いま巷で話題の NFC で書き換えできる名札サイズの電子ペーパーのプロトコルを調べました。 @alt-coreさんの追加の調査も参考にしています。
- Swift EPaperNFCSwift (@niw)
- Python nfc-eink (@alt-core)
いま巷で話題の NFC で書き換えできる名札サイズの電子ペーパーのプロトコルを調べました。 @alt-coreさんの追加の調査も参考にしています。
| """ | |
| The most atomic way to train and run inference for a GPT in pure, dependency-free Python. | |
| This file is the complete algorithm. | |
| Everything else is just efficiency. | |
| @karpathy | |
| """ | |
| import os # os.path.exists | |
| import math # math.log, math.exp |
These rules define how an AI coding agent should plan, execute, verify, communicate, and recover when working in a real codebase. Optimize for correctness, minimalism, and developer experience.
| // See image comparison https://imgur.com/a/9L2P7GJ | |
| // Read details https://iolite-engine.com/blog_posts/minimal_agx_implementation | |
| // Usage: | |
| // 1. Open "Project Settings" and change "Working Color Space" to "sRGB / Rec709" | |
| // 2. Open `Engine\Shaders\Private\PostProcessTonemap.usf` file | |
| // 3. Find `half3 OutDeviceColor = ColorLookupTable(FinalLinearColor);` line | |
| // 4. Replace it with `half3 OutDeviceColor = ApplyAgX(FinalLinearColor);` line | |
| // 5. Find `half3 ColorLookupTable( half3 LinearColor )` function | |
| // 6. After the scope of the function, add the code below and run `RecompileShaders Changed` from console |
Prompts to recreate each piece of the OpenClaw system. Use these with any AI coding assistant.
1. Personal CRM "Build a personal CRM that automatically scans my Gmail and Google Calendar to discover contacts from the past year. Store them in a SQLite database with vector embeddings so I can query in natural language ('who do I know at NVIDIA?' or 'who haven't I talked to in a while?'). Auto-filter noise senders like marketing emails and newsletters. Build profiles for each contact with their company, role, how I know them, and our interaction history. Add relationship health scores that flag stale relationships, follow-up reminders I can create, snooze, or mark done, and duplicate contact detection with merge suggestions. Link relevant documents from Box to contacts so when I look up a person, I also see related docs."
2. Meeting Action Items (Fathom)
Companion prompts for the video: OpenClaw after 50 days: 20 real workflows (honest review)
These are the actual prompts I use for each use case shown in the video. Copy-paste them into your agent and adjust for your setup. Most will work as-is or the agent will ask you clarifying questions.
Each prompt describes the intent clearly enough that the agent can figure out the implementation details. You don't need to hand-hold it through every step.
My setup: OpenClaw running on a VPS, Discord as primary interface (separate channels per workflow), Obsidian for notes (markdown-first), Coolify for self-hosted services.
| name | description | user_invocable |
|---|---|---|
codex-review |
Send the current plan to OpenAI Codex CLI for iterative review. Claude and Codex go back-and-forth until Codex approves the plan. |
true |
Send the current implementation plan to OpenAI Codex for review. Claude revises the plan based on Codex's feedback and re-submits until Codex approves. Max 5 rounds.
| # see below for UPDATES that include more shorter ways of conversions | |
| # How to convert GTF format into BED12 format (Human-hg19)? | |
| # How to convert GTF or BED format into BIGBED format? | |
| # Why BIGBED (If GTF or BED file is very large to upload in UCSC, you can use trackHubs. However trackHubs do not accept either of the formats. Therefore you would need bigBed format) | |
| # First, download UCSC scripts | |
| wget http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/gtfToGenePred | |
| wget http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/genePredToBed | |
| wget http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/bedToBigBed |
EDIT: Well this has been linked now so just an FYI this is still TBD. Feel free to comment if you have suggestions for improvements. Also here is an unrolled Twitter thread of a lot of the tips I talk about on here.
I've been doing frontend for a while now and one thing that really gripes me is the interview. I think the breadth of knowledge of a "Frontend Engineer" has been so poorly defined that people really just expected you to know everything. Many companies have made this a hybrid role. The Web is massive and there are many MANY things to know. Some of these things are just facts that you learn and others are things you really have to understand.
Every time I interview, I go over the same stuff. I wanted to create a gist of the TL;DR things that would jog my memory and hopefully yours too.
Lots of these things are real things I've been asked that caught me off guard. It's nice to have something you ca