code ai

The Second Brain

You have a folder of notes you paste into a chat and re-read every time, and it is slow, it dilutes the answer, and it cannot settle an argument it has with itself. Turn that pile into a corpus: plain text files, one question each, an index a machine can read, and a review that keeps it true after three months. No database, no embeddings, no vector store.

  • trending_upIntermediate
  • schedule6h 19m
  • menu_book12 堂課程
  • publicEnglish
  • workspace_premiumBasic

課程簡介

This is the segment that comes after the one page on your desk got too big. You already keep notes. A folder of them, grown by accretion: meeting minutes typed live, a handover document somebody started and never finished, a pasted email thread, a file called misc. When you have a question you paste the lot into a chat and re-read it, every time, because a chat has no memory. That works until the pile is large enough to be slow, expensive, and — the part nobody warns you about — undecided. It ties on the questions that matter, it answers the wrong search because you wrote in jargon and search in plain English, and the one sentence that settles an argument is outvoted by two thousand words that do not. You will measure your own pile first, using the cost arithmetic from AI Without the Hype rather than re-deriving it, and the number will be larger than you think. Then you will turn it into a corpus: one document per question, a title that states the answer, what to summarise and what to keep word for word and what must never go in at all. You will give every document a name that survives a search and a line of the words you would actually type. You will generate an index — one line per document, small enough to paste whole — with five lines of awk you can read, and you will answer a question the pile could not, at a fraction of the tokens. Then the lesson that decides whether any of it was worth doing: what you do the first time something changes and two of your own documents disagree. A supersedes line, four checks a machine can run, and a twenty-minute quarterly review that a person does. You finish with your own folder measurably better — actually navigable, actually searched, answering a question it could not answer at the start. **There is one hard prohibition and it is the point of the segment.** No embeddings, no vector store, no database of any kind. The moment it reaches for one it becomes a different course. The whole idea is that the structure is plain files and plain text a human can also read, because the thing that kills every personal knowledge system is not retrieval quality, it is that nobody maintains it, and a folder of text files survives a laptop change, a job change and eleven years. **Redaction is not optional here.** A personal corpus is the easiest place to keep material that should never have been kept, so every lesson that captures real work states what does not go in, and why, and the gate is at the moment you write rather than the moment you paste. AI Without the Hype is assumed, and AI at Work Without Leaking the Company owns the data classes this segment applies rather than rebuilds. You need a folder of your own notes, a terminal or PowerShell, and a chat interface. Nothing is installed and nothing runs in the background.

課程大綱 · 4 個單元

lock隨存取權限解鎖
  1. 01 The Pile, Measured
    3 堂課程·1h 27m

    Every number in this module is measured on the learner's own folder. It is always larger than they expect, and the argument only lands because it is their number and not a slide.

  2. 02 One Document, One Question
    3 堂課程·1h 46m

    A pile records events; a corpus records conclusions. The module is the machinery that turns one into the other, and the hardest part throughout is deciding what to leave behind.

  3. 03 Finding It, and Using It
    3 堂課程·1h 34m

    The index is the one file small enough to paste, and it carries the words that are not in the documents. That is what makes the corpus cheaper than the pile it replaced, and it is the payoff for two…

  4. 04 Keeping It Alive
    3 堂課程·1h 32m

    The pile-to-corpus work is a weekend. Whether it is still true in three months is decided here, by what the reader does the first time two documents disagree. The module ends with the corpus…

常見問題

我將在 The Second Brain 中學到什麼?
You have a folder of notes you paste into a chat and re-read every time, and it is slow, it dilutes the answer, and it cannot settle an argument it has with itself. Turn that pile into a corpus: plain text files, one question each, an index a machine can read, and a review that keeps it true after t
我需要事先具備經驗嗎?
建議在開始 The Second Brain 前具備一些先備知識。
The Second Brain 需要多長時間?
The Second Brain 包含 4 個單元和 12 堂課程。你可以按自己的進度學習。
我如何取得存取權限?
The Second Brain 包含在任何付費訂閱方案中。

程式設計 中的更多內容

Binary, Hex and Data Units
Beginner Binary, Hex and Data Units The topic that costs more marks than any other on the paper, taught by hand. Bits and bytes, binary and hex in all six directions, the 1000-versus-1024 trap, file sizes, transmission times, overflow, two's complement and character sets. Every module ends in a timed drill marked the way an examiner marks it.
First Program — Scratch for ages 5–9
Beginner First Program — Scratch for ages 5–9 Nine Scratch blocks, three sessions of about twenty-five minutes, and one small program a child of five to nine builds themselves. Written for the parent sitting beside them: what to click, what they will get stuck on, what to say when it goes wrong, and when to keep your hands off the mouse.
AI Without the Hype
Beginner AI Without the Hype What the model is actually doing when it answers you, why that produces something that looks like thinking, why it invents citations, and the cost mechanic almost nobody explains: a chat resends the entire conversation on every single turn. You will do the arithmetic yourself.
Python From a White Sheet
Beginner Python From a White Sheet The exact sequence nine students have already walked, from a blank file to a program that asks questions, checks the answers and refuses bad input. No prior programming. No maths. You will break it repeatedly, on purpose.
IGCSE and GCSE Computer Science — Theory That Actually Gets Marked
Intermediate IGCSE and GCSE Computer Science — Theory That Actually Gets Marked The theory half of the paper, taught so it survives the exam room. The memory hierarchy and what actually happens at boot. Compilers, interpreters and assemblers, including the answer that sounds right and scores nothing. Databases from a spreadsheet up to keys and normalisation. DNS and the full path between pressing Enter and seeing the page. Systems software, and the ethical and legal section that is the easiest ten marks on the paper.
Programming for the Exam — Python Answers That Score
Intermediate Programming for the Exam — Python Answers That Score The programming half of the paper, taught at exam pitch. Pseudocode translated both ways, because the mark scheme is written in a notation nobody practises. Trace tables done column by column, including the ones with a loop and a condition inside it. Linear and binary search, bubble and insertion sort, what each costs and the comparison questions boards love. Validation against verification, and the boundary test data everybody forgets. Procedures against functions, and a systematic method for finding your own error with four minutes left.