mkwatson

Fast path: M4 Mac mini → OpenClaw → iMessage “hello world”

Goal:

• Dedicated bot identity
• Remote control over Tailnet
• iMessage working
• Minimal permissions, easy to expand later

---

mkwatson

{
  "data": {
    "product": {
      "id": "gid://shopify/Product/8471924539415",
      "title": "Black Lazio Tuxedo",
      "handle": "suitsupply-lazio-tuxedo",
      "description": "This tuxedo features a slim, well-defined fit with a handsome black dinner jacket. The jacket includes a slightly curved silk-covered peak lapel, a single silk-covered button,
silk-lined jetted pockets and lightly padded shoulders. The pants are slim through the hip and thigh with a straight leg, featuring a mid-rise cut, flat front, side adjusters, and silk side-stripe down the
 leg outseam. Made from Pure S110's Wool by Vitale Barberis Canonico, Italy. Features: Pure S110's Wool (Vitale Barberis Canonico, Italy), Silk-covered peak lapel, Silk-lined pockets, Lightly padded
shoulders, Slim fit through hip and thigh, Silk side-stripe on pants",

mkwatson

What does "No low surrogate in string" mean when talking about invalid JSON?

This error occurs when JSON contains a broken Unicode character encoding. Here's everything you need to understand it:

Unicode Background

Unicode assigns every character a unique number (code point). Simple characters like "A" get small numbers (U+0041), while emojis like 😀 get large numbers (U+1F600).

Unicode organizes these numbers into 17 "planes" - think of them as 17 floors in a building, each holding 65,536 characters:

• Plane 0 (U+0000 to U+FFFF): Common characters - Latin, Asian scripts, basic symbols

mkwatson

Employee Engagement Pulse, minimal build plan

Takeaway: Ship a single SSR page that fetches last‑7‑days Slack messages for selected channels on demand, scores text and emoji (including reactions), aggregates to daily mood with simple burnout rules, and prints three actionable bullets, nothing more.

---

Project definition

 Project 3: Employee Engagement Pulse

mkwatson

Create project

➜ npx create-next-app@latest buildathon-example
✔ Would you like to use TypeScript? … No / Yes
✔ Would you like to use ESLint? … No / Yes
✔ Would you like to use Tailwind CSS? … No / Yes
✔ Would you like your code inside a `src/` directory? … No / Yes
✔ Would you like to use App Router? (recommended) … No / Yes
✔ Would you like to use Turbopack for `next dev`? … No / Yes
✔ Would you like to customize the import alias (`@/*` by default)? … No / Yes

mkwatson

Buildathon Graph & AI Tech Textbook

Introduction

Welcome to the Graph & AI Buildathon reference textbook. This guide covers 15 key technologies spanning graph databases, LLM tooling, and rapid demo stacks. Each section provides a cheat sheet of commands and syntax, example use cases with code, setup instructions, and common pitfalls with debugging tips. We also include a comparison matrix of agent frameworks, guidance on tool selection trade-offs, and tips for deploying polished demos quickly. Use the interactive table of contents below to navigate:

• LLM APIs (OpenAI, Anthropic, Vectara) – How to call large language model APIs in Python/TypeScript, key parameters, and differences.
• Neo4j + Cypher – Graph database queries with Cypher, CRUD operations on nodes/relationships, and data modeling patterns.
• LangGraph (LangChain) – Building complex multi-agent workflows with LangChain’s LangGraph library.
• CrewAI – Creating collaborative AI agent “crews

mkwatson

{
  "HighRoller": [
    {
      "startTimeStamp": 1751365068,
      "Id": "ALL_HR@1751365068",
      "ProgressiveId": "hr_mystery_MustHitByAmount1",
      "GameIds": [],
      "MinimumHitByAmount": 700000000,
      "MustHitByAmount": 1000000000,
      "MinimumHitByTime": 0,

mkwatson

The problem:

Every time someone builds an AI-powered app or website, they hit the same crossroads. Either they bolt an LLM key into front-end code, risking leaks, surprise bills, and instant compliance red flags, or they stop progress to write a custom mini-backend that hides keys, authenticates users, meters usage, and logs every prompt. Every new project does this from scratch.

Let's build that layer once, open-source it so the whole ecosystem can stop duplicating effort. Install a tiny SDK, drop in the team's own OpenAI, Anthropic, or Cohere key, and call the model: the gateway stores secrets, authenticates each request, enforces per-user limits, records full audit logs, and lets developers switch providers without touching front-end code.

Stripe removed the need to build payment rails and Auth0 removed the need to build login flows. This removes the need to build AI plumbing.

mkwatson

Flight Research Request: SFO to SEA Family Travel

I need comprehensive flight options for a family of 3 (2 adults + 1 infant) traveling from San Francisco (SFO) to Seattle (SEA).

Travel Details:

• Departure: Friday, July 18, 2025
• Return: Monday, July 21, 2025
• Departure time constraint: Only flights leaving between 6:00 AM and 7:00 PM (both outbound and return)
• Airlines: Research ALL airlines, but MUST include comprehensive coverage of Delta and Alaska Airlines options
• Passengers: 2 adults + 1 infant (lap infant, under 2 years old)

mkwatson

Based on the search results, here's a detailed analysis of Tank Dell's receiving yards performance:

Recent Performance

Tank Dell has shown promising performance in his recent games:

• In his last 5 games, Dell has accumulated 192 receiving yards on 20 receptions[6].
• His average yards per reception over this period is 9.6 yards[6].
• Dell's best performance in these 5 games was against Minnesota, where he caught 5 passes for 62 yards[6].