Nobel Prize winner and Google DeepMind CEO Demis Hassabis just revealed the real AI skill gap: “The next generation will do things that used to take teams of 10, 20, 30, 50 people” Most people heard that and thought: “Cool, AI makes me faster” Wrong. AI does not just make people faster. It changes what one person can become. A startup used to need: > researcher > designer > developer > marketer > analyst > support team > ops manager Now one AI-native person can wire all of that into workflows. > Agents that research. > Tools that write. > Workflows that test. > Automations that publish. > Memory that compounds. This is not prompt engineering. This is leverage. The next 5 years will not belong to people who write better prompts. They will belong to people who build better workflows. Watch the full interview. Bookmark this. It is one of the most important ideas of the decade.

Daniela and Dario Amodei, co-founders of Claude, predicted their own model would get banned. Then it happened. "This thing kind of seems like a weapon. We probably shouldn't give it to everyone right away" - Dario, on Mythos In his Oprah interview he described Mythos as better than human engineers at breaking into code - the exploits behind ransomware on hospitals. So they never released it publicly. Then the warning came true. On June 12 Anthropic shipped Fable 5, the public Mythos-class model. 3 days later a jailbreak unlocked that exact "weapon" capability and the US government forced Fable 5 and Mythos 5 offline worldwide. Too dangerous to release, banned 3 days after launch. He saw it coming. Who decides when a model is safe: the lab, or the government? Watch the full Oprah interview. Bookmark this.

Nobel Prize winner and Google DeepMind CEO Demis Hassabis just revealed the real AI skill gap: “The next generation will do things that used to take teams of 10, 20, 30, 50 people” Most people heard that and thought: “Cool, AI makes me faster” Wrong. AI does not just make people faster. It changes what one person can become. A startup used to need: > researcher > designer > developer > marketer > analyst > support team > ops manager Now one AI-native person can wire all of that into workflows. > Agents that research. > Tools that write. > Workflows that test. > Automations that publish. > Memory that compounds. This is not prompt engineering. This is leverage. The next 5 years will not belong to people who write better prompts. They will belong to people who build better workflows. Watch the full interview. Bookmark this. It is one of the most important ideas of the decade.

6 co-founders of Claude just exposed why OpenAI and Google are chasing Anthropic: "Simple things work very, very well" But not the way you think. Everyone in AI says they want simplicity. Then they build complexity. More evals. More metrics. More guardrails. Anthropic asked: what if we just... didn't? Traditional safety training needs tens of thousands of human labels. They replaced almost all of it with ~16 written principles. A constitution. And let the model read it. Everyone said it wouldn't work. Now Gemini and Qwen use versions of it. Google's own research confirmed it matches human-feedback training at a fraction of the cost. The simple thing beat the complex thing. Because in AI, simple is scalable. This is the framework every AI builder needs for 2026. Bookmark it.

Boris Cherny, Head of Claude Code: "I don't prompt Claude anymore. I write loops they do the work" Most people still type perfect instructions into AI and wait. Cherny skipped that. Instead of one query at a time, he built a loop. The AI writes. Checks itself. Fixes it. Moves to the next task. No babysitting. Think of it this way: you're rowing by hand. He built an engine. The numbers are wild: > Tens of thousands of AI agents running simultaneously > Code shipping grew 8x since January > 4% of all GitHub code now comes from Claude Code He wakes up. Work's already done. People spend $500 on AI courses for this. You just learned it. Bookmark this to watch on the weekend.

Meta CEO Mark Zuckerberg just revealed the uncomfortable truth about AI: "People are afraid of AI. But reality is simpler: you will either use these tools or lose to someone who uses them" It's not about whether AI replaces you. It's about whether you use it better than the person next to you. The question is no longer "Will AI take my job?" The real question is: "Am I moving faster than my competition?" Right now, the best teams are already building AI agents that research, code, test, and ship. While most people ask ChatGPT one question and stop. The divide is not between those who have AI and those who don't. The divide is between those who use it and those who don't. Meta is scaling Llama across billions of people. They're not waiting for the future. They're building it. Bookmarked. Watch later.

Google CEO Sundar Pichai just said a solo dev with Claude now outcompetes a 10-person Google team. And he's right. But most developers heard it and thought: "Cool, I'll write better prompts" Wrong. That's not the gap anymore. The gap is: a real system prompt. Stack context. Memory. Behavior rules. Claude walking in already knowing the job. Because here's what 90% are doing they open a fresh session and re-explain everything. Every. Single. Morning. It's like hiring a genius who forgets the job overnight, every night. $895 burned per developer every week just re-explaining the same context. The split is brutal: > 90% = re-typing the same context into a blank box forever > 10% = Claude acts like a senior expert before they type word one The 90% think the fix is a smarter model. It's not. It's the system prompt. Which group are you in? Bookmark this - you'll want to reference it.

Boris Cherny, Head of Claude Code, said the line that makes "writing the perfect prompt" sound outdated: "I don't prompt Claude anymore. I write loops, the loops do the work" Most people are still trying to type the perfect instruction into AI and wait for an answer. Cherny skipped that entirely. Instead of asking the AI one thing at a time, he sets up a loop and the AI keeps going on its own. It writes. It checks its own work. It fixes it. Then it picks up the next task. No babysitting. Think of it like this: most people are still rowing the boat by hand. He built an engine. The numbers are hard to believe: > some days he's running tens of thousands of AI agents at once > the code his company ships has grown 8x since January > Claude Code now accounts for around 4% of all code on GitHub He wakes up in the morning and the work is already done. In 30 minutes, he walks through the exact setup he uses every single day. Worth more than most $500 AI courses. So here's the real question: are you still typing prompts one by one or are you ready to build the loop? Bookmark this to watch on the weekend.

Boris Cherny, Head of Claude Code at Anthropic, hasn't hand-written a line of code in 8 months. Most devs think that means he's just using AI autocomplete a lot. Wrong. He's orchestrating fleets of agents, some days tens of thousands: that write, review, and decide what to build next. He's not even in the loop. Another Claude does the prompting. The split is brutal: > 90% of devs = typing every line by hand > 10% = managing agents, working at the level of goals not keystrokes Code output at Anthropic is up 8x since January. Claude Code now writes itself. In 5 years the 10% ship products solo while they sleep. The 90%? Doing work the fleet already does faster. But Boris still says: learn the craft. The bottleneck isn't building anymore - it's the idea. Which group are you in? Watch the full breakdown. Bookmark this.

Jensen Huang says every engineer will soon run a hundred agents. He runs Nvidia, the ~$5 trillion company that makes the chips all of AI is built on. So people listen. Funny thing. 90% of people can't get ONE agent to remember the task past 3 messages. You're not managing a hundred agents. You're managing a hundred goldfish. The problem was never the number. Nobody teaches the three things that actually matter: - agent memory (why it keeps losing context) - harness engineering (how agents don't trip over each other) - project context (how a task survives a restart) No CS class covers this. One builder mapped the whole thing out. Free, from zero, step by step. Bookmark it for the weekend 👇

Anthropic's Head of Engineering just dropped the wildest Fable 5 / Claude 5 line yet: their model found a bug that hid in OpenBSD for 27 years. Humans missed it. The model didn't. That's why this matters, not benchmark theater. Frontier evals where the model finds what humans couldn't. The part most people skipped: Fable 5 and Mythos 5 are the same model. Mythos is the locked version (cyber bio partners only) Fable 5 is that same frontier brain with safeguards and the one you can try right now. So that OpenBSD capability? One tab away. The 7-min Code with Claude Tokyo opener breaks down how. Watch it, then go push Fable 5 till it breaks.

Ex-Google CEO Eric Schmidt says the people getting rich from AI aren't smarter than you. They just stopped scrolling threads and learned the actual stack: Agents → Claude Code → Prompts → Memory → Skills → MCP → Routines 13 free resources that teach all of it. Built by the people who made the tools. $0. Bookmark this. Links below 👇 Start here: Anthropic Academy anthropic.skilljar.com Claude Code 101 anthropic.skilljar.com/claud… Claude Code in action anthropic.skilljar.com/claud… Core docs: Claude Code overview code.claude.com/docs/en/over… Prompt engineering platform.claude.com/docs/en/… Interactive prompt course github.com/anthropics/course… The stack, piece by piece: CLAUDE.md memory code.claude.com/docs/en/clau… Skills code.claude.com/docs/en/skil… MCP code.claude.com/docs/en/mcp Routines code.claude.com/docs/en/rout… Agent architecture langchain.com/blog?category_… Going deep: Claude Code ultimate guide github.com/FlorianBruniaux/c… Awesome Claude Code github.com/hesreallyhim/awes…

DEVELOPERS ARE QUIETLY CANCELING THEIR $20/MONTH CLAUDE PRO SUBSCRIPTIONS Not because the model got worse. Because they signed up at freemodel .dev, verified via Telegram, and now run Opus 4.8 free in their terminal The quiet rebellion is happening right now: Heavy users are bypassing Anthropic's paywall - freemodel .dev with $10 free credits, referral bonuses, no subscription lock-in. One-time setup cost > endless monthly rent One dev's stack: > freemodel .dev - sign up, get instant $10 (STEP 3) > Telegram bot verification > API key created, saved to secure location > settings.json at C:\Users\<you>\.claude\ with base URL https:// cc.freemodel .dev > total monthly AI spend: $0 for 80% of daily work He keeps one cheap frontier subscription only for the hardest 20% of tasks. Everything else runs through freemodel .dev The era of paying Anthropic $240/year for terminal access is ending for those who are willing to own their config

Nobel Prize winner Demis Hassabis just accidentally revealed who survives the next 5 years and who doesn't. "One person who understands AI will outperform an entire startup team" Most founders heard that and thought: "Oh no, I need to learn prompt engineering" Wrong. That's not what "understands AI" means anymore. It means: building workflows. Chaining systems. Automating entire departments. Not typing better questions into ChatGPT. The split is brutal: > 90% of people = still using AI like a calculator > 10% of people = treating it like infrastructure In 5 years, the 10% will run everything with half the headcount. The 90%? Replaceable. Which group are you in? Watch the full breakdown. This is the only skill gap that actually matters right now. Bookmark this. You'll want to reference it.

Paying $459/month for cloud AI, I paid $3. One machine took back $5k/year from OpenAI and Anthropic.

pov: made $50k in a week for walking through Google Maps and realizing dentists from 2009 still have 2009 websites.

POV: didn't know faceless YouTube channels could be cloned in 8 languages and make $262k/month