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One of the biggest limitations of Anthropic's

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Claude models today is the lack of true persistent memory across sessions, and this is due to sessions being stateless by design as well as them having a small context window in comparison to other models like Gemini.

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When a chat or coding session ends, the model usually starts fresh the next time. This is where Claude forgets your project context,

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decisions,

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and past work. That means you're forced to actually re explain everything again and again, which not only wastes time, but also burns through your tokens on repeating context instead of actual useful generations.

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This constant repriming

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eats up into your token budget,

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leaving fewer tokens for real reasoning, full use, and high quality output.

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In practice, that can even limit how effectively Claude can use tools or produce deeper, more thoughtful results

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because so much of the budget is actually spent just getting the model back up to speed. But there's a solution to this, and it's called CloudMem.

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CloudMem turns CloudCode into a tool that actually remembers your project history across sessions,

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so you don't have to re explain context every single time.

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Instead of forgetting everything when a session ends,

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Claude memory or Claude mem automatically

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captures what Claude does with tool usage, decisions,

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and observations,

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then compresses that information

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and stores it into a local database with vector search.

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It can inject relevant context back into future sessions so Claude truly remembers your project.

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On top of that, it lets you search your past work using natural language through mem search and MCP tools. And the best part is is that it's open source and runs automatically in the background once you install it. Now to test the impact of persistent memory,

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I used the same detailed dashboard prompt twice, once with claud in a stateless session and once with ClaudeMem enabled.

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And there's definitely a drastic impact in terms of the differentiation.

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Without ClaudeMem,

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Claude was able to produce this functional dashboard,

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but it missed a lot of project specific details. There's a couple of errors already showcasing

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when I am scrolling through this dashboard, repeated generic patterns, and required more iterations to actually align with the editorial.

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The high end product design that was described in this prompt wasn't actually outputted

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with this generation.

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Whereas if I'm to compare it with the CloudMem generation,

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it remembered previous decisions, the tool usage,

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as well as the context from prior sessions, which resulted in a cleaner, more precise dashboard

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that followed the design constraints.

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And you can see that there's subtle interactions with each component, the signature feature

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exactly that was intended from the prompt that was actually sent in. Now I'm not saying that it is perfect because you can see that this generation over here with the chart doesn't look as great. But in terms of adding all of the required features that I'd asked for was added with this generation with Claudemep. The difference clearly shows how persistent memory directly improves output quality, which reduces redundancy

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as well as allows the model to focus its token budget on creating thoughtful production ready UI

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rather than just reconstructing context.

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feature flags,

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Posthog is worth checking out with the links in the description below.

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Now there's a couple of prerequisites that you're gonna need to have beforehand. You're obviously gonna need to make sure you have Cloud Code installed beforehand.

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If do not have it, you can easily install it for whatever operating system you have, then just make sure you have Node dot g s 18 or above, bun installed u v, and then SQL lite three for persistent storage. And once you have all these requirements fulfilled, we can then get started with the installation. It's super simple. All you gotta do is go into your terminal and just start up cloud code using the Cloud command. Once you have it running, use the slash plugin command, and then what you wanna do is head over to the marketplace by using the arrow key on your keyboard, and you're gonna go ahead and add a new marketplace, and that is by clicking enter.

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This is where you're gonna need to go back into the repo or this doc.

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Essentially, what you wanna do is just copy this last section

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of the creator as well as the repository name. And then what you wanna do is just simply go ahead and paste this in into the add marketplace section and click enter.

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This will clone the repo. Then you'll see within the marketplace section

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the new CloudMem marketplace,

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and you wanna click on enter. You wanna browse the plugin, and you wanna go ahead and install CloudMem if you haven't already. After installing, it's recommended that you close Cloud Code, and then you can restart it back up, and you should have CloudMem now working within your Cloud sessions where you're gonna be able to have persistent memory

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across all of your sessions.

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Now this is gonna be a huge feature that will help you in so many ways. You can see right now that bunnett is actually running, which is also gonna let you view this with the web viewer UI,

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which is where it's gonna prompt open this UI for you to actually manage your session

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as well as have it so that you can interact with your memory. Now there's a lot of different commands that you can use with CloudMem, like injecting your own memory directly within all of your sessions, which is something that you need to be really careful about. Because if you inject the incorrect memory, it could be interfering with future generations and sessions, which is why it's recommended that if you're working with the production build, might wanna consider that you should turn off CloudMem in certain cases. But now that CloudMem is enabled, you have a full cycle where you can now use this memory feature, that persistent memory where it's gonna be able to read all of your files, write them, it can edit, use bash, glob, grep,

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all other cloud tools,

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and it is gonna capture all of that with this persistent memory locally.

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And you're gonna be able to even retrieve context with the slash, uh, commands to even have it so that you can pull and even inject new memory.

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And right now, you can see that there's two new, uh, commands that you'll see. The cloud mem do, which is where you can execute a plan using sub agents for implementation,

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which is a pretty cool new feature, and then creating an implementation plan with the documentation discovery.

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So two of these features can go hand to hand. But you can see right here that I had requested to create a landing page,

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and it is gonna use the plan tool with the memo feature.

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And you can see that it is using multiple tools to help me execute this task right away. Also, an FYI, if you use the MCP tools, you're gonna be able to get better memory search with your project history,

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and you can easily enable this with the link in the description below, which showcases how you can set this up. But you can see that it has created multiple phases as to how it is actually gonna create this, so let's go ahead and have it work upon creating this landing page for us. And here we go. Now I wanna give you guys some context as to why I created a landing page. What does that actually do with persistent memory? Well, the thing is is that I actually went ahead and injected

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a lot of my previous catalogs of landing pages, And I had it reference all of those landing pages because I was gonna have it remember my context that I had with previous generations.

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So I didn't have to re explain what sort of output I was looking for because clearly if you are to request any AI model to generate a landing page, it is gonna generate that typical purple

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AI SaaS landing page that you don't wanna see. In this case, it saves up 95%

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of the tokens each time that you start a session. There's far more tool calls to get the best generations outputted.

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And with memory preserved, you can have it so that Claude can make 20 times more tool calls with ClaudeMem enabled, which is why I get these beautiful generations out of it. And I kid you not, this is another landing page that I had generated with the same prompt, and in this case, it was able to use the catalog of typography

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UI elements that I had saved through other

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generations that I had injected into claudamem, and you can see that it did do a great job with this interactive landing page that was created in a single shot. If you like this video and would love to support the channel, you can consider donating to my channel through the super thanks option below. Or you can consider joining our private discord where you can access multiple subscriptions to different AI tools for free on a monthly basis,

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plus daily AI news and exclusive content, plus a lot more. But that's basically guys for today's video on CloudMem as to how you can have persistent memory across all of your sessions within Cloud Code. This is a remarkable project and there's a lot more to this. You're only gonna get to understand the true capability of it as you use it more and more as you build up your persistent memory

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and have it used across all of your sessions. I'll leave all these links in the description below so that you can easily get started. But if you haven't already, make sure you go ahead and subscribe to our second channel. Join the newsletter. Join the Discord. Follow me on Twitter. And lastly, make sure you guys subscribe, turn on notification bell, like this video, and please take a look at our previous videos so that you can stay up to date with the latest AI news. With that thought, guys, have an amazing day. Spare positivity, and I'll see you guys fairly shortly.