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# OpenClaw Memory Problems: Why It Forgets and How to Fix It (2026)

By Dhravya Shah February 19, 2026 · 4 min read 

![Supermemory header reading "Give OpenClaw memory it can use across conversations" — A small wind-up lobster beside a remembered card in an open index box](https://supermemory.ai/_astro/cover.BpeGGcoL_23DUaR.webp)

TLDR: Today, we are releasing a new version of our openclaw plugin - [github.com/supermemoryai/openclaw-super…](https://github.com/supermemoryai/openclaw-supermemory).

This post is going to be a bit technical, so bear with me (or bookmark for later!)

In this post, I will talk about what we do about OpenClaw memory, and how we fix it.

BENCHMARKS AT THE END!!! :)  

  
It's been about two weeks since [@OpenClaw](https://x.com/@OpenClaw) absolutely took over the internet. Everyone's been talking about it - the things it can do, how it can connect to all our tools, and how we can chat with it on our preferred messaging platform. This always-running, always working assistant.  

  
It's biggest problem? Memory. It's not just me saying it. We launched our plugin a [few weeks ago](https://x.com/DhravyaShah/status/2016308406701981731?s=20) (it got 500k views!!), and it is much-loved!  
just do an x search about openclaw memory. no one has good things to say about it :([x.com/pedrodias/status/2023013765911122…](https://x.com/pedrodias/status/2023013765911122065?s=20) [x.com/DhravyaShah/status/20232589583711…](https://x.com/DhravyaShah/status/2023258958371119131?s=20)

Openclaw obviously saw this - and they even added the QMD memory plugin. This should fix it, right???? ....Even today morning, I woke up to this post by [@Levelsio](https://x.com/@Levelsio) \- and I did my usual plug, talking about the [@supermemory](https://x.com/@supermemory) plug etc. etc.

X content is paused until you allow embedded content.

[Open on X ↗](https://twitter.com/levelsio/status/2023109374676496519?ref%5Fsrc=twsrc%5Etfw)

> <https://twitter.com/levelsio/status/2023109374676496519>

And, to my surprise, MANY recommended supermemory. But why? What do we do differently that the built-in version does not? How is it different from filesystem? or QMD? How does it compare on the benchmarks?I kept getting these questions - so here's a practical, technical explanation of what supermemory does differently.

## OpenClaw's memory problems

To understand this well, we first need to learn exactly how openclaw remembers things. It has a **Two-layer storage:**

![Tool-based memory flow: the agent explicitly calls MEMORY_SEARCH and a hybrid BM25/vector pipeline returns snippets](https://supermemory.ai/_astro/image-1.Dzmt0ahh_Z1nvaUR.webp)

1. **memory/YYYY-MM-DD.md** — daily append-only logs. The agent reads today + yesterday at session start. Think of it as a scratchpad for running context.
2. **[MEMORY.md](https://memory.md/)** — curated long-term facts, preferences, decisions. Only loaded in private/DM sessions (never group chats, for privacy).

**Two tools (read-side):**

* memory\_search — semantic search over all memory files. Returns snippets with file path, line range, and score. Mandatory before answering anything about prior work, decisions, dates, people, preferences. \*\*
* memory\_get — read specific lines from a file after finding them via search.

**The problem?**

1. It uses tools, not hooks.  
    
Because it is highly reliant on tools, you are always expecting the main agent to UTILIZE the tools to do any memory operation.  
You tell OpenClaw your name? It has to spend tokens and time to save it, using a tool.  
    
You ask it a basic question? you have to ask it to use the memory tool to actually collect the context to answer the question.  
    
This approach is rather slow, but also context is only fetched when you need it. \*_The problem? Counterintuitively, this uses MORE, not LESS tokens - because the tool call etc are expensive too!_
2. It does not handle knowledge updates, temporal reasoning, multi-session context well.  
    
When saving new things to memory, it has no idea of what's already in there (Unless you explicitly ask it to traverse through the whole memory again). This leads to it being a bit stupid when adding things, as it will add redundant information, not "update" existing knowledge, and generally not build on top of everything it knows about you.
3. **It does not forget.**Forgetfulness is more important than you think. This is the primary way to keep the context fresh and useful, even after time has passed.

## How [@supermemory](https://x.com/@supermemory) fixes it.

We have been building the context infrastructure for agent memory for years now. Throughout this time, we have learnt and built something that we think is ideal for the age of OpenClaw.

What's different? Supermemory is built with a vector-graph layer, which automatically learns and updates it's knowledge about users.

It comes with Knowledge updates, temporal reasoning, and other things. Every fact is built on top of other facts, and it's always contextual.

For the plugin, we make use of HOOKS. The saves happen implicitly, in the background, with both the memories extracted out of it, as well as the raw chunks being saved.

This is mainly because we don't know what to "remember" on ingestion time - so if something was not remembered, the chunk referencing it will show up to provide context. But it will always be there.

Importantly, this memory system also forgets! Irrelevant information over a long time horizon will automatically decay and be forgotten, unlike static markdown files.

![Hook-based memory flow: pre-request recall injects context and a post-response hook stores facts asynchronously](https://supermemory.ai/_astro/image-2.Dd229zL2_Z21wOVG.webp)

claude helped me with a nice UI to put this in picture

## Ok so the architecture is better. but benchmarks?

To verify our claims, we ran supermemory against both - OpenClaw's memory system as well as Claude code's memory system, on our open source memory evaluation platform, Memory Bench. [github.com/supermemoryai/memorybench](https://github.com/supermemoryai/memorybench)Supermemory consistently scored 10-20% better across the board.

* Filesystem (Claude code's memory): 54.2%
* RAG (OpenClaw's memory): 58.3% \*Note that this is expecting that the memory tool is actually called.
* Supermemory: 85.9% \*Automatic, implicit!

The supermemory plugin also saves on tokens used (by the LLM provider), so it ends up being **better, faster AND cheaper.**

**Yeah. that's right.**

You can use it today.

Just go here or ask openclaw to set it up for you. Premium memory for all your services, for just $20 /month - [github.com/supermemoryai/openclaw-super…](https://github.com/supermemoryai/openclaw-supermemory)

## Other posts.

1. [We're open sourcing the company brain. Here's how we designed the multiplayer harness Company Brain is now open source. A walkthrough of the multiplayer harness behind its Slack experience, from proactivity and memory boundaries to approvals and recovery. NewsSep 25, 2026 ](https://supermemory.ai/blog/open-sourcing-company-brain)
2. [Jev changes a lot in memory & context engineering. Here's exactly how. We tested Jev across reranking, chunking, observation, and harness decisions. Here is where fast decision models help memory systems, where they cost more, and where they still fall short. EngineeringSep 24, 2026 ](https://supermemory.ai/blog/jev-memory-context-engineering)
3. [I reverse-engineered Instinct's memory. Here's exactly how it works Instinct keeps its memory as git-tracked markdown files, found with grep rather than vectors. Here is the whole system as far as black-box probing can reconstruct it, and how to rebuild it on supermemory in about 60 lines. EngineeringSep 20, 2026 ](https://supermemory.ai/blog/reverse-engineering-instinct-memory)
4. [An update to supermemory We've discontinued the supermemory company brain and Nova. Everyone who was charged has been refunded, our MCP and plugins continue to run, and we're going all in on the memory engine. NewsSep 10, 2026 ](https://supermemory.ai/blog/an-update-to-supermemory)
5. [Scaling Conversations: How Adapta Grew Usage Without Losing Context Adapta added Supermemory as a persistent memory layer so every conversation keeps its context — letting the team scale usage without losing the thread. Case StudyJun 12, 2026 ](https://supermemory.ai/blog/adapta-scaling-conversations)
6. [How Chatarmin Ditched RAG and Went Memory-Only with Supermemory Chatarmin replaced a heavy RAG pipeline with Supermemory's memory layer — cutting average AI response time from 40s to 12s and token usage by 40–50%. Case StudyJun 10, 2026 ](https://supermemory.ai/blog/chatarmin-memory-only)
7. [SMFS: making agentic retrieval 55% cheaper AND more accurate We launched SMFS.ai (Supermemory Filesystem) a few weeks ago, with a simple bet: We can redesign the filesystem specifically for agents, with special files, structures, and commands that it can use for it's tasks. Today, SMFS is used by hundreds of companies to power their agents. EngineeringMay 28, 2026 ](https://supermemory.ai/blog/smfs-making-agentic-retrieval-55-cheaper-and-more-accurate)
8. [Introducing Dynamic Dreaming: supermemory now connects the dots, for you. Dreaming is magical. TLDR: We're launching Dynamic Dreaming in supermemory today, which automatically works if you're using supermemory in any way - API, OpenClaw, Hermes agent, etc. EngineeringMay 25, 2026 ](https://supermemory.ai/blog/introducing-dynamic-dreaming-supermemory-now-connects-the-dots-for-you)
9. [Dear reader, we just made supermemory insanely cheap... the Context Cloud When I first started building supermemory, I had one goal: To build the best memory system for AI. I would talk to customers, and find out that memory was not the only thing they needed - They were all setting up 7-8 different vendors at the same time. EngineeringMay 18, 2026 ](https://supermemory.ai/blog/dear-reader-we-just-made-supermemory-insanely-cheap-the-context-cloud)
10. [Introducing @supermemory/tools v2.0.0 Today we're releasing v2.0.0\. This release unifies the API across all agents sdk integrations from AI SDK to Mastra, makes conversation identity a first-class concept, and ships with memory saving on by default. EngineeringApr 27, 2026 ](https://supermemory.ai/blog/introducing-supermemory-tools-v2-0-0)
11. [Solving the Precision-Recall Tradeoff: Search Result Aggregation When you're building memory for AI, search is your foundational layer. The way search generally works is straightforward: the user defines a query, and then sets a limit (top-K) on how many search results they want returned. Usually, this is set to 10 or 20. EngineeringApr 5, 2026 ](https://supermemory.ai/blog/solving-the-precision-recall-tradeoff-search-result-aggregation)
12. [Stateful Coding Agents with Memory: Build Long-Running Agents (2026) We built a plugin for Claude Code and OpenCode that gives your coding agent persistent memory. It remembers your preferences, learns your codebase, and never loses context mid-conversation. The result is an agent you can run for months without starting over. EngineeringFeb 18, 2026 ](https://supermemory.ai/blog/infinitely-running-stateful-coding-agents)
13. [Clawd / Molt bot's memory SUCKS. We gave it supermemory. I'm the founder of supermemory. Clawd/Molt bot is blowing up right now, with many, many use cases. I set it up, too, and have been using it through telegram. TLDR: just go to https://supermemory.ai/docs/integrations/clawdbot to set up supermemory for your clawd bot. EngineeringJan 28, 2026 ](https://supermemory.ai/blog/clawd-molt-bots-memory-sucks-we-gave-it-supermemory)
14. [Catch up with our UNFORGETTABLE Launch Week Over the last year, one belief has guided almost everything we’ve built at Supermemory AI becomes meaningfully useful only when it remembers. Memory shouldn’t be something developers rebuild from scratch. It shouldn’t be fragile, expensive, or trapped inside a single tool. NewsJan 4, 2026 ](https://supermemory.ai/blog/catch-up-with-our-unforgettable-launch-week)
15. [Empowering the Next Generation of Founders: Supermemory Startup Program If there’s one thing we’ve learned while building Supermemory, it’s that most startups don’t fail because they didn't build features; they fail when infrastructure slows them down, or they built too slow. NewsDec 31, 2025 ](https://supermemory.ai/blog/empowering-the-next-generation-of-founders-supermemory-startup-program)
16. [Building code-chunk: AST Aware Code Chunking At Supermemory, we're building context engineering infrastructure for AI. A huge part of that is dealing with code: ingesting repos, understanding structure, and making it searchable. The problem is that most code chunking solutions are terrible. We built code-chunk to fix this. EngineeringDec 29, 2025 ](https://supermemory.ai/blog/building-code-chunk-ast-aware-code-chunking)
17. [Supermemory raises $3 million with the best memory engine for LLMs Today, I am excited to announce our first funding round to accelerate our mission of building an interoperable, scalable and reliable memory for LLMs and agents. Memory is one of the hardest challenges in AI right now. NewsOct 6, 2025 ](https://supermemory.ai/blog/supermemory-raises-3-million-and-building-the-best-memory-engine-for-llms)
18. [Mem0 vs Supermemory: Why Scira Switched Scira AI moved its production memory layer from Mem0 to Supermemory. This is what failed, what improved, and how the team evaluated the two systems. Case StudyOct 2, 2025 ](https://supermemory.ai/blog/why-scira-ai-switched)
19. [Never Record Again: How Montra Uses Supermemory to Rethink Video Creation Campbell Baron, the founder of Montra, has been making videos since he was twelve. By thirteen, he was already doing brand work. Today, he’s betting on a very different future for creators: a world where recording is the exception, and most videos are generated from scratch. Case StudyAug 21, 2025 ](https://supermemory.ai/blog/never-record-again-how-montra-uses-supermemory-to-rethink-video-creation)
20. [Unified Memory That Works Where You Work: Your Second Brain With Supermemory Hi everyone, I’m Dhravya, the founder of Supermemory. I want to start with a little story behind why this product means so much to me. You can also skip straight to what it is and how it works below. EngineeringJul 25, 2025 ](https://supermemory.ai/blog/unified-memory-that-works-where-you-work-your-second-brain-with-supermemory)
21. [Supermemory just got faster on PlanetScale What is Supermemory? Supermemory completes the missing part of the LLM puzzle: memory. Just as memory is crucial for human intelligence, it's essential for truly intelligent AI systems. EngineeringJul 18, 2025 ](https://supermemory.ai/blog/supermemory-just-got-faster-on-planetscale)
22. [Faster, smarter, reliable infinite chat: Supermemory IS context engineering. People are obsessed with prompts and prompt engineering. Sure, what you say is important, but what the model knows when you say it is the difference between a stateless text generator and an intelligent AI system. In short, context is the most crucial component. NewsJul 9, 2025 ](https://supermemory.ai/blog/faster-smarter-reliable-infinite-chat-supermemory-is-context-engineering)
23. [We solved AI API interoperability One API to rule them all, One spec to find them, One library to bring them all and in the TypeScript, bind them. When we were building the Infinite Chat API, initially, we only supported the OpenAI format. This was fine, until a lot of our customers started asking for more. EngineeringJul 7, 2025 ](https://supermemory.ai/blog/we-solved-ai-api-interoperability)
24. [The Wow Factor of Memory - How Flow Used Supermemory To Build Smarter, Stickier Products Overview: Flow is a note-taking app built around a bold vision: to create a more personal, context-aware writing experience powered by AI. At the heart of this mission is memory. Case StudyJun 14, 2025 ](https://supermemory.ai/blog/the-wow-factor-of-memory-how-flow-used-supermemory-to-build-smarter-stickier-products)
25. [The UX and technicalities of awesome MCPs Last month, we launched the Supermemory MCP, mostly to test our own infrastructure and get some initial traction. It blew up. To my absolute surprise, the initial launch itself got half a million impressions (!!!). Then, we launched and got #2 on ProductHunt too. EngineeringJun 8, 2025 ](https://supermemory.ai/blog/the-ux-and-technicalities-of-awesome-mcps)
26. [Architecting a memory engine inspired by the human brain Language is at the heart of intelligence, but what truly powers meaningful interaction is memory — the ability to accumulate, recall, and contextualize information over time. Large Language Models (LLMs) have mastered language, but memory remains their Achilles’ heel. EngineeringJun 5, 2025 ](https://supermemory.ai/blog/memory-engine)

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