20 posts tagged with "How-to"

To study for an exam from lecture slides with AI, first rebuild what the lecturer said around each slide, then ask about the exact diagram or formula you did not follow, then switch from reading to being tested — answering questions before seeing answers. Reading AI explanations feels like learning; being quizzed is what tells you whether it was.

Slides are a strange thing to revise from. They are the lecturer's prompts, not the lecture. The half that explained them lived in someone's head and is gone.

To steelman an argument is to restate the opposing view in its strongest form — better than its own advocates might — before you respond to it. It is the opposite of a straw man. If your position still stands against the steelman, it is worth holding; if it does not, you found out cheaply.

Part of Thinking models in practice, a short series on classic methods and how to run them on your own material.

To read a Kindle book on your desktop with AI, you need a DRM-free .mobi or .azw3 file and a reader that converts it into a proper book with chapters. Open it in MindMax and it becomes an EPUB-style book the first time, with the original file left untouched; from there you can ask questions with quotes, or have an AI annotate it chapter by chapter.

The catch comes first, because it decides whether the rest applies to you: books bought from the Kindle store carry DRM, and they cannot be opened. That lock is not ours to remove, and this post does not explain how to remove it.

A pre-mortem is a planning exercise in which you assume the project has already failed — it is a year from now and it went badly — and list the reasons why. Because the failure is treated as a fact rather than a possibility, people name risks they would otherwise keep to themselves. It takes about twenty minutes and works best right before a decision is final.

This is the first post in a short series, Thinking models in practice: one classic method per post, what it is for, how to run it by hand, and how to run it on your own material.

To turn a ChatGPT or Claude answer into a proper Word document, copy it with the assistant's own copy button (which gives you Markdown), paste it into an editor that renders Markdown and understands the assistant's equation format, fix it there, then export to .docx. Pasting straight into Word skips the step that turns the formatting symbols into formatting.

Everyone who has tried it knows the result: hash signs in front of headings, asterisks around bold words, tables that are rows of vertical bars, and equations that arrive as \frac{a}{b}.

The simplest way to use AI with an Obsidian vault is to open the same folder in a second app that reads it in place. MindMax opens your vault directly — no import, no copy, no upload of the whole folder — and can answer questions across your notes and the PDFs and EPUBs sitting in your attachments folder, with quotes that open on the page. Obsidian keeps working on the same files.

Most AI options for Obsidian are plugins that send note text to a model. They help with notes. They do very little for the other half of a typical vault: the two hundred PDFs your notes are about.

To translate a whole EPUB with AI and keep it consistent, settle a glossary of recurring terms before translating anything, translate every chapter against that same glossary in one run, have the result checked for dropped passages and changed numbers, and read it side by side with the original. Pasting chapters into a chat window one at a time cannot do the first two.

Sentence quality stopped being the hard part of machine translation a while ago. Length is.

To OCR a scanned PDF into text you can rely on, recognise it once on purpose, check the result page by page rather than trusting one accuracy figure, re-run only the pages that came out badly, and keep the original scan untouched so every quote can be checked against the page image it came from.

A scanned PDF is a stack of photographs. Until the photographs become characters, nothing can search it, quote it or translate it — and an AI that answers questions about it anyway is answering from nothing.

To chat with multiple PDFs reliably, ask questions that name what you want compared, require every claim to say which document it came from and quote it, and look at which documents the answer actually read. The common failure is not a wrong sentence — it is a source that was never looked at, and an answer that sounds complete anyway.

One PDF is the easy case. The questions worth asking usually span ten: which of these papers use the method, where do these reports disagree, what does the contract say that the summary left out.

To read a research paper with AI without being misled, ask for the paper's central claim and what it rests on before you read anything, insist that every point comes with a verbatim quote and a page, check the two quotes that matter most, and only then read those sections properly yourself. The AI finds the way in; you still do the believing.

The usual approach — paste the PDF into a chat window and ask for a summary — is fast and feels productive. It also gives you a fluent paragraph you cannot evaluate without reading the paper, which is the thing you were trying to avoid.