IN THIS EDITION OF THE LEARNING STACK:
Why saving more never fixed my information overload
What an actual Capture, Organise, Distill, Express system looks like in practice
This week's newsletter is sponsored by Sana.

Sana Learn is what you get when you stop bolting learning tools together and build one platform that actually holds it all.
Most L&D stacks are an accretion: an LMS for compliance, an LXP for discovery, a separate authoring tool, a virtual classroom, each one a good app that doesn't talk to the others.
Sana collapses that into a single platform with an AI Tutor sitting on top of your whole knowledge base - Notion, Slack, Drive, your own courses - so a learner asks a question in plain language and gets a real answer instead of a search result.
It automates the admin most teams lose days to, enrolments and reporting included, and it's built to move business metrics, not just completion rates.
I have so many saved LinkedIn posts going back years. Hundreds of them. Every one of them meant something to me the moment I hit save: a line that stopped me mid-scroll, an argument I wanted to think about, a framing I knew I'd want again. I went looking through them recently and most of what I found was just a title and a stranger's name. Whatever they'd actually made me think was gone, because I never wrote that part down.
That pile of posts wasn't alone. Alongside it: a Notion workspace with two or three half-built systems inside it, none of them talking to the others. A trial of Obsidian that lasted about three weeks before I quietly stopped opening it. A running list of "second brain" tools I'd bookmarked to try next, itself a small monument to the problem it was supposed to solve.
You've probably got your own version of this. Maybe it's not LinkedIn: Kindle highlights, meeting notes, screenshots, a browser full of tabs you'll definitely get back to. The tool changes. The pattern doesn't: you save something because it mattered, build no bridge back to why, and the saving quietly becomes the whole act. The thinking and meta-cognition never happens.
It’s Not a Tools Problem
I'd been treating this as a tools problem (the right app, the right template, the right folder structure) up until now. That wasn't the issue. What actually mattered was whether anything I used talked to anything else I used. Nothing did. So every system I tried started again from zero, no matter how good the app was.
Finding OpenBrain

My OpenBrain Dashboard
What changed it was finding OpenBrain, an open source semantic memory project built by Nate B Jones. I now have one place to hold everything I’ve actually thought or decided, searchable by meaning rather than by which app or folder I happened to use that day. I set it up, and had it ingest a few weeks of scattered thoughts. I then connected it with a LLM, which surfaced connections across things I'd captured in completely different tools at completely different times, pairings I'd never have thought to search for together. That was the moment the real idea hit me: the fix was never a better note app. It was making everything I already used feed one actual memory, instead of each tool quietly hoarding its own slice of my thinking.
The Practical Bits
A few other things about it mattered too. It isn't locked to one AI assistant: OpenBrain is just an open server underneath, so it works with Claude today and would work with whatever I'm using in a year, without starting again from nothing. The thing making that possible has a name, MCP (Model Context Protocol), a shared standard that lets AI tools talk to outside systems without custom glue code for every single connection. That's a rabbit hole for a future edition, but it's worth knowing the name: it's the reason any of this could be built at all.
It's open source, so when Claude and I needed it to do something it didn't do yet (actually edit and delete memories, not just add them), we wrote that ourselves and added it, rather than waiting on someone else's roadmap. And the running cost is close to nothing: no monthly subscription, just a small, pay-as-you-go fee for the AI calls happening behind the scenes that turn what you save into something searchable by meaning.
Building It Properly
So, working with Claude, I built it properly. Notion stays for the operational layer: drafts, planning, the actual project tracking. OpenBrain became the one memory underneath everything, holding what I've captured and thought regardless of where it came from. Claude runs the automation between them: one instruction like "save this" now does in a single pass what used to mean opening three separate apps and filling in fields by hand.
This is the Claude setup I ended up with but everything here is portable and saved in a Github Repository

What a Morning Looks Like Now
A morning looks like this now: I read something that catches me, tell the system to capture it, and it asks me one thing back, not for a summary of what I just read, but what it actually made me think. That's the part that gets kept front and centre. The source stays too, but only for reference. My reaction is the point. A weekly pass then reviews what's piled up, sharpens ideas that keep recurring into one clear version instead of five scattered ones, and drafts newsletter and LinkedIn ideas straight from what the week actually produced, checked over before I ever see them, never published without me.
It maps, almost exactly, onto Tiago Forte's C.O.D.E. (Capture, Organise, Distill, Express). Except it isn't a framework I just read about any more. It's the actual shape of what happens every time I save something.
Four tools that didn't talk to each other were quietly duplicating the same struggle to remember, over and over, in four different places. One memory, fed from everywhere, is worth more than four good apps that never speak to each other.
More info:
Nate B Jones' OpenBrain project, the semantic memory layer that started all of this: github.com/NateBJones-Projects/OB1
Nate also has a fantastic newsletter and YouTube ChannelTiago Forte's Capture, Organise, Distill, Express framework, from Building a Second Brain, the shape I ended up building towards without setting out to.
Some interesting reading from my saves:
Nick Shackleton-Jones: A clean push/pull framework for why some learning experiences actually stick and others don't.
Onees Silié: PwC's 2026 data on why judgement, not prompting, is now the fastest-rewarded skill at AI-exposed companies.
Courtney Sembler: A sharp two-by-two on the difference between content that looks finished and content that actually changes behaviour.
If you are in a learning role, you could do worse than subscribe to The Customer Education Bi-Weekly. Eric Mistry does a fantastic job of curating the best posts, articles, and podcasts from across the Customer Ed world. Even if you are in a different area of learning, there is a lot to takeaway from every edition.
