Byterover - Memory layer for your AI coding agents
Byterover is a self-improving memory layer for your AI coding agents—create, retrieve, manage vibe-coding best practices across projects and teams. You can start now by installing Byterover's extension via your AI IDE like Cursor, Windsurf, and more.
Replies
Byterover
MindPal
@andy_byterover congrats for the launch
Byterover
@maiquangtuan thank tuan; it would be grate if mindpal team can try and leave us your feedback
@andy_byterover Nice products bro, congrats for the launch!
Byterover
@tonyhothu Thanks so much, Tony — your support really means a lot to us!
Byterover
Hi builders everywhere, we can’t wait to see what you all do with our memory layer!
We’ve launched an earlier version. From Solana trading bots to automated Meta Ads tools, we’re seeing builders use Byterover for a variety of use cases—not just to store coding practices, but increasingly to capture vertical business logic of the application as well. Some use us to switch seamlessly between Cursor and Windsurf, and others without losing context.
Looking forward to seeing what you can build with our memory.
Byterover
@minh_phan6 it is exactly what byterover is buit for, this is the way we can fuse our knowlege with the agent's capability, kind of "context" engineering
MindPal
Congrats on the launch guys!!
Byterover
@sylviangth thanhs Tham!
Congrats on the launch! I'm trying it for myself but curious about how does Byterover handle conflicting coding practices when sharing memory across teams?
Byterover
@chanitypham Hey, thanks a lot for the awesome question! So, ByteRover is what we call an “agentic memory” — basically, there’s an internal agent that handles all the memory stuff for you. Here’s how it works: when it notices a new coding experience, it creates a memory for it. If it sees something needs to be updated with new concepts, it updates it. And if it finds a concept that clashes with an old one, it’ll delete the outdated memory and replace it with a fresh one. Hope that makes things a bit clearer!
I would love of it had like a api version or something we could integrate into our own app as a memory layer would love of if it could happen.
Byterover
@its_abhinav_jangid Hey! Thanks for your question. We’re planning to add more connection interfaces in the next release (coming soon!) so you’ll be able to connect ByteRover to your application via API calls. Right now, we’re focusing on IDE support, so MCP is the current connection interface we’re using.
@andy_byterover Thanks anyway you could notify me for early access or when you release. Killed the launch btw 👏
Byterover
@its_abhinav_jangid I’ll let you know as soon as our upcoming release is available.
For early access, we’ll notify you about our open-source version — you’ll be able to connect it to your app via APIs or MCPs, whichever works best for you. Plus, you’ll have the flexibility to customize it to suit your needs. We’re aiming to release it soon, likely next week!
Congratulations on the launch! Byterover’s approach to persistent memory for AI coding agents is truly innovative. Do you see potential for expanding this memory layer to enhance team collaboration?
Byterover
@hi_caicai Hey, thanks! We already support team collaboration — you can create an organization then workspace, invite your team members, and start collaborating on the same memory workspace. (This is actually how we’re using ByteRover ourselves right now!)
Byterover
I believe Byterover is solving a real pain of almost all developers right now, and the movement of AI coding is just in the early phase.
This is massive. 🔥 Congrats on the launch, guys!
Byterover
@polsabandal Thanks! It would be great if you could try it out and leave us some feedback about the product. We’re rolling out lots of improvements and updates very soon!
Congrats on the team! I wonder if there will be bi-directional syncing between the memory feature of each IDE supported?
Byterover
@kynamng Hey Nam, thanks so much for your time! That’s a great suggestion, and we’ll definitely work on it — it could bring a lot of value to users. Here’s what we’re thinking: right now, the memory generated by Cursor is written as rules. We’ll have an MCP server hooked up to our extension that reads those rules and syncs them into ByteRover memory. We’ll keep experimenting with this — excited to see where it goes!
MagicSlides App
Congratulations on the launch duy, but isn't this something cursor is adding in built?
Byterover
@indianappguy Hey, thanks! So, Cursor’s memory is just one of their features — but for us, memory is the product. There are three main things that make us different from Cursor:
1. Under the hood, we use both a vector database and a graph database to store memories for your vibe coding agent. This means the agent can retrieve memory semantically, with extra structure and context captured from the graph.
2. Memory is fully managed by an agent, so you don’t have to worry about how it’s stored. Everything — creating, updating, deleting memory — is handled automatically by the agent (we call it “Cipher” internally).
3. Our memory system is IDE-agnostic, so if you switch from Cursor to another IDE, it’s plug-and-play — and it just works.
Awesome products! Didn't know what i would do without this Cursor memory doesn't allow exporting to other tools 🥹
Byterover
@kynamng Hey Nam! Really appreciate your idea about syncing Cursor’s memory with ByteRover — it’s a great one, and we’re definitely working on it. Stay tuned, exciting stuff coming soon!
@andy_byterover
Byterover quietly solves one of the most overlooked pain points in AI coding tools: they forget you. Your naming patterns, folder logic, the way you structure handlers or write that one clever utility file—it’s gone the moment you change context.
But Byterover? It’s that one AI layer that actually remembers how you code, not just how code works.
🔍 What it really does?
Byterover adds a “memory vault” inside your IDE (Cursor, Windsurf, Zed, etc.)—letting your AI coding assistant store, retrieve, and reuse your logic across projects, or even across teams. It’s like giving Copilot long-term memory without giving up control.
🚀 Why it matters?
If you’ve ever had to teach the same abstraction or structure to your agent three times in three projects… you know the frustration. Byterover stops that loop.
You can:
Organize memories by workspace/project
Prioritize by starring key examples
Share patterns with teammates, so your assistant collaborates like a real dev partner.
It’s one of those “why didn’t this exist sooner?” moments. The fact that it fits inside your current IDE flow—no switch, no lock-in—is a smart move too.
💡 Creator-to-creator suggestion
Right now, memory feels project-based and dev-centric—which is powerful. But imagine this taken one level up:
Tags or categories to link design patterns across different stacks
Memory snapshots for comparing evolution of logic over time
Maybe even contextual comments where the agent reminds you why a decision was made
That’s not a shortcoming—it’s a horizon. And knowing how tuned-in the Byterover team is, I wouldn’t be surprised if that’s already on the roadmap.
🛠 Real-world workflow
Let’s say you’re building a Node API and always abstract your services in a specific way. Byterover sees the pattern, remembers it. On your next project—or your coworker’s—the agent auto-suggests the same structure, imports, file split, naming logic. It feels like that one AI dev who just gets your style.
And with team memory sharing, you're not just saving time—you’re scaling consistency.
🎯 The verdict
Byterover isn’t just another AI wrapper—it’s memory infrastructure. Lightweight, dev-native, and meaningful.
It’s exactly the kind of tool we spot and track at ThatOneAI—those subtle game-changers that improve how builders actually build.
Seems very powerful, how much better would this be than cursor rules?
Byterover
@skyler_ji Hey Skyler, thanks a lot for the great question!
We think the Cursor rules system is an awesome feature for customizing agents — and ByteRover is built to support that in a few key ways:
• It’s especially helpful when you need to store domain-specific concepts, like if you’re building an investment platform, trading bot, or asset management tool. These kinds of apps usually require a lot of specialized knowledge, and ByteRover makes it easy to save and retrieve that.
• Behind the scenes, ByteRover uses semantic search, which makes it much more efficient for your agent to find the right information when it needs it.
• Another nice bonus: ByteRover is IDE-agnostic, so your teammates can use it with whatever IDE they prefer!
Let us know if you have more questions — we love hearing from you!
Congrats on the launch. The idea of agents remembering context inside the IDE is spot on.
Curious how you're handling memory under the hood. Is it something devs can inspect or tweak?
Byterover
@kareemayyad thanks Here’s a quick breakdown of how ByteRover works behind the scenes:
We’ve built an agent that takes care of all the memory management tasks for you — it handles concept detection, creates new memories, updates existing ones, and removes outdated stuff when needed.
For storage, we’re using both a vector DB and a graph DB. This combo helps us capture not just the meaning (semantics) but also the structure of the agent’s experience — all to support smarter reasoning for vibe coding agents. I’m a developer myself, and honestly, I hate when we don’t have full control over things. So in the next version, we’re giving users more power — like being able to edit memory directly. We’re even planning to open-source the memory agent, so you can plug it into your system however you like.
Good jobs team! I wonder if it will be possible to edit the memory on the dashboard later? While the agent has done a pretty good job of analyzing and summarizing the context, I think there will be cases when we might want to edit the memories ourselves (e.t.c, security / customization of memory).
Byterover
@anh_nguyen78 The memory edit feature has been one of the most requested — and we’ve made it a top priority! It’s coming very soon, so stay tuned!
This has improved my dev workflow since I can easily manage the memory for the AI model, so requiring fewer prompts to fix bugs or code convention. It would be even better if you could initialize a starting memory for any particular project, like if you could scan the entire codebase and detect the framework, how code is organized, etc., so that any new users could instantly see the value of it.
Byterover
@builechibao Hey! Huge thanks for your feedback and awesome suggestions
We’ve added them to our release plan — keep the great ideas coming!
Really appreciate your support
A promising Vietnamese product. Wishing the project great success!
Byterover
@quang_vu_l_u_cong thanks it would be great if you tried out the product and leave us the feedbacks
Scrapeless
Hi Byterover AI team,
Big congratulations on your product launch — it looks truly impressive and caught our attention! 🚀
I’m Liam from Scrapeless. We build browser infrastructure and scraping tools designed for AI — including our Scraping Browser, ChatGPT Scraper, and Deep SERP API — helping companies get structured data quickly and reliably into their AI workflows and analytics systems.
We’d love to offer you free access to our tools in exchange for a mention or shoutout on your Twitter or LinkedIn. We’re also happy to cover any promotion costs to help boost your visibility.
If this sounds interesting, I’d love to chat more — feel free to suggest a time or just reply here!
Best,
Liam
Widgera
Byterover
@demetre_mildiani1 Hey! Thank you so much for trying us out and leaving feedback. We’re on a mission to make vibe coding better for everyone. Features like memory — or even better, an evolving knowledge hub — will be a big win for developers who love working with AI coding agents. We’ve got more exciting features coming soon, so stay tuned!
Thanks again for all the support
Slashit App
Congrats on the launch!
Byterover
@rakibulism thanks !!!!