Claude

When I shared my critical appraisal tool a while ago (to have Claude help with critical appraisal and summarizing content), a friend gave me a very honest reply: the tool is nice, but having to dig up the PDF yourself every single time is actually the most annoying part. It really is. To let AI read papers for you, you first need the full text. And when it comes to getting the full text, what usually gets you stuck isn’t the AI—it’s permissions, publishers, and the library. ...

Introduction: Why official scores aren’t enough My workflow for turning recorded lectures into notes goes in a straight line: transcript → matching slides → final summary. The foundation of this line is automatic speech recognition (ASR). However much it mishears, every subsequent layer of notes will be just as wrong. Originally, I was using OpenAI’s Whisper large-v3. The starting point for all this was actually me scrolling on my phone and seeing MediaTek Research announce their Taiwanese model, Breeze-ASR-26. A Taiwanese model is intriguing enough on its own, but clicking through, I learned they had already released Breeze-ASR-25 last year. Fine-tuned from Whisper-large-v2, it was optimized specifically for Taiwanese Mandarin and Mandarin-English code-switching, and open-sourced under Apache 2.0. Medical lectures happen to be ground zero for Mandarin-English code-switching. I had somehow missed this for a whole year. ...

The paper learning station I shared earlier had “Quality” and “Content” buttons, but I didn’t release the backend implementation back then. It was basically a platform with a frontend web page, but you still had to organize the backend yourself. But for my own setup, of course the backend still had to be wired to AI to reduce the cognitive load. So here I’m sharing those two backend skills to help speed up everyone’s learning! ...

📖 Saving Tokens series (four parts): Part 1: Why your AI gets dumber the more you chat · Part 2: Don’t boot up a supercomputer if an abacus will do · Part 3: Setting up a clean desk for your AI · Part 4 (this post, the finale) We’ve arrived at the final post of the series. Over the first three parts, we went from “why your AI gets dumber the more you chat” all the way to “when not to use AI” and “how to clean up its desk.” This post is about the moment you actually spend the money: how to make every penny count. ...

📖 Token Saving Series (4 parts): Part 1: Why your AI gets dumber the longer you chat · Part 2 (This post) · Part 3: Clearing a clean desk for your AI · Part 4: I built a budget dashboard for my AI In the previous post, we talked about how longer AI chats get more expensive and dumber, along with three ways to save right now. This post takes it a step further to discuss a more fundamental divide: ...

📖 The Token Saving Series (4 parts): Part 1: Why your AI gets dumber the more you chat · Part 2: If an abacus works, don’t boot up a supercomputer · Part 3 (This post) · Part 4: I built a budget dashboard for my AI The first two posts were still at the “everyone can use this” level. Starting with this one, I’ll show you the setup on my computer that I’ve endlessly tinkered with. ...

📖 Token Saving Series (4 parts in total): Part 1 (this post) · Part 2: If an Abacus Works, Don’t Boot Up a Supercomputer · Part 3: Organizing a Clean Desk for AI · Part 4: I Installed a Budget Dashboard for AI You’ve definitely had this experience: you chat with ChatGPT or Claude for an afternoon, and the longer it goes, the more sluggish it gets. It replies slower, suddenly “forgets” what you said earlier, or even starts talking in circles. ...

Ever since becoming a resident, looking for continuing education courses has hit the same pain point every time: ultrasound, manual therapy, foot and ankle, neuro, pediatric rehab… The courses are scattered across a dozen society and institution websites. I’d have to refresh the sites every few days, and I was never sure if I’d actually seen a particular post before. Later on, I set up web scrapers for these course pages in my Home Assistant at home to automatically notify me of new courses, and things finally got a lot easier. But realizing I’d be completing residency soon, this little tool sitting at home wouldn’t be able to keep reminding the junior residents. Figuring I had Claude anyway, I just asked it to scrape all the courses and announcements from these 17 rehab-related societies and institutions, aggregate them in one place, update automatically every 3 hours, and put it on the web for everyone to use. ...

Background: What I was already using When studying for the board examination, I set up a RAG (Retrieval Augmented Generation) pipeline for myself. Using semantic search to look at similarity, I turned hundreds of physical medicine and rehabilitation (PM&R) textbooks and my own notes into something I could search and query. I use it for reading in Obsidian, while also letting Claude find what I need via MCP. Its weakest point right now is connecting knowledge across different documents. So a few days ago, when I saw someone share a newly published paper, SAG (SQL-Retrieval Augmented Generation), claiming that adding SQL and graph concepts on top of semantic search makes cross-document search easier—with effects similar to GraphRAG but easier to build and maintain—my eyes lit up. ...