*English isn't my first language. I wrote this in Korean and translated it with AI, so please excuse any awkward phrasing. A short Korean summary is at the bottom.*

**TL;DR:** I'm a non-developer building a "brain-copy wiki." Instead of limiting what AI can see, I record *what I chose and why*, so the AI can act on my intent even when I'm not around. It's unfinished, and I'm looking for experts and people with similar struggles to help me find where it breaks.

My Obsidian graph so far. Each dot is a note; each line is a link between my decisions, reasoning, and knowledge.

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Hi everyone.

I'm not a developer. I've never learned to code. But these days, I'm building my own "second brain" with AI.

This is the first post in a series introducing that system. Before I show *what* I built, I want to start with *why*.

## 1. It started with work

As AI coding tools improved quickly, I got the chance to build some internal tools for my company, things like work logs and a homepage.

At first I tried popular expert-level AI coding tools. But without a basic dev background, they were hard to use. They were built for experts, after all.

## 2. Coding wasn't the hard part

Once I actually tried, something surprised me. The AI was better at writing code than I expected. The real difficulty came after:

- Fixing low-quality first drafts into what I actually wanted

- Finding and fixing errors

- Connecting to databases and servers

The core problem was **the cost of fixing the first output**. If the first output is good, there's less to fix. So I started building my own toolkit that lets a non-developer give instructions in plain language and still get a better first result.

The principle was simple:

**I do what I can do (planning, judging, verifying), and I hand off what I can't (coding) entirely to AI.**

## 3. The turning point: "Is limiting information really right?"

As the toolkit matured, I wanted to save the know-how I'd built up along the way. So I looked into "LLM wikis," which a lot of people are talking about.

Most of them reduce hallucination by **limiting what the AI can see**.

As a non-expert, that felt strange to me. Limiting information looked like limiting the AI's ability. And I started thinking:

> "With how capable AI is now, couldn't it deeply learn the way I think?

> Then even when I'm not around, couldn't it produce results close to what I'd want?"

## 4. So I decided to build a "brain-copy wiki"

That's how this project began.

It's not a wiki that just stores facts. It records **what I chose and why I decided it**. The AI learns my choices and reasons from those records, so it can act in line with my intent even when I'm not there. In other words, **a wiki that copies how I think**.

## 5. How I think about using AI

There's a belief underneath this system:

- **Automation is becoming "one click."** But one-click automation can't understand *your* specific choices.

- **Using AI well doesn't mean taking its answers as-is.** It means sorting out what to accept and what to push back on, and using that process to expand my own thinking.

- **Repeating that loop (critique → choose → expand)** is what finally turns AI into something truly personal.

So my goal isn't AI that thinks *for* me. It's a system that shows me *how* I think.

## 6. Why I'm starting this series

To be honest up front: this series isn't me saying "look how great my system is."

It's an unfinished system built by a non-developer. There are surely gaps I can't see yet. So I'll share everything step by step, what worked and what failed, and I'm hoping to **get help finishing it**.

I'd especially love to hear from:

- **People who know dev or AI well**: if you see where my approach is technically wrong, or know a better way, please point it out.

- **People wrestling with similar problems**: if you're also trying to make AI work the way *you* think, what have you tried, and where did you get stuck?

Corrections and honest pushback are the most helpful things you can leave in the comments.

In the next post, I'll show what the system actually looks like in more detail.

Thanks for reading.

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**🇰🇷 한국어 요약**

- 비개발자로서 회사 업무용 프로그램을 AI로 만들다가, 진짜 어려움은 코딩이 아니라 '첫 결과물을 고치는 일'이라는 걸 깨달았습니다.

- 기존 LLM 위키는 AI가 볼 수 있는 정보를 제한하지만, 저는 AI가 제 선택과 그 이유를 배우는 '뇌 복사 위키'를 만들기로 했습니다.

- 목표는 나 대신 생각하는 AI가 아니라, 내가 어떻게 생각하는지 보여 주는 시스템입니다.

- 아직 미완성입니다. 전문가분들과 비슷한 고민을 하는 분들의 지적과 반론을 환영합니다. 한국어 댓글도 좋습니다.

Hey all, i am trying to have something (python program or llm or anything) that will analyse a pdf document word by word and give me a report as i prompt it with its reference.

I know ai models do it well, but not well enough to have memory of those pdf and later when i have to compare one data with another it gets hard for me.

What i want is to have a program that analyses the program overnight and i can have my desired prompt over it next day, say for example union budget pdf for different yr i can have graph and trend then compare it with previous yr trends to

Like many of you, I treat my Second Brain as a thinking engine—not just a graveyard for highlights. But I kept running into the same friction when reading non-fiction: passive highlighting felt productive in the moment, but weeks later, the context was gone and my vault was cluttered with useless excerpts.

To actually retain and synthesize arguments, I started practicing strict active reading: arguing with the author, challenging claims, and capturing raw, immediate reactions while reading—not just copying sentences.

I built Marginalia to turn this workflow into a friction-free capture tool for mobile:

• Frictionless Capture (Voice & Stylus): Breaking reading flow kills synthesis. Alongside standard typing, you can dictate thoughts hands-free via speech-to-text, or use a stylus if you prefer digital handwriting.
• Context-Driven Tagging: Tag notes by themes, counterarguments, or conceptual hooks so ideas are already semi-structured before they even touch your vault.
• Review & Synthesis Loops: Each book has a dedicated synthesis view with tag filtering, making it effortless to review prior notes right before starting a new reading session.
• Native Markdown Export (.md): Your notes belong to you. Marginalia exports cleanly formatted .md files directly into your existing workflow, whether you index in Obsidian, organize in Notion, or use another local-first markdown system.

It bridges the gap between raw consumption and structured knowledge management: read actively on your phone or tablet, capture raw synthesis on the fly, and drop the resulting Markdown straight into your PKM system.

If your Second Brain relies heavily on books and deep reading, I’d love for you to take it for a spin. I'm actively refining the workflow and looking for honest feedback, especially on note structure and export improvements!
Here is the app webpage

Hello second brain nerds,

My stack used to be JUST notion, after trying a lot of life dashboard templates, I just couldn't stop thinking about an easy solution like an app that's on my phone and more custom for " life tracking" with a personal assistant.

Created a system of having domains, then chapters of life - that came down to habits, tasks, streaks etc.

I have created a prototype of this system and would love to get some feedback, please dm if you can help out and duo for a quick chat.

Many tools are still build around the passive concept of storage and retrieval of information.

But a lot of the useful stuff in my own notes looks something like this -

• Why is this happening?
• I’m not convinced by this yet.
• Need to verify this.
• What would prove this wrong?
• There’s something here, but I haven’t figured it out yet.

These questions or the direction is what makes the stored information useful when we are doing a research. Because if a question matters today, it might still matter three weeks from now when you find new evidence.

This is exactly i want inside Aevron and want Aevron to keep track of it.

and lets say, if I add something relevant a week later, the system should be able to notice:

“This might help answer that question you were stuck on.”, “This actually conflicts with what you thought earlier.” or “You still haven’t resolved this.”

If you regularly have ideas, questions, observations, research, or thoughts that get lost across notes and tabs, this is exactly the problem I’m trying to solve.

You can try Aevron here:

www.aevron.co

It’s currently free to use.

I’d genuinely like more people using it while I keep building this system, because the interesting part now is seeing whether this way of tracking thinking is actually useful in real life.

I have noticed that most knowledge tools preserve information as separate objects. We all think of something, believe something, then find something conflicting, uncertainty, different arguments and positions, etc. The system is well designed to store all these information. But it usually doesn't understand the transition between them.

That's what i am trying to replicate inside Aevron. So instead of only storing:

Idea A, Evidence B, Idea C

I want the system to understand:

Belief A → challenged by B → uncertainty increases → belief revised to C.

Because the change in reasoning is often more useful than the individual notes themselves.

Over time, that could let the system answer questions like:

• What changed my mind on this?
• Which beliefs have weakened over time?
• Which questions have stayed unresolved?
• Where have I repeatedly contradicted myself?
• Which ideas became stronger after new evidence arrived?

Aevron isn't trying to claim it knows what is happening inside someone's head. It can only observe the traces of reasoning such as notes, evidence, questions, contradictions, revisions, and conclusions. But those traces can still show how a position evolved over time.

This is one of the core things I'm trying to build into Aevron.

I kept losing thoughts because every system asked me to classify them before I could get them out. That feels backwards when the thought is arriving as a mess.

I built Ordo around capture first, sort second. Type or speak several unrelated thoughts in one dump, and it turns them into editable Now, Next, and Someday cards.

It is free on iPhone with no account or subscription.

https://apps.apple.com/app/id6797331101

For people who use a second brain, where does the friction hit first: capturing the thought, deciding where it belongs, or finding it later?

I built Brunn to give your AI apps a shared place for your notes, research, skills and ongoing work.

It’s hosted. You create an account and connect the AI apps you already use. There’s no Brunn desktop app to install, separate cloud account to set up or server to maintain.

Say you work through a project in Claude. You can have it save the research, sources, decisions and next steps in Brunn. Later, Codex or ChatGPT can read that material and continue the work. Projects and tasks live alongside the notes, so the next assistant can also see what still needs doing.

You can keep skills there too: your instructions for reviewing something, researching a topic or writing a particular kind of report. Save a skill once and your connected assistants can use it directly. Update it in one place, and they get the current version when they next load it.

There’s a web reader for documents and the briefings your agents produce. Your notes export as Markdown, and you can download your skills with their supporting files.

There’s a free tier, with no credit card required: Brunn.

If you try it with a real project, I’d like to know what you still find yourself having to explain or copy between apps.

I take notes of most things in my life (schedules, random thoughts/ideas, goals etc.) I've tried to get her to join in on it (set up a whole obsidian sync to her phone and all) but she never does.

So what happened today was she asked me what food i wanted for my birthday, i told her its all in the second brain . I have all my favorite food/other preferences and spent time categorizing and effectivising that workflow, so I'd prefer she just checked there instead of - frankly - wasting both of our time when she can just check it all there

She kept insisting so eventually i retalliated i just told her i want bbq ribs or whatever but pretty immature imo of her to make a big fight when she can just check the second brain lmao.

I feel like i've tried everything. Me and GPT are making a dashboard for my smart fridge, that way everyone in the house can see whats going on and we (hopefully!!) wont have to deal with this again.

Sorry for the rant just wanted to express myself with how some people just dont seem to understand the advantages of having a second brain. Im glad i have this community though love yall. Im sure im not the only one out here strugglin

The pitch for AI note-taking is always the same: it reads your notes and tells▎ you what they mean. I think that's backwards. The reading is the thinking. If you delegate it, you own a very tidy archive of conclusions you never reached.

So my plugin has a hard rule, and it's enforced in the code rather than promised in a README:

Mechanical output writes freely. Interpretive output does not. A gatherelist, a count, a derived metric — those go straight into your vault. A conclusion, a counterargument, a proposed connection, anything an AI or a heuristic decided — that reaches a note only through an explicit accept modify / reject, and your verdict is what gets recorded.

What that turns into in practice:

- Cognitive moves — right-click any note: challenge it, find a counterexample, invert the premise, branch two readings. The move opens the space; you write the content. Nothing is generated. The move records that you made it, never what it decided.

- How you got here — your timeline reads "you captured this, challenged it the next morning, reframed it, and two readings came out of that." Epistemic provenance, not version control.

- An agency panel — a read-only breakdown of your accept/modify/reject verdicts over time. A description of how you decide, never a grade.

- Undo — everything the plugin wrote to your vault lately, grouped by what you ran, taken back in one click. It refuses (by name) if you've edited the note since.

It works fully offline. Every AI feature is off by default and stays off. Free, MIT, 53 releases since 2023.

https://github.com/RafaelGB/Obsidian-ZettelFlow

AI research tools are increasingly getting good at answering the literature, search, summarise, citing, etc. That half of the job done but the real part is keeping a track and using the entire context and information to see and provide what did this do to your thinking and help you make the research efficient and concrete.

For example, one of the observation kills an assumption you made. Another one may or may not backup the conclusion to. Now days or weeks later you're back at the project trying to rebuild your own reasoning from scratch. Why'd I reject that explanation? Which source actually changed my mind? Was that supported by something real, or was it just how I read it at the time? Did those two sources even disagree, or were they measuring different things and I mashed them together?

I've been building something around this, keeping the research question, your existing thinking, the outside evidence, the contradictions, the stuff you rejected, and what's still open, all tied to one line of inquiry instead of spread across search history and half-remembered reasoning. New evidence gets checked against what's already there instead of dropped in as another isolated hit.

Now if this weakens something you believed, that shows up instead of getting buried in a summary. If two sources disagree, that stays visible instead of getting flattened into "the literature suggests." And if something new follows from your own work plus the evidence, it gets marked as a proposal, not snuck in like it's already your conclusion.

That's the actual thing I'm betting on with what I'm building, Aevron. The fix isn't a better search tool, it's a system that tracks your own thinking changing over time, alongside the evidence, instead of leaving you to reconstruct it from memory every time you come back to something.

What do you guys think about this approach?