bmaupin

See also:

• Free database hosting
• https://free-for.dev/#/?id=iaas
• https://free-for.dev/#/?id=paas

Service	Type	RAM	Storage	Limitations
👉 Adaptable	PaaS	256 MB	Non-persistent? (1 GB database storage available)
AWS EC2	IaaS	1 GB		⚠️ Only free for 1 year

osy

QEMU on Apple Silicon with Vulkan support

The following is taken from https://gist.github.com/akihikodaki/87df4149e7ca87f18dc56807ec5a1bc5 with modifications to introduce Vulkan support. Since we need custom patches to QEMU, virglrenderer, MoltenVK, and libepoxy, the provided script will pull the right refs and build everything with the right params. Feel free to inspect the script to find the source for all the modifications. We are actively working to upstream everything so please do not build anything long-term with these patches.

Testing

Prerequisites

• Xcode (relatively recent version)
• Vulkan SDK for macOS (Make sure to select "System Global Installation" during Select Components.)

joshbuchea

Semantic Commit Messages

See how a minor change to your commit message style can make you a better programmer.

Format: <type>(<scope>): <subject>

<scope> is optional

Example

rydmike

# RydMike LINTER Preferences v2.6.0
#
# Get this file here: https://gist.github.com/rydmike/fdb53ddd933c37d20e6f3188a936cd4c
#
# We include and activate all_lint_rules, then below we disable the not used or desired ones.
# You can find a list of all lint rules to put in your all_lint_rules.yaml file here:
# https://dart.dev/tools/linter-rules/all
#
# This version is updated for Flutter 3.38 and Dart 3.10.
#

sshh12

Slack System Design: A Grounded Teardown

A reverse-engineered system design of Slack's web application, built from live network traffic analysis of the authenticated Enterprise Grid experience. 200+ API calls captured across boot, search, messaging, reactions, and navigation. Every backend service named.

Architecture Overview

┌─────────────────────────────────────────────────────────────────────────────┐
│  BROWSER (Gantry v2 SPA)                                                    │
│                                                                             │

karpathy

LLM Wiki

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.

The core idea

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.

Pulimet

Hi All!

I've recently launched a tool that wraps many of the commands here with a user interface. This desktop application is currently available for macOS. There's a roadmap outlining planned features for the near future.
Feel free to request any features you'd like to see, and I'll prioritize them accordingly.
One of the most important aspects of this application is that every command executed behind the scenes is displayed in a special log section. This allows you to see exactly what’s happening and learn from it.

Here's the link to the repository:  https://github.com/Pulimet/ADBugger

App Description:
ADBugger is a desktop tool designed for debugging and QA of Android devices and emulators. It simplifies testing, debugging, and performance analysis by offering device management, automated testing, log analysis, and remote control capabilities. This ensures smooth app performance across various setups.