A selection of problem solving resources that can be helpful for developers.
Discover gists
| Last update: 09/09/2024 21:56 | |
| !Completed: https://mega.nz/folder/sMcCXKpa#_R-M2Cqh9NYbFWWVWVAmxw | |
| !EPUB: https://mega.nz/folder/5AE2DTKS#-u5vZ1LauFo4vRDiAvFQIw | |
| !PDF: https://mega.nz/folder/ER1HXJZT#AnftN521aESOeisBWk_tMw | |
| !Yaoi/37C: https://mega.nz/folder/8A0RyZIS#x4N8tGqddmDHMMbCy1L0qA | |
| !Yaoi/A Kiss and a Pair of Handcuffs: https://mega.nz/folder/0V9zTQ6J#TnF--X0XuXuKr_lmIqTOxA | |
| !Yaoi/Ai no Kusabi: https://mega.nz/folder/5FUhmLyA#p_iCdky89s6sTHJNAHXMDQ | |
| !Yaoi/Ai Shika Iranee yo: https://mega.nz/folder/cR9FRADS#8Byg_qCw_mQ1VIGEFCc4KA | |
| !Yaoi/All My Loving: https://mega.nz/folder/Ud80ATRK#BFzuo5vhxZx1uYtZlhwbVw | |
| !Yaoi/Amazing Grace: https://mega.nz/folder/FcFW2bRC#vxpnv6Kq4MwPYOsUI1353g |
Shell Oil Company in its gas station offers loyalty program under name Shell ClubSmart. Members collect points which can be later used to get rewards. In 2020 they have offered a collection of die-cast car models under name Shell Motorsport. All models of the colletion are equipped with electrical motor. One of the models - Nissan Formula E Gen 2 Car - contains a battery that can be used to control a model remotely over Bluetooth. In some markets a battery with
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
主体:北京某某网络科技中心(个体工商户),2026-10 新注册 初衷:注册 Apple / Google Play 开发者组织账号。结果:Apple 组织账号走不通(个体户身份限制),DUNS 照拿,用于 Google Play
- 个体工商户可以申请邓白氏码,官方渠道免费。别找代办,代办收 1000~3000 就是赚信息差
- 个体工商户不能注册 Apple 开发者组织账号——邓白氏电话审核时官方告知。但可以要求照常分配 DUNS,供 Google Play 等其他场景使用
- Apple 的替代方案:个人开发者账号(无需 DUNS,688 元/年,App Store 卖家显示个人姓名,App 名称不受限)
Prune low-signal unit tests aggressively. Agents often write tests that restate the implementation, always pass, break on every refactor, and add little protection beyond existing tests.
Prefer a smaller suite that protects behavior over a large suite that protects coverage numbers.
Keep a test only if all of these are true:
- It protects a specific observable behavior, invariant, or contract.
- There is a concrete, credible regression its assertions would detect.
- Its expected results are justified independently of the implementation under test.
- It adds meaningful value beyond other retained tests: a distinct failure mode, an important edge case, or substantially faster, more reliable, or more precise feedback.
If Tony Stark had a Wordpress blog
Forked from Hugo Darby-Brown's Pen Iron Man Login Form.
A Pen by Alok Rajasukumaran on CodePen.
| import java.util.* | |
| import javax.crypto.Mac | |
| import javax.crypto.spec.SecretKeySpec | |
| import kotlin.experimental.and | |
| class DeprecatedOTPSecurity { | |
| private val SECRET_KEY_HEX = "120395F099840593405B03838449A72933484040A3034750C0403938290A293B" | |
| private val SECRET_KEY_BYTES = SECRET_KEY_HEX.chunked(2).map { it.toInt(16).toByte() }.toByteArray() | |
| private val TIME_STEP_X = 300L | |
| private val CODE_DIGITS = 6 |
