Claude + Obsidian turned out to be a practical memory layer: capture → structure → retrieve → compound. Are you running this loop yet?

it's funny that the people who think this system is pure hype and not practical at all are actually the ones missing out this time. we're not talking about a trojan horse system where you start using another useless note-taking app and waste your time structuring your ideas instead of using them. the whole point of "second brain improvements" is to actually use that brain to improve quality and speed. that was the bottleneck of past systems. this is completely different. few get this.

On point, the old failure mode was ‘capture theater’ — endless organizing, no execution. A real second brain should reduce decision latency and increase output quality in live workflows. If it doesn’t improve speed + quality, it’s just polished procrastination.

hey Nyk have you seen my article yet? I think you’d find it compelling. Heck even just give it to your agent.

Hey — I did read it, nice work. The ytscribe pipeline is legit, and the write-up does it justice. Quick thing I wanted to flag: a good chunk of what you're presenting as the autonomous layer — the nightly orchestration, dual-harness routing, GPU pre-flights, quality gates, memory stack, brain-ingest, provenance chain — that's all LACP running underneath. You gave me a nod for "compounding control plane" which I appreciate, but LACP itself never gets named or linked. Someone reading it would think you built that whole layer from scratch. Would you mind adding an attribution that names the project and links the repo? I'm genuinely glad to see the work in the wild — just want the foundation to be set transparent. Cheers mate.

To clarify - ytscribe doesn't use LACP. I cited your 'compounding control plane' concept, but the orchestration layer is custom-built. Many of the control gateways were already implemented into the system weeks ahead of discovering your “Control Plane” article. The corpus simply used the article to describe what was already built. We both seemed to independently arrive to similar solutions, and thus similar nomenclature.

Thank you for the clarification! I guess we are all building towards the same and around the same idea mindset 🤝🫡

Running a version of this. The key insight is that the structure step does most of the work. Capture is easy. Retrieval is solved. But if you don't structure it in a way Claude can reason over, you just have a pretty vault collecting dust.

Exactly right. Structure is the bottleneck nobody talks about — everyone optimizes ingestion speed and retrieval recall, but the quality ceiling is set by how well your intermediate representations map to the way the model actually reasons. That's why LACP treats the knowledge graph as a first-class layer with its own quality gates and provenance, not just a dump target. A vault without governance is just a fancy file system.

Check out @getcontexto, and Openclaw plugin I'm building which allows you to connect your @Obsidian vault and use it as a knowledge base with openclaw

@getcontexto @Obsidian Nice I’ll check

the AI that remembers your context compounds faster than the one that doesn't. memory is the real moat

🧑‍🚀

@nyk_builderz not yet but this sounds super helpful. gotta get better at retrieval, I always forget stuff I swear!

Can this work with openclaw?

It can - someone built an OpenClaw version of my LACP stack - need to dig it out

Basic Memory works well for this. Its all markdown, mcp tools or cli to read/write notes. Tracks relations, semantic search, etc. Everyone should own their own data. Open source, local or cloud.

Claude + note tools like Obsidian compound knowledge 3–5x faster for solos than standalone chats.

💯 🧑‍🚀

Protecting my data too tight? What's your trade-off?

Even better is Claude + Coreviz to give your AI a *Visual* Memory →

@mitko_wtf

@mitko_wtf 🧑‍🚀 you know you want it @mitko_wtf

Yes. It’s amazing. And I’d add it’s excellent for storing/retrieving session transcripts. I have /session-store and /session-restore skills for saving/reading full sessions + summaries to Obsidian. Useful for when I need to perform system updates or continue work on another device.

I like what I see 👀

Where’s the best guide that shows are by step how to set this up and how it practically works for non-techies

You can basically follow these steps:

Claude's chunking in Obsidian works well for retrieval, but token limits hit hard on compound loops—especially around 100k contexts. Using Dataview for metadata filtering now. How do you handle multi-hop reasoning across vaults? 🤔

That’s the pattern I run on top of LACP’s brain/retrieval gates, not a one-command default pipeline yet.

Makes sense. The routing logic for multi-hop is always the hardest part to standardize. Keep iterating on those gates, would love to see a deep dive when it's a default pipeline!

🤝👨‍🚀

I pointed Hermes to this article to try such a thing.. guess not enough data yet. Any way to publish a skill or something for us plebs 🌞🙏🏽 Saw the awesome agent repo that looks nice too but haven’t unpacked yet

This is exactly the problem I keep seeing: teams don’t lack AI access, they lack a durable memory layer. Re-explaining context every session is hidden tax. I’d add one more layer: automatic capture of key AI conversations into Markdown decision logs, so Obsidian becomes not just memory, but reusable execution context.

What is this graphical interface visual and what is it built off of?

It's Obsidian (@obsdmd) - the logic is LACP

Are you able to explain the full setup. That would be great!

@blenz2002 Yes, I will do a thread on it

Looking forward to it

Yep. Ridiculously powerful. Wrote up my setup here:

Smooth brained C- student from Downriver, Detroit. Cutting corners into radii as per usual. Setting up itself so far