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This is most funny video of the day 🤣🤣

Omg.. this can't be true... I kept building AI agents on my eventually list because everything I read made it sound like a six month project requiring a technical background I did not have. One Reddit thread changed that by saying the one thing nobody had said clearly: pick the smallest possible problem and finish it completely before you try to build anything impressive. MY ARTICLE IS THE CLAUDE CODE VERSION OF THAT LESSON. Working agent - Under one hour - Zero coding. Full guide below.

My friend applied to 200 tech jobs in two years. No PhD. No Stanford. Last month Anthropic offered him $750,000. I asked him how he broke in from zero. He sent me a course that was never supposed to get out. A 3-hour video to build a full LLM from scratch. A developer teaches you exactly how LLMs like ChatGPT and Claude are actually built. I watched it last night. Halfway through, I realized it's embarrassingly simple to break into an AI lab. Bookmark this and read the article below. • 00:00 - intro to LLMs • 05:43 - LLM transformer architecture • 40:24 - training the LLM • 1:30:27 - modernizing the LLM • 2:33:53 - scaling the LLM

@BoPolnyResults @BoPolny Bo needs to stop being MAGA and just focus fully on Jesus, and the holy spirit will tell him which maths is correct. One cannot worship God and Trump

Bo Polny set the terms (apology on July 4th) and lost, but now he's being a sore loser by refusing to admit it. @BoPolny just kicked the can down the road again, pushing it to "Summer" (ends September). After that fails, he'll switch calendars again to October, November, etc.

this is f**king dangerous someone just figured out how to get fable 5 reasoning in opus 4.8 with one prompt you have less than 24 hours to set this up as this takes away 20% of your usage limit here is how: 1) Paste the prompt and ask it to "make an operating manual" 2) Create a New Claude Project and "Add this .md in Project instructions 3) Use Opus 4.8 High/Max and now you have Fable 5 reasoning at 1/5th the price save and bookmark it no matter what

this is f*cking gold Andrej Karpathy came over to Anthropic just five weeks back. Someone on his team pulled up the actual Claude.md they run day to day and showed it to me. I plugged it straight into my workflow. Claude’s next reply wasn’t just improved. It felt like a different model. The canned, one-size-fits-all stuff vanished, and it started reasoning in my voice. Save this before it disappears down your timeline. Read it first then hit the article below.

I don't prompt Claude Code anymore. I have loops running that prompt Fable, and my job is just to write loops. This is the Boris Cherny method, and I have to say, it's extremely powerful. Everything you need to get started with loop engineering (as a complete beginner):

The Company Brain has 6 layers: LAYER 1: capture The brain only knows what made it into the system. Calls, CRM notes, Slack threads, SOPs, sales calls, client feedback. If the raw material never lands, the agent has nothing to work with. Scattered inputs, scattered answers. ---- LAYER 2: retrieval Capture gives you the pile. This layer pulls the right piece off it. A bigger knowledge base doesn't make the agent smarter on its own. It has to grab the right context for the task, at the right moment, in the right format. Bad retrieval makes good memory useless. ---- LAYER 3: source truth Retrieval finds the context. This layer decides which version of it to trust. A live CRM update beats a 9-month-old Google Doc. A client call beats a stale SOP. A manager-approved correction beats a random note. Without source truth, the AI confidently repeats old information. ---- LAYER 4: permissions A company brain can't just be a shared folder with better search. Sales shouldn't see everything finance sees. A junior employee shouldn't get the same context as leadership. Access follows role, workflow, and risk. Skip this and your AI system becomes a security problem. ---- LAYER 5: feedback This is the layer that quietly rots. A human corrects the AI once. The correction disappears. The same mistake is back next week. In a working company brain, corrections turn into rules, examples, updates, or eval cases. The system wakes up smarter tomorrow. ---- LAYER 6: evaluation If nobody scores the output, nobody knows if the brain is improving. Every serious AI workflow needs the loop: answer, human review, correction, rule, eval, better answer. No eval layer and the system feels impressive but stays unreliable. ---- The simple test. Ask your AI agent 3 questions: 1. Where did this answer come from? 2. Which source won when sources conflicted? 3. What changed after the last human correction? If it can't answer those, you don't have a company brain yet.

instead of watching 2 hours of Netflix tonight, watch this 40-minute masterclass from the founder of a $20B China AI company it's the clearest explanation I've seen of how AI Agent and AI systems actually work at scale useful whether you've never built an agent in your life or have been using Claude every day for the past year I took the key ideas and turned them into 30 core agentic engineering concepts every developer should actually know find it below ↓

Anthropic CEO Dario Amodei: "Recursive self-improvement isn't coming - it's already here." the guy building Claude just told Bloomberg: - 90% of Anthropic's codebase is already AI-written - 20-30% of their own research is AI-accelerated - Entry-level white-collar jobs have 1-5 years left - AI assists - AI replaces is one smooth exponential curve watch it, then read why your CLAUDE.md won't survive what's coming

Google CEO Sundar Pichai: "75% of new code at Google is already written by AI" "But the real metric is how many agents one engineer can run at once" In 14 minutes, he changes the whole productivity story The next frontier is not autocomplete It is agent orchestration Inside Google, they hand a C++ to rust migration to a small team and a swarm of agents The old binary becomes the spec. Agents handle the rewrite. Every engineer gets sub-agents running 24/7 in Google cloud Hands off the keyboard Eyes on the orchestration Better than most $500 AI coding courses Bookmark and watch the full interview

Running 5+ different AI chats across two monitors feels like having superpowers. Claude Code here, Codex there, Hermes in the corner, all working at once. But this gets messy fast. Threads pile up, work gets lost, and by Thursday you can't even remember what you were even supposed to ship. So everything those chats produce should feed two places. Obsidian and Linear. Here's why:

an OpenAI engineer just showed how he gets agents to do his whole job: code, debug and more, using loops 29 minutes from the engineer who coined "harness engineering" he writes the rules, agents write the code, a reviewer agent loops until it's right the winners won't have the smartest model, they'll have the best loop around it watch it, then read the full guide on loops below

My friend applied to 200 tech jobs in two years. No CS degree. No callbacks. Last month Anthropic offered him $750,000. All because of one Stanford lecture. Free on YouTube. One hour. A professor explains how ChatGPT actually works. Not the Twitter version. The real one. He watched it in bed. Paused it eleven times. After that hour he told me something I didn't believe. "It's embarrassingly simple." Three days later he applied to Anthropic. Every single question they asked him, he knew from that video.

Met a guy making $1.6 million a year. Three days ago he was at a Meta conference. Told me he saw the best AI talk of his life. Boris Cherny was on stage. Showed how the Anthropic team actually uses Claude day to day. Boris deleted his IDE eight months ago. Now he codes from his phone. I watched it last night. Had to pause it twice. Not because it was hard. Because I realized I've been using Claude like a toy. He sent me the recording. It was never published. Posting it below.

A senior Google engineer dropped a 424-page doc on agentic design patterns. 424 pages. Most engineers bookmarked it and never opened it again. I read the whole thing. Here are the 15 patterns that actually matter — explained in plain English, with exactly when to use each one ↓

Google CEO, Sundar Pichai: "If you don't teach your agents to debug themselves now, you will keep wasting hours every week." In 30 minutes he explains why the best engineers stopped writing code and started building agents. Most people think building an agent requires an engineering degree. It doesn't. It requires one guide and one afternoon. Watch the interview, then save the exact setup below 👇

THIS NOTEBOOKLM + OBSIDIAN WORKFLOW IS THE FASTEST WAY TO BUILD A REAL SECOND BRAIN > most people dump sources into folders and never touch them again the actual workflow: NotebookLM takes up to 25 million words of raw input - PDFs, YouTube videos, websites - and lets you interrogate them in a single chat with source citations for every answer > once you understand the terrain, the best ideas move into Obsidian. the notebook gets archived. NotebookLM is the scout. Obsidian is where your universe of ideas actually lives 📁 Obsidian ↳ obsidian.md 📁 NotebookLM ↳ notebooklm.google.com

Anthropic engineers just showed how they build a full app from scratch, using a loop of agents 40 minutes from the team behind Claude Code they used three agents: one to plan, one to build, one to judge, cycling until the app actually works the winners won't have the smartest model, they'll have the best loop watch it, then read the full guide on how to actually use loops below