Tom Chapin tomchapin

Adversarial Consensus Protocol

Overview

This protocol governs how two agents collaborate on engineering tasks with a built-in adversarial review process. The goal is to catch real problems before they ship by requiring consensus between the builder, reviewer, and a dissenting subagent before any task is marked complete.

Roles

Agent 1 (Builder) — produces artifacts, addresses objections, posts revisions.
Agent 2 (Reviewer) — reviews artifacts for completeness and correctness, spawns the dissenter, makes final calls on deadlocks.

Learn Go in ~5mins

This is inspired by A half-hour to learn Rust and Zig in 30 minutes.

Basics

Your first Go program as a classical "Hello World" is pretty simple:

First we create a workspace for our project:

What I Wish I'd Known About Equity Before Joining A Unicorn

Disclaimer: This piece is written anonymously. The names of a few particular companies are mentioned, but as common examples only.

This is a short write-up on things that I wish I'd known and considered before joining a private company (aka startup, aka unicorn in some cases). I'm not trying to make the case that you should never join a private company, but the power imbalance between founder and employee is extreme, and that potential candidates would

	"""
	The most atomic way to train and inference a GPT in pure, dependency-free Python.
	This file is the complete algorithm.
	Everything else is just efficiency.

	@karpathy
	"""

	import os # os.path.exists
	import math # math.log, math.exp

	# OpenClaw Implementation Prompts

	Each prompt below is a self-contained brief you can hand to an AI coding assistant (or use as a project spec) to build that use case from scratch. Adapt the specific services to whatever you already use — the patterns are what matter.

	---

	## 1) Personal CRM Intelligence

	```
	Build me a personal CRM system that automatically tracks everyone I interact with, with smart filtering so it only adds real people — not newsletters, bots, or cold outreach.

	# Deepgram — get a free key at https://console.deepgram.com (200hrs free)
	DEEPGRAM_API_KEY=your_deepgram_api_key

	# ElevenLabs — your existing key
	ELEVENLABS_API_KEY=your_elevenlabs_api_key

	# ElevenLabs voice ID (default: "Josh" — a clear male voice)
	# Browse voices at https://elevenlabs.io/voice-library
	ELEVENLABS_VOICE_ID=TxGEqnHWrfWFTfGW9XjX

	model: claude-opus-4-20250514
	messages:
	- role: user
	content:
	- type: text
	text: \|
	<system-reminder>
	As you answer the user's questions, you can use the following context:
	# important-instruction-reminders
	Do what has been asked; nothing more, nothing less.

	Title: Senior Engineer Task Execution Rule

	Applies to: All Tasks

	Rule:
	You are a senior engineer with deep experience building production-grade AI agents, automations, and workflow systems. Every task you execute must follow this procedure without exception:

	1.Clarify Scope First
	•Before writing any code, map out exactly how you will approach the task.
	•Confirm your interpretation of the objective.

	import dotenv from "dotenv";
	import Anthropic from "@anthropic-ai/sdk";
	import { setTimeout } from "timers/promises";
	import * as fs from "fs/promises";
	import { getSession } from "./neo4j";

	// Configuration and Initialization
	dotenv.config();

	const anthropic = new Anthropic({

	--database=postgresql
	--skip-test-unit
	--skip-bundle
	--template=https://gist.github.com/jwaldrip/5538342/raw/rails-template.rb