The components of agent memory
For Claude to learn from experience, it has to decide what’s worth remembering before it knows what’s next. Here’s how “dreaming” helps it organize memory and correct mistakes.
Topic
#agent-memory
28 篇笔记
Designing an Always-On Agent
Chatbots wait for a message. An always-on agent is single-threaded, proactive and situationally aware. Here's how we design them, and what models still lack.
为团队构建真正的 Agent OS：来自 Ankole 的工程实践
此为《Building a Real Agent OS for Teams: Lessons from Ankole》的中文翻译版，倘有歧义请以英文原版为准。1. 从单用户 Harness 到集体认知在独立开发者的笔记本电脑上，Claude Code、Codex 与 OpenCl...
New context engineering challenges in late 2026
It feels like everyone is converging on the same agent architecture: an LLM, running in a loop, calling tools, running in a sandbox. Claude ...
Memory Is a Compiler
tl;dr: Memory preserves the past in a form meant to be useful in the future, then recompiles what that past means as new evidence and new qu...
Building Self-Correcting Memory in OpenWiki
Memory Has a Forgetting ProblemA memory system is only as good as its ability to forget.Most discussions about agent memory focus on creatin...
How to Build a Company Brain That Gets Smarter Every Week
I am going to show you how to turn every correction, decision, and useful workflow your team gives AI into one company brain that makes ever...
5 design patterns for long-horizon agent harness
Any agent can look brilliant on a one-shot task. Give it a week of real work and it starts to fall apart."Long horizon" means the agent keep...
From context to dreams: architecting memory for AI agents
Have you ever felt that every conversation you have with an LLM across sessions feels like starting over from scratch? LLMs have a problem: ...
How to Design an Agent Harness: six decisions that turn a model into a worker you can leave alone
Your agent says the job is done and the tests never ran. It's sharp for twenty minutes, then forgets a rule you gave it at the start. You re...
How Compaction Works in Pi
Why compaction is needed for large language models and how Pi implements it
How to Build a Shared AI Harness for Your Team
I am going to show you how to turn the models, agents, skills, and automations living across your team's tools and workflows into one coordi...
The company brain has a permissions problem
Every company is connecting Slack, email, docs and meetings into one brain that gives everyone access to everything the company knows.Nobody...
Your Agent Remembers Everything and Understands Nothing
Agent memory is where analytics was for years, returning what you asked for and nothing more. Then analytics started surfacing which number ...
Why Agents Started Dreaming (And What is Dreaming)?
A long-running agent gets really worse at remembering facts over time.As the context window fills up during the conversation, and especially...
YC 开源 QM：当每个员工都有 Agent，公司需要怎样的协作系统？
未来一家公司里，可能每个员工都有自己的 Agent。它们能读文件、查数据库、写代码、回复邮件，也能在后台持续运行任务。问题随之而来：这些 Agent 应该看到什么？记住什么？使用谁的账号？哪些能力可以共享？危险动作由谁批准？7 月 31 日，Y Combinator 开源的 QM...
The new rules of context engineering for Claude 5 models
I’ve written previously about how to best prompt the newest generation of Claude 5 models and work with them iteratively to discover what yo...
The State of Agent Wikis
In April 2026, Andrej Karpathy published a GitHub Gist describing a pattern he called the LLM Wiki.In the months since, four different teams...
A Taxonomy of Self-evolving Agents
Self-evolving agents are becoming popular. [Hermes Agent](https://hermes-agent.nousresearch.com/docs/user-guide/features/skills) enables aut...
Towards org-level agent harnesses
Claude Tag has grown rapidly in Anthropic. I want to share some of the reasons for this and the behavioral shifts I’ve seen with this agent ...
30 Core Agentic Engineering Concepts Every Developer Should Know
There are 8 billion people on the planet.Only a fraction of developers understand how AI agents actually work.Not the demos. Not the hype.Th...
The 7 Types of Agent Memory: A Technical Guide for AI Engineers
Agent memory explained: the 7 types — working, semantic, episodic, procedural, retrieval, parametric, prospective — and when to build each.
I Replaced My Entire Growth Team With 6 AI Agents. Here Is the Full System.
The week everything changed, I was not in front of my computer.Three content pieces went out before 9am. Four leads got qualified and follow...
Dreaming: Better memory for a more helpful ChatGPT
ChatGPT introduces a new memory system to better remember preferences, keeping context fresh and relevant across conversations.
The Ultimate Guide for a Working Agent Memory
构建有效Agent记忆的终极指南：分层记忆栈、Research Packets、5级晋升阶梯和质量过滤系统
How Memory Works in DeerFlow?
mem0 团队深度解析 ByteDance DeerFlow 的记忆系统实现：基于 JSON 的本地存储、置信度评分、异步提取和 2000 token 注入预算
We broke the frontier in agent memory: Introducing ~99% SOTA memory system.
Supermemory 团队发布 ASMR (Agentic Search and Memory Retrieval) 技术，在 LongMemEval 基准测试达到 ~99% 准确率，无需向量数据库或嵌入