cross-harness continuity by detecting AI harnesses, injecting session flags, and exporting transcripts to a unified workstream store.

- Tags: how-to-guide
- Published: 2026-08-19

### [How the ai-memory Cross-Agent Handoff Mechanism Transfers Context Between Sessions](/akitaonrails/ai-memory/how-does-the-cross-agent-handoff-mechanism-transfer-context-between-sessions)

Learn how ai-memory's cross-agent handoff mechanism transfers context between sessions. It persists records to SQLite and re-injects them into new sessions for seamless workflow continuity.

- Tags: deep-dive
- Published: 2026-08-19

### [How ai-memory Resolves Workspace and Project Scopes From the Current Working Directory](/akitaonrails/ai-memory/how-are-workspace-and-project-scopes-resolved-from-the-current-working-directory)

Learn how ai-memory resolves workspace and project scopes from your current working directory using a deterministic fallback chain. Understand project scoping effortlessly.

- Tags: how-to-guide
- Published: 2026-08-19

### [How the Auto-Improvement Scheduler Works in ai-memory: Session Review and Proposal Approval](/akitaonrails/ai-memory/how-does-the-auto-improvement-scheduler-work-and-how-are-proposals-approved)

Discover how the auto-improvement scheduler in akitaonrails/ai-memory operates. Learn about session review, LLM proposal generation, and approval workflows for enhanced AI memory management.

- Tags: internals
- Published: 2026-08-19

### [What Is the Hook Capture Pipeline and How Are Observations Sanitized in ai-memory](/akitaonrails/ai-memory/what-is-the-hook-capture-pipeline-and-how-are-observations-sanitized)

Learn about the ai-memory hook capture pipeline. Discover how untrusted script output becomes safe, searchable observations via sanitizer before storage.

- Tags: deep-dive
- Published: 2026-08-19

### [How ai-memory’s FTS5 Full-Text Search Ranking Works Internally](/akitaonrails/ai-memory/how-does-ai-memorys-fts5-full-text-search-ranking-work-internally)

Discover how ai-memory’s FTS5 full-text search ranking works internally. Learn about query normalization, score adjustment, and Reciprocal Rank Fusion for precise search results.

- Tags: internals
- Published: 2026-08-19