gary23w

Startup resource list

A revised version of IBEXSOFT awesome start up tools list.

Adding and updating as I go along.

Tech

Git Repos

mzelzoghbi

description	Capture and analyze the current Android device/emulator screen via ADB

Screen Debug: ADB Screen Capture & Analysis

You are tasked with capturing and analyzing what is currently displayed on a connected Android device or emulator. This helps debug UI issues, verify screen state, and inspect the view hierarchy.

User Context

schnell18

sudo rm -fr /Library/Java/JavaVirtualMachines/jdk-9.jdk/
sudo rm -fr /Library/Internet\ Plug-Ins/JavaAppletPlugin.plugin
sudo rm -fr /Library/PreferencePanes/JavaControlPanel.prefPane

emaillenin

public void downloadUpdate() {
        DownloadManager dm = (DownloadManager) getSystemService(DOWNLOAD_SERVICE);
        String destination = Environment.getExternalStoragePublicDirectory(Environment.DIRECTORY_DOWNLOADS) + "/";
        String fileName = "your_app.apk";
        destination += fileName;
        final Uri uri = Uri.parse("file://" + destination);

        File file = new File(destination);
        if (file.exists())
            file.delete();

staltz

The introduction to Reactive Programming you've been missing

(by @andrestaltz)

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This tutorial as a series of videos

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

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jevakallio

TL;DR;

com.package.name is your app identifier, and the file path is relative to the app user's home directory, e.g. '/data/user/0/com.package.name.

adb shell run-as com.package.name cp relative/path/file.ext /sdcard
adb pull /sdcard/file.ext

See long explanation below.

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.