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⸻

👉 Alias master → main

git symbolic-ref refs/heads/main refs/heads/master
git symbolic-ref refs/remotes/origin/main refs/remotes/origin/master
git switch main

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alias webpconvert='convert_to_webp'

convert_to_webp() {
  original_path="$1"
  output_path="${original_path%.*}.webp"
  extension="${original_path##*.}"
  extension_lower=$(echo "$extension" | tr '[:upper:]' '[:lower:]')

  if [[ "$extension_lower" == "heic" || "$extension_lower" == "heif" ]]; then
    # Convert HEIC/HEIF to temporary JPEG first, then to WebP

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• “DoorDash problem” defined: AI agents sit between users and service providers, stripping away monetizable layers like ads, reviews, loyalty, and upsells, reducing platforms to commodity backends.

• Threat to App-era companies: Uber, Lyft, Airbnb, DoorDash, TaskRabbit, ZocDoc risk losing direct customer relationships that fund their business models.

• AI agents don’t care about monetization: They choose cheapest/fastest options, bypassing differentiation, brand, and promotional economics.

• Service-provider dilemma: Continue supporting agentic access and risk commoditization, or block agents and risk losing customers.

• Amazon vs Perplexity lawsuit: First major clash; Amazon argues Perplexity violated ToS, masked bots as humans, and circumvented blocks.

• High stakes for Amazon:

  • Massive ad business ($60B+) threatened by agentic shopping that hides ads.
  • Prime’s stickiness weakened if AI agents shop anywhere automatically.

• Amazon retail already commoditized; easy for agents

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1) Measure (so you know what to kill)

systemd-analyze
systemd-analyze blame
systemd-analyze critical-chain

These show kernel vs userspace time and the slowest units. ([wiki.archlinux.org][1])

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🧰 What You’ll Need

• Raspberry Pi 5 running Raspberry Pi OS
• Little Bird Toucan HAT (8 × APA102 LEDs)
• Python 3
• The spidev and time modules (standard or installable via apt/pip)

---

⚙️ Wiring / Setup

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{
  "tools": [
    {
      "name": "search",
      "description": "Searches for resources using the provided query string and returns matching results.",
      "input_schema": {
        "type": "object",
        "properties": {
          "query": { "type": "string", "description": "Search query." }
        },

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body  { font-family:Verdana, Geneva, sans-serif; font-size:10pt; color:#828282; }
td    { font-family:Verdana, Geneva, sans-serif; font-size:10pt; color:#828282; }

.admin td   { font-family:Verdana, Geneva, sans-serif; font-size:8.5pt; color:#000000; }
.subtext td { font-family:Verdana, Geneva, sans-serif; font-size:  7pt; color:#828282; }

input    { font-family:monospace; font-size:10pt; }
input[type='submit'] { font-family:Verdana, Geneva, sans-serif; }
textarea { font-family:monospace; font-size:10pt; resize:both; }

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import https from 'https';

export const handler = async (event) => {
  try {
    // Get the livestream status
    const status = await getLivestreamStatus();
    
    // Check if it contains "Currently off the air"
    const isOffAir = status.includes('Currently off the air');
    

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The linux/arm and linux/arm64 targets will cover most Raspberry Pi models, but you need to set GOARM properly when targeting 32-bit ARM devices.

Mapping Raspberry Pi Models to Go Architectures

Raspberry Pi Model	Go Architecture
Raspberry Pi 1 (A, B, A+, B+), Zero, Zero W	GOARCH=arm GOARM=6
Raspberry Pi 2 (v1.1)	GOARCH=arm GOARM=7
Raspberry Pi 2 (v1.2), 3, 3+, CM3	GOARCH=arm GOARM=7
Raspberry Pi 4, 400, CM4 (32-bit OS)	GOARCH=arm GOARM=7
Raspberry Pi 4, 400, CM4 (64-bit OS)	GOARCH=arm64

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package main

import (
	"encoding/json"
	"fmt"
	"image"
	"image/color"
	"image/draw"
	_ "image/jpeg"             // Register JPEG decoder
	_ "image/png"              // Register PNG decoder