[Blog](https://supermemory.ai/blog) · [Engineering](https://supermemory.ai/blog/tag/engineering)

# 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.

By Dhravya Shah May 25, 2026 · 5 min read 

![Supermemory header reading "Dynamic Dreaming connects the dots in your memory" — Warm points connect among leaves in a blue night garden](https://supermemory.ai/_astro/cover.6xMIpivO_Z229O9a.webp)

Dreaming is magical.

> TL;DR
> 
> We're launching Dynamic Dreaming in supermemory today, which automatically works if you're using supermemory in any way - API, OpenClaw, Hermes agent, etc.

We (humans) dream to condense and reflect on our thoughts, not only things that happened today, but a weird blend of everything that has ever happened. It's how we connect dots that don't have obvious wires between them.

A conversation you had three weeks ago clicks with something you read this morning, and you wake up with an idea that wasn't there the night before.

Most memory systems don't do this. They learn instantly, the moment data flows in, and then never look at it again. A fact gets written and it just sits there - a frozen snapshot of one moment, oblivious to everything that has shifted around it since.

Some systems take a smarter swing at this. Claude Code, for example, condenses its context when the window fills up, summarizing what's been said and packing it down. Better, but still a single pass. Whatever the summarizer thought mattered at that one moment is what gets kept. Everything else is gone.

We think both of these approaches have their own caveats - What if the conversation was only half done when you learnt something? Or what if the user asks about the last conversation in this one?

A user spends twenty minutes debating two architectures and lands on option B in the very last message, but the system already wrote down "prefers option A" from the middle of the discussion. Every future session is now quietly poisoned. Or what about the user who comes back tomorrow and asks about _yesterday's_ conversation, only to find that the only thing left of it is a three-line summary that decided, prematurely and forever, what mattered?

### Dynamic Dreaming

Memory shouldn't be a transcript. It shouldn't be a snapshot.

It DEFINITELY shouldn't be a hash table you write once and read forever (like other memory providers). It should _think about what it knows_, on its own, in the background, and get better at remembering you the longer it lives.

So we built dynamic dreaming.

Best part? If you're already a user of supermemory, **this will just work.** Use it in your OpenClaw, or Hermes Agent. Just ask your agents to use supermemory. No additional configuration is required on your end. You'll be able to see a "Dreaming" symbol next to memories that will be dreamt on.

### It just works

When you go quiet, or when enough new context has piled up, Supermemory will now enter a dream cycle on its own.

No cron job, no fixed timer. The system decides when, and it decides how deep to go based on what the heuristics tell it. A quick reflection for a short session. A longer dive when the day's worth of context warrants it.

During a dream, Supermemory does what brains do at night. It reconsolidates what it already knows. It merges fragments that belong together. It generates new abstractions over the raw material.

And the part that matters most: it reweights old facts in light of everything that's come in since they were written.  
Memories that were too confident get tempered.  
Memories that contradicted each other get resolved.  
Memories that were just sitting there, isolated, suddenly find their neighbors.

The output isn't a summary.  
It's three things at once: new memories, a graph of _inferences_ (we also call them derivations) that weave between them, and a weighted, evolving picture of who the user actually is. Not a static profile, but a thought-out view that updates as the evidence changes.

![Supermemory chat suggestion card titled "From Mumbai to CEO" asking how self-taught origins shaped problem-solving](https://supermemory.ai/_astro/image-1.Byvzb6NH_12j68P.webp)

The card above is a real inference. None of those facts were written together. The Mumbai jailbreak, the O1 visa, the two acquisitions, the GitHub stars. They came in over months, across dozens of separate conversations, in no particular order. Dreaming is what stitched them into a single thought. The narrative emerged on its own.

This is the thing we're most excited about: dynamic dreaming connects dots that, frankly, we thought were uncatchable.

**It is the closest thing I've seen to a context window that never expires.**

### Still real-time

This part took us the longest to get right. If dreaming takes time, what happens when a user asks about the conversation that just ended thirty seconds ago, before any dream has touched it?

Nothing breaks. Supermemory's hybrid retrieval keeps unprocessed content queryable the moment it arrives, falling back to conversation search for memories that haven't been dreamt yet. New context is available instantly. The dreamt state catches up in the background, at most fifteen minutes, and when it does, the agent gets a richer version of the same truth.

And every inference stays grounded. We don't let the system invent things it can't trace back to source memories. If it can't show its work, it doesn't get to claim the thought.

### What changes

Agents stop forgetting the things that matter. Contradictions get caught and reconciled instead of silently rotting in the index. User profiles stop being a brittle list of attributes and start being something closer to understanding. And the longer you use Supermemory, the better it gets. Not because it's accumulating more data, but because it's actually _thinking about_ the data it has.

We've been building memory infrastructure for a year. This is the first feature that makes memory feel less like a database and more like a mind.

Dream away.

Use supermemory today. [supermemory.ai](https://supermemory.ai/)

## Applying this in an application

When moving beyond a local prototype, use the [connector ingestion guide](https://supermemory.ai/blog/agent-memory-ingestion-connectors/) to test synchronization and permissions. Define [correction, retention, and deletion behavior](https://supermemory.ai/blog/memory-lifecycle-retention-corrections-deletion/) for imported documents and derived context.

Keep [source connectors separate from memory policy](https://supermemory.ai/blog/connector-provider-separation/) and test [whether remembered context improves the user outcome](https://supermemory.ai/blog/useful-agent-memory-acceptance-tests/). For research workflows, preserve [an evidence ledger](https://supermemory.ai/blog/research-agent-evidence-ledger/) so derived conclusions remain traceable.

## 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. [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)
9. [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)
10. [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)
11. [OpenClaw Memory Problems: Why It Forgets and How to Fix It (2026) TLDR: Today, we are releasing a new version of our openclaw plugin - 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. EngineeringFeb 19, 2026 ](https://supermemory.ai/blog/why-everyone-is-complaining-about-openclaws-memory-it-sucks-and-why-supermemory-fixes-it)
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)

## Start building with supermemory.

Memory and continual learning for any model, any harness. Available through our API, plugins, and MCP.

[Build with supermemory ](https://console.supermemory.ai/)