if you've aped pons you already know the math. ~24,000 launches a day, and barely 2% ever migrate. everything else bleeds out on the curve while the dev and his bundle take your entry. and you get about two minutes to make the call. the average runner hits its pool in 126 seconds. by the time it's on your feed with a green candle, the migration already happened and you're chasing. i got tired of fumbling the ones that ran and bagholding the 98% that didn't, so i built Augur. the second a token deploys it reads the launch and prints one number, the odds it actually migrates, then ranks the board by that, not by newest. so you're eyeing the 5 that might run, not scrolling 24,000 that won't. it clocks the stuff you'd miss in the chaos: → the real dev behind the deployer wallet → how much of the supply they aped themselves → the bundle they waved past the opening tax → whether that same dev's been serial-launching tickers before every one's a line on the card, and every line links to the tx, so you're not trusting me, you're reading the chain. and the score isn't hopium. gradient-boosted on 23 features frozen at deploy, trained only on launches labeled after they already ran or died, so it can't cheat with hindsight. 2.1% of launches migrate. the ones Augur ranks top-decile migrate 3.74x as often. there's a second model for how far the peak runs, shown as a range, not a fake target. every call is logged before the outcome, and the whole track record is public, Ls included. MIT, open source, runs local. no wallet, no keys, nothing to connect. $AUGUR hasn't launched. no CA yet. the only real address will drop on the site and the github, nowhere else. anything before that is someone scamming with our name. i'd rather you tear it apart than shill it. open the board, find the first call you'd fade, and come tell me why.

LangChain's Lance Martin: "context engineering was the discipline everyone learned last year. the agent harness is the one replacing it" In 50 minutes he explains why Claude Code and Manus are in permanent re-architecture, why Sutton's bitter lesson kills every clever system you build, and what a harness adds without adding complexity this is the talk that named the layer most people are still building blind watch it, then read what a harness is actually made of in the article below

someone put the entire Claude Code stack into one 4-hour course, from 0% to 100%: 0% → 00:24:01 - build your first app from one prompt 25% → 00:55:13 - the .claude directory: what actually runs your agent 50% → 02:35:29 - creating skills 75% → 03:11:08 - turning skills into subagents 100% → 03:26:27 - agent teams: many agents, one job most people stop at the first prompt and never leave it this is the full path from one prompt to a harness that runs without you watch it today, then read the full harness architecture in the article below ↓

Someone finally explained the whole agent harness stack in 20 minutes, for free: - 03:37 - what a harness really means - 05:07 - storing and updating memory: databases, skills, summarizer agent - 10:52 - loop engineering and end-loop guardrails - 14:18 - eval and LLM Ops: why you need them - 18:57 - zoom out: the full system most people are still prompting one agent at a time this is the layer above: the harness that gives the agent memory, tools, evals and a loop that knows when to stop watch it today, then read the full architecture in the article below

ChatPRD founder, Claire Vo: "Everybody is saying it's not the model, it's the harness" In 24 minutes she builds one live on stream: a bug triage harness on the Claude Agent SDK, wired into Sentry, Linear, GitHub and Vercel worth more than any $500 agentic engineering course watch it, then read what a harness is actually made of in the article below

SpaceXAI engineer (ex-Cursor): "I don't prompt my 20 GrokBot agents. I built a harness once, now it automates 90% of my life and prompts for me" In a 1-hour session, a SpaceXAI engineer showed how to build a team of effective AI agents from scratch this is worth more than a $500 agentic engineering course watch this workshop today, then read how to build a fleet of GrokBot agents in the article below

Andrew Ng just released a free 2-hour course on complete Harness Engineering How to go from one prompt to a reliable system of agents that can run, test, and improve themselves: 09:14 - Build your first agent from scratch 33:11 - Master agent loops 1:02:46 - Turn loops into reliable workflows 1:30:15 - Build agents that improve their own work 1:49:05 - Run the complete system without supervision Model → Harness → Reliable Software Most agent tutorials stop once the model can call a tool This one shows you how to build the infrastructure around it within the first 20 minutes Most people are still prompting one agent at a time Andrew Ng is already teaching the layer above: Harnesses that give agents context, tools, tests, and feedback Watch this brilliant course and build the harness Then read the full architecture below ↓

Sam Altman: "if I were 22 right now, I'd feel like the luckiest kid in history" because payroll used to be the moat, now it is the line you deleted one person → one harness → the output of a team that no longer exists worth more than any agentic engineering course you almost bought watch it, then read the exact setup I ran below

SpaceXAI engineer, Lauren Tan: "99% of people using GrokBot just for 1% of its real power. They run 1 agent without a harness" In a 1-hour session, a SpaceXAI engineer showed how to build a team of effective AI agents from scratch this is worth more than a $500 agentic engineering course watch this workshop today, then read how to build a fleet of GrokBot agents in the article below

OpenAI CEO, Sam Altman: "You don't need to write prompts anymore. You need a harness." In 39 minutes he explains how to use LLMs better than almost anyone does Prompts → Agents → Harness a harness closes the job without you you are still closing it by hand Watch it, then read the full guide on harness engineering below

Google engineer: "We don't prompt agents anymore. We build harnesses that prompt them for us." In 32 minutes he shows what agents are actually costing the people who host your code. The missing piece most people skip: your $20 plan is subsidised and somebody is counting. Watch it, then read the full guide on harness engineering below

Anthropic engineer: "build a system that prompts itself → build a harness that prompts itself" In 60 minutes she breaks down how Anthropic's own teams run Claude Code at scale, and the token bloat killing your prompt before you type a word. This beats any $500 agentic engineering course you can find. Watch it, then read the full guide on harness engineering below.

Somebody finally explains the whole harness in 22 minutes "There's no point in using Claude if you haven't set up your harness" He takes the model out of the car and walks you through everything else that makes it drive. You have been upgrading the engine for a year. Nobody sold you the wheels. Watch it, then read the full guide on harness engineering below

NVIDIA CEO, Jensen Huang: "Nobody writes prompts anymore, the new job is building Loops and Harness." In 68 min at Stanford he shows what he does to a paper after he reads it. He doesn't read the next paper. He hands it to a harness and reads the answer. Watch it, then read the full guide on harness engineering below

Today, we are introducing Orbis 1.0, our first Live Model! Create living worlds and stream them in real time, with persistent memory, interactivity, and physics-grounded generation of unbounded length. Try it now at API available via @reactorworld Dynamic version: Stable version:

OpenAI co-founder, Ilya Sutskever: "It's back to the age of research again, just with big computers" In 96 min he explains why your model fixes one bug and brings back another. Scaling stopped paying. What you build around the model is the only lever left. Watch it, then read the full guide on harness engineering below

someone ran their whole content operation through 7 Grok Bot agents and Elon reposted the writeup one agent that researched, wrote and scheduled was mediocre at all three seven agents with one job each fixed it, same models they share one cloud computer, so the researcher saves a file and the writer just opens it nothing auto publishes, everything lands as a draft and he approves five on tuesday morning 40 minutes a week, and the full setup with every prompt is below

Claude Code creator: "Every six months, delete your claude md, delete your skills, delete your hooks" In 35 min he explains why they cut 80% of the prompt and what they put back. The instructions you wrote for last year's model are now making it dumber. Watch it, then read the full guide on harness engineering below

OpenAI engineer: "Code is free" In 46 min he shows what changes when writing the code stops being the expensive part. Every time you retype "continue" to your agent, that is the harness failing, not the model. Watch it, then read the full guide on harness engineering below

LaunchDarkly CPO: "Everybody's saying it's not the model, it's the harness" In 24 min she builds one live and shows the three parts every harness needs. You have been prompting your way around a problem that code solves once. Watch it, then read the full guide on harness engineering below