memory
Guide: Add AgentCore Runtime Memory with Hindsight
Add AgentCore Runtime memory with Hindsight using the runtime adapter, stable user bank IDs, and recall plus retain hooks across session churn.
Guide: Add Claude Code Persistent Memory with Hindsight
Add Claude Code persistent memory with Hindsight using the memory plugin, automatic recall hooks, and project aware bank IDs across sessions.
Guide: Add Codex CLI Persistent Memory with Hindsight
Add Codex CLI persistent memory with Hindsight using hook based recall, automatic retain, and project scoped bank IDs that survive across sessions.
Guide: Add CrewAI Persistent Memory with Hindsight
Add CrewAI persistent memory with Hindsight using ExternalMemory, HindsightStorage, and optional per agent banks so repeated crew runs build on earlier work.
Guide: Add LangGraph Persistent Memory with Hindsight
Add LangGraph persistent memory with Hindsight using tools, recall and retain nodes, or the BaseStore adapter so agents remember users across runs.
Guide: Add LlamaIndex Persistent Memory with Hindsight
Add LlamaIndex persistent memory with Hindsight using HindsightMemory for auto recall and retain, or HindsightToolSpec when agents need explicit tools.
Guide: Add Pipecat Voice Agent Memory with Hindsight
Add Pipecat voice agent memory with Hindsight using HindsightMemoryService to recall context before replies and retain completed turns across calls.
Guide: Add Pydantic AI Persistent Memory with Hindsight
Add Pydantic AI persistent memory with Hindsight using async memory tools and auto injected instructions so agents remember users and workflow context.
Guide: Add SmolAgents Persistent Memory with Hindsight
Add SmolAgents persistent memory with Hindsight using native Tool subclasses, optional memory instructions, and stable bank IDs for repeat runs.
Guide: Add Strands Persistent Memory with Hindsight
Add Strands persistent memory with Hindsight using native tools, optional memory instructions, and stable per user banks across agent sessions.
Reduce Hindsight Consolidation Memory Fan-Out Safely
Reduce Hindsight consolidation memory fan-out by tuning recall budget, source fact limits, and FlashRank memory settings on large banks in production.
Size Hindsight Memory Footprint for Real Deployments
Size Hindsight deployments with the new memory footprint guidance for full and slim images, workers, the control plane, and PostgreSQL capacity planning.
安全地减少 Hindsight 合并内存扇出
通过调整回忆预算、源事实限制和大型库上的 FlashRank 内存设置，减少 Hindsight 合并内存扇出。
为实际部署调整 Hindsight 内存占用空间
使用完整和精简映像、workers、控制平面和 PostgreSQL 容量规划的新内存占用空间指导来调整 Hindsight 部署。
Beginner's Guide to Persistent Memory for AI Agents
A beginner's guide to persistent memory for AI agents, including what it is, why it matters, and how to think about setup, recall, and retention clearly.
Context Windows Are Not Memory
Context windows are not memory. Learn why bigger prompts help only temporarily, and what real persistent memory adds for reliable agents over time.
Designing AI Agents That Remember What Matters
A practical guide to designing AI agents that remember what matters without storing everything, polluting recall, or overwhelming the active prompt.
How Agent Memory Reduces Repetition and Rework
How agent memory reduces repetition and rework by carrying forward facts, choices, and preferences that users should not have to repeat every session.
How AI Agents Learn Across Sessions
How AI agents learn across sessions when memory captures durable preferences, facts, and outcomes instead of resetting from scratch every time.
How Memory Helps AI Agents Stay Consistent
Learn how memory helps AI agents stay consistent across sessions, tools, and repeated tasks without forcing users to restate critical context.
How Persistent Memory Changes Agent Behavior
See how persistent memory changes agent behavior by improving continuity, reducing repetition, and making agents more adaptive across sessions.
Short-Term vs Long-Term Memory for AI Agents
Understand short-term vs long-term memory for AI agents, including what each layer does and why useful systems need both working together well.
Stateless Agents vs Memory-Powered Agents
Compare stateless agents vs memory-powered agents so you can decide when memory is essential, and when a simpler agent design is enough today.
The Difference Between Memory, Retrieval, and Context
Understand the difference between memory, retrieval, and context so you can design agent systems with clearer responsibilities and fewer blind spots.
The Hidden Cost of Memoryless AI Agents
The hidden cost of memoryless AI agents includes rework, repeated prompting, weak continuity, and poor handoffs across sessions and tools today.
What Agent Memory Really Means
Learn what agent memory really means, how it differs from chat history and retrieval, and what a useful memory layer should actually do in practice.
What Makes Agent Memory Actually Useful
What makes agent memory actually useful: good retention, reliable recall, clear scope, and enough visibility to trust the system in real workflows.
When Do AI Agents Need Memory?
When do AI agents need memory? Use this guide to tell whether your workflow needs durable recall, or whether a simpler approach is enough today.
Why AI Agents Forget, and What to Do About It
Why AI agents forget, the most common memory failures behind that behavior, and what to do if you want more reliable continuity over time today.
Why Chat History Is Not Enough for AI Agents
Why chat history is not enough for AI agents, and what a real memory layer adds when the task needs continuity, recall, and structure over time.
Why Multi-Step Tasks Break Without Memory
Why multi-step tasks break without memory, especially when agents need to preserve goals, intermediate results, and prior decisions accurately.
Why Reliable AI Agents Need More Than Prompts
Why reliable AI agents need more than prompts, especially when long-lived tasks require memory, retrieval, and stronger operational structure.
Why Tool-Using Agents Need Shared Memory
Why tool-using agents need shared memory when several assistants, editors, or surfaces should build on the same durable context together well.
Why Your AI Agent Needs Memory
Why your AI agent needs memory, what breaks without it, and how persistent recall helps agents stay useful across sessions, tasks, and tools.
The Agent Memory Benchmark: Hindsight vs Alternatives
The agent memory benchmark story is now clearer: Hindsight leads BEAM at 10M tokens, while common alternatives break down or rely on weaker retrieval patterns.
Hindsight vs RAG for AI Agents, and When to Use Each
Agent memory vs RAG is not an either-or slogan. This guide explains when Hindsight fits better, when RAG is enough, and when a hybrid makes sense.
Hermes Agent Holographic Memory: A Technical Deep Dive
Hermes agent holographic memory uses HRR algebra, local SQLite, and trust scoring. This deep dive explains the architecture and tradeoffs clearly.
Why AI Agents Lose Context, and How Hindsight Fixes It
AI agent context window limits cause dropped preferences, broken continuity, and weak recall. Hindsight fixes that with persistent memory built for agents.
Hermes Memory Bank Strategy for Production
Choose the right Hermes memory bank strategy for production with Hindsight, scope banks safely, and keep recall clean across users, teams, and environments.
Hermes Multi-User Memory Setup with Hindsight
Set up Hermes multi-user memory with Hindsight, map each user to the right bank, and keep recall isolated so one user never inherits another user’s context.
Hermes Shared Memory Across Agents Setup
Set up Hermes shared memory across agents with Hindsight, reuse one bank on purpose, and test that multiple agents can build on the same context safely.
Move Hermes Memory to Hindsight Cloud Guide
Move Hermes memory from local files to Hindsight Cloud, keep the setup clean, and verify that recall still works after the switch to a managed backend.
OpenClaw and Claude Code Shared Memory Setup
Set up shared memory between OpenClaw and Claude Code with Hindsight, reuse one bank across both tools, and verify that context moves cleanly between chat and coding work.
OpenClaw Memory Bank Strategy for Teams
Choose the right OpenClaw memory bank strategy for teams with Hindsight, compare per-user and shared patterns, and avoid the most common isolation mistakes.
OpenClaw Project-Scoped Memory Setup Guide
Set up OpenClaw project-scoped memory with Hindsight, keep one project’s context separate from another, and choose when to use fixed banks versus dynamic isolation.
OpenClaw Shared Memory Across Agents Guide
Set up OpenClaw shared memory across agents with Hindsight, choose the right bank granularity, and verify that multiple agents reuse the same context safely.
Comparison: MCP vs SDK Memory with Hindsight
Compare MCP vs SDK memory with Hindsight so you can choose the right integration path for AI clients, custom apps, and team workflows.
Comparison: Single-Bank vs Multi-Bank Hindsight
Compare single-bank vs multi-bank Hindsight setups so you can choose the right memory isolation model for one agent, a team, or many clients.
Guide: Set Up ContextForge Memory with Hindsight
Set up ContextForge memory with Hindsight so every client behind the gateway can use retain, recall, and reflect through one unified MCP endpoint.
Guide: Use Hindsight Skills for Persistent Memory
Use Hindsight Skills for persistent memory in Claude Code, OpenCode, or Codex so user preferences and project lessons survive across sessions.
Guide: Add OpenCode Memory with Hindsight
Add OpenCode memory with Hindsight using the native plugin for auto-recall, auto-retain, and direct retain, recall, and reflect tools.
Guide: Add Paperclip Memory with Hindsight
Add Paperclip memory with Hindsight so agents can retain, recall, and reflect across heartbeats and sessions instead of starting cold each run.
Guide: Run Hindsight as a Local MCP Server
Run Hindsight as a local MCP server with embedded PostgreSQL so Claude, Cursor, and other MCP clients get persistent memory without extra infra.
Guide: Share One Hindsight Memory Across AI Tools
Share one Hindsight memory bank across AI tools so Claude, ChatGPT, coding agents, and MCP clients can reliably build on the same long-term context.
OpenClaw Local vs Cloud Memory Setup with Hindsight
Compare OpenClaw local vs cloud memory setup with Hindsight, including setup, privacy, shared memory, maintenance, and when each option fits best.
Control Recall Injection in OpenClaw with Hindsight
Control recall injection in OpenClaw with Hindsight, choose the right position, and tune memory placement for better context and prompt behavior.
OpenClaw Per-User Memory Across Channels Setup Guide
Set up OpenClaw per-user memory across channels with Hindsight, choose the right bank granularity, and keep one user's context consistent everywhere.
How to Fix Hermes Memory When It Stops Recalling Context
Debug Hermes memory when it stops recalling context. Check mode, health, hooks, logs, and retention timing so auto-recall starts working again.
Hermes Memory Modes with Hindsight, Hybrid, Context, Tools
Choose the right Hermes memory mode for Hindsight. Learn when to use hybrid, context, or tools, how to switch modes, and how to verify recall.
Guide: Migrate hindsight-hermes to Native Hermes Memory
Learn how to migrate hindsight-hermes to native Hermes memory without losing your bank, then verify recall, tools, and cross-session memory still work.