Loopz

OpenAI Core Products Lead, Tibo Sottiaux: "Almost a billion people use ChatGPT every week. We're announcing ultra mode, which unleashes a whole team of agents to do work for you." 34 minutes on ChatGPT Work: connectors, Codex, and GPT-5.6 Sol doing the job while you watch. Most people will still be doing this work by hand next month. Watch it, then read the 12 steps to build a Sol agent that runs for hours without you, below.

@0xClodex I appreciate it!

@0xLoopz Thanks bro

@de1lymoon I appreciate that, my friend!

@0xLoopz GPT SOL, now is crazy. Booked this alpha

@0xCodez Sure thing, buddy

@0xLoopz Thanks, Loopz! By the way, are you building long‑running agents yourself?

NVIDIA engineer: "my job is two things. I build agents, and I babysit agents. 3 moments changed everything for me: • ChatGPT - when my parents finally got it. • Reasoning models - when model first high-fived itself. • January '26 - agents started running for hours on their own" in this 1‑hour talk, Nvidia engineers reveal how to build agents that can run for hours from scratch. Watch the talk, then save the playbook below.

@AnatoliKopadze i want the same cap he's got

Meta CTO Andrew Bosworth: "If you skip learning to integrate AI, you'll fall behind people who didn't, we both know that." The people who adapt now won't be waiting for the ones who don't. 45 minutes of straight talk from the man running AI at Meta. Watch it, then read the guide below on the Claude features 99% of people never find.

@kingwilliam_ really good materials, thanks buddy!

Anthropic just dropped 5 free workshops on building self-improving Claude agents from scratch: • 00:00 – Ship your first Claude agent • 36:44 – Make agents self-improve (tools + skills) • 1:21:25 – Give your agent real memory • 1:49:47 – Set up a proactive agent • 2:11:31 – Make it fully autonomous These 3 hours of workshops will replace a $3,000 agent bootcamp. Watch them today, then read the full system for running Fable 5 hands-off in the article below.

@noisyb0y1 it was all obvious, the future's easy to read

John McCarthy created "Artificial Intelligence" in 1956 and predicted everything that is happening today: 00:12 - who invented AI and changed the world 05:48 - 4 year old child is smarter than AI 22:24 - AI will destroy humanity in 7 months He built the Stanford AI lab that trained the engineers behind OpenAI Google and Anthropic. This talk gives you for free what Stanford charges $90,000 a year to teach its students. Watch it today, then read the full breakdown in the article below.

@RohOnChain Great post, Roan!

Met a guy making $1.2 million a year as a prompt engineer. I asked him how he learned prompting so well. He sent me the exact video that that got him in. Anthropic's 2 hour prompting course. You won't find anything better about prompting Claude than this video. I watched it last night. Halfway through, I realized I have been prompting Claude completely wrong for years. Bookmark this and read the article below. • 00:00 - the prompting playbook • 33:30 - prompting class 1 • 1:01:16 - prompting class 2 • 1:26:10 - prompting class 3

Cursor's CEO just answered the question every engineer is scared to ask. 3 hours on what happens to your job when agents do the work, mapped: 00:05 – Michael Truell on where Cursor and agents go next 47:42 – agents and infrastructure at scale (Sam Lambert) 1:13:22 – the new PM: your role in an agent-first world (Claire Vo) 1:39:13 – what your job actually becomes now (Farhan Thawar) 2:20:30 – how agents actually make decisions (Alane Suhr) 2:35:03 – the memory problem that breaks most agents (Baseten) Worth more than any $500 enterprise-AI course. Watch it today, then read how these agent loops actually work, below.

@phosphenq Nailed it, Phos!

NVIDIA just dropped a 2.5-hour course on how to build coding agents, featuring the CTO of Cursor: 00:07 – self-driving codebases with async agents 37:50 – agentic AI, from the ground up 1:16:35 – context engineering for high-signal AI code reviews 1:53:26 – teach AI to code in any language Worth more than any $500 enterprise-AI course. Bookmark this & steal my harness, below.

@CreaoAI Agree, that's a very important part

@0xLoopz The tool vs skill vs subagent breakdown at 36:58 is the part worth watching first. That distinction is where most people building their first agent actually get stuck.

Anthropic just dropped a 3-hour course on how to build AI agents with Claude, from scratch: 00:08 – ship your first managed agent 36:58 – tool, skill, or subagent: when to use each 1:21:44 – the expanding agent toolkit 1:42:41 – build a proactive agent workflow 2:04:26 – give your agents real memory 2:32:49 – stop babysitting your agents and let them run This 3-hour watch will replace 10 paid AI agent courses on the internet. Watch it today, then start with part 1, mastering Claude Code, in the post below.

@wladwtf It's very simple, u can optimize all your tasks

@0xLoopz Now you can create agents from scratch using Cludo

The most powerful man in AI just called your AI agent a vacuum cleaner. Jensen Huang, on how much to anthropomorphize agents: "It's electrons, not atoms. No consciousness. It's not awake. It's a tool, like my vacuum cleaner roaming around the house." 20:40 - 21:00 But that "tool" is already rewriting NVIDIA from the inside: "Every one of my engineers prefers building agents to writing Python. Coding is like typing." 22:26 - 22:33 The job stopped being writing code. It's building the agents, and the loops that run them. Watch it, then read the full tutorial on building those loops, below.

@0xCodez Thanks! Of course I like them, I love them!

@0xLoopz amazing watch, bro. love Boris sessions with founders?

DoorDash gave Claude Code to every single employee. Then one of them did a job that used to take four engineers an entire quarter. "One person did it in 3 weeks." 11:53 - 12:00 His one rule for getting there wasn't working harder. It was refusing to touch the keyboard: "I set a goal for myself to not write code manually. I try to have the agent write everything." 2:18 - 2:30 25 minutes with Anthropic's Boris Cherny on how they did it. Watch it, then read the clearest breakdown of the loops that made it possible, below.