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Instant noodles vs Real food : How Ultra processed meals shape your child’s growth.

Claude Cowork, Mythos, and the Future of Software: my conversation with @felixrieseberg, who leads Cowork at @AnthropicAI 00:00 Intro 01:53 Claude Mythos Preview and the “step-function change” 06:16 Why Anthropic is treating Mythos differently 11:19 The real story behind Claude Cowork’s “10-day” build 12:42 Why Anthropic realized Claude Code needed a non-technical version 15:44 What Claude Cowork actually is 17:03 Under the hood: virtual machines, tools, skills 18:36 Where Cowork’s memory actually lives 19:26 How Cowork connects to files, apps, and the internet 20:45 Why Felix thinks the local computer is under-appreciated 24:49 Trust: how do you get users comfortable with AI agents? 28:45 What UX actually means for AI agents 31:27 Anthropic Cowork's roadmap is only one month long 34:12 Building 100 prototypes 35:10 If execution is free, what becomes the bottleneck? 37:25 Does it come down to taste? 40:12 The hardest part of building Claude Cowork 41:43 Advice for founders building AI agents 44:21 SaaSpocalypse: what’s left for software startups 49:30 Where AI agents are going next 51:20 Regulated industries and enterprise adoption 54:15 Hot takes: what's underrated, overrated, and what Felix would build today

The founder of a $4B inference company says that if you're building agents, foundational models could become your IP. According to @lqiao, 90% of the world's data is still private and locked inside applications and enterprises. Foundation models are trained on public internet + labeling company data, which is barely 10% of all the data. And this is why your application and foundation models are misaligned by definition. Companies building agents don't treat models as APIs. They opt for a product-model co-design. - Models continuously learn from your private data - Pick up domain-specific intelligence - Run faster - Cost less - Scale to millions of users

Highest form of super intelligence! Ignited by Indian spirituality and meditation.

If you struggle with morning energy, do this right when you get out of bed: • 5 squats • 5 push-ups • 5 lunges per leg • 30-second plank I call it my 5-5-5-30 Method. It’ll give you a boost and start your day with a winning feeling. Takes 2 minutes and just works. Try it.

This 16-minute talk by two Anthropic engineers who built Claude Skills will teach you more about building them right than most developers figure out on their own in months. Bookmark this & watch, no matter what. Then read the guide below by @eng_khairallah1

Major life hack: The ability to keep showing up even when the rewards are uncertain. Tolerance for uncertainty is the most valuable human trait. The one who can tolerate the most uncertainty is the one who will eventually win.

I became an Amazon Tech VP because I made decisions that turned into money. Coding skills, a "hard skill" did not matter despite the "tech" in my title. All your hard skills will be irrelevant soon, so learn from my experience:

Walking rewires the brain. Walking rewires the brain. Walking rewires the brain. Walking rewires the brain. Walking rewires the brain. Walking rewires the brain.

Introducing the OpenAI Safety Fellowship, a new program supporting independent research on AI safety and alignment—and the next generation of talent. openai.com/index/introduc…

My biggest takeaways from @AnthropicAI's Head of Growth Amol Avasare: 1. Engineering is getting the most AI leverage—and it’s squeezing PMs and designers. With Claude Code, a five-engineer team now produces the output of 15 to 20 engineers. But PM and design productivity haven’t scaled proportionally. The result is a compressed ratio where one PM is effectively managing the output of a much larger engineering team. Anthropic's growth team is responding in two ways: hiring even more PMs (!), and formally deputizing product-minded engineers to act as mini-PMs for any project with less than two weeks of engineering time. 2. Anthropic is using Claude to automate its own growth. The internal initiative is called CASH (Claude Accelerates Sustainable Hypergrowth). It works across four stages: identifying opportunities, building features, testing quality, and analyzing results. Right now it handles copy changes and minor UI tweaks. The win rate is comparable to a junior PM with two to three years of experience, and improving rapidly. 3. The one part of PM work that AI can’t automate yet: getting six people in a room to agree. Amol and his head of design joke that even with AGI, it’ll still be impossible to align six stakeholders. Cross-functional coordination—managing opinions, navigating politics, mediating tradeoffs—remains the bottleneck that AI doesn’t touch for larger projects. This is why Amol believes PM roles aren’t going away, and may actually grow. 4. 60-80% of Anthropic’s growth team's projects have no PRD. For smaller work, kickoffs happen on Slack—messages back and forth with product-minded engineers who can push back and ask the right questions. For larger projects, Amol believes in a proper 30-minute cross-functional kickoff (legal, safeguards, stakeholders) to surface concerns early. 5. Adding friction to onboarding drives growth—if the friction helps users understand why the product is for them. His work Mercury, MasterClass, Calm, and now Anthropic, adding steps to onboarding flows consistently improved conversion. The key: cut annoying friction that doesn’t add value, but add friction that helps users understand why the product is for them. 6. AI companies need to focus on bigger bets, not better A/B tests. Amol’s argument: if your core product value is driven by AI, then the future value is orders of magnitude higher than today’s value, because model capabilities grow exponentially. In that world, micro-optimizations capture a shrinking share of a growing pie. Traditional growth teams do 60% to 70% small optimizations and 20% to 30% big swings. At Anthropic, they flip this ratio. 7. Amol built a weekly AI agent that scans Slack for cross-functional misalignment. Using Cowork with the Slack MCP, he has a scheduled task that looks across his projects and conversations and surfaces areas where teams are about to do overlapping work or pull in different directions. A colleague on the enterprise team already caught major misalignment that would have caused weeks of wasted effort. 8. A traumatic brain injury taught Amol the principle that now drives his work: freedom through constraints. In early 2022, a kick to the head during a Muay Thai sparring session caused a traumatic brain injury. Amol spent nine months off work and months relearning to walk, unable to look at screens or listen to music for more than 20 seconds. He was re-injured a month after joining Mercury and had to take two more months off. He’s still not fully healed. But the constraints—no alcohol, no caffeine, mandatory breaks, daily meditation—have become the habits that let him operate at the intensity Anthropic demands. “The true freedom in life is learning how to be content when you don’t get what you want.”

Wealth is not about working more hours. It's about building systems that work without you. AI is the fastest way in history to build those systems.

Jevons Paradox, live on the scoreboard. AI made coding massively cheaper. Everyone predicted engineering layoffs. Instead: 67,000+ open roles, highest in 3 years, doubled since the 2023 trough. This is the coal story all over again. Efficient steam engines didn't reduce coal consumption. They made coal so cheap that it spread into every corner of the economy. Production climbed for another century. AI did the exact same thing to software. When the cost of building an app drops 10x, every company that couldn't justify custom software suddenly can. The total addressable market for code exploded. The narrow "translate logic into syntax" programmer roles? Down 27% since 2023. The system architects, AI integrators, and product engineers? More demand than ever. Software engineer postings up 11% YoY while the broader job market is flat. AI is eating jobs. Just not tech jobs.

Jensen Huang just killed the AI jobs panic. Not with a forecast. With a pattern. Huang: “The fact of the matter is PCs made us more busy. The internet made us more busy. Mobile devices made us super busy.” Every tool that promised to free us expanded what we could reach instead. The PC did not give accountants their afternoons back. It gave them ten times the clients. The internet did not slow anything down. It erased the geographic limit on what one person could build. The smartphone did not hand you time. It handed work your coordinates and never let go. None of them reduced what we did. All of them raised what we could. AI will not be different. It will not give you rest. It will give you a thousand things you couldn’t have built before. The people waiting for relief are reading the wrong pattern. This was never about less. It was always about expanding what one person can attempt. The panic runs on one assumption. That labor is surplus. Huang: “We are millions of truck drivers short. We are tens of millions of manufacturing workers short.” The economy is not drowning in surplus labor. It is bleeding from the absence of it. Robots are not arriving as invaders. They are arriving as reinforcements to a system already failing without them. The collapse was already underway. The machines just showed up to a building already on fire. Huang: “They’ll hire more people to manage more robots, hire more people, manage more agents.” The raw work is leaving human hands. The direction of it is not. Every company deploying agents still needs someone deciding what they’re pointed at. The question is not whether AI replaces you. The question is whether you learn to command it before someone who already has. Every tool that promised less work delivered more world. AI will be the largest expansion of that pattern in history. You are not losing your job to a machine. You are losing it to someone who learned to run one.

7 THINGS YOUR CHILD WILL REMEMBER ABOUT YOU FOREVER: And it's not the one you think THREAD 🧵

The "AI job loss" narratives are all fake. AI = massive ramp in productivity = massive ramp in demand = massive jobs boom. Watch.

Right form, Right Energy. Correct your Surya Namaskar, correct your practice.

Anthropic is on an unprecedented growth run. Just in the past year they grew from $1B to $19B ARR. They added $6B in ARR just in *February*. Companies like Palantir and Atlassian took 15-20 years to reach ~$5B ARR. Anthropic is adding that every month. Amol Avasare is head of growth at Anthropic, and one of the most impressive people I've had on the podcast. In his first ever public interview, Amol shares: 🔸 How Anthropic is automating growth experiments with Claude (their internal tool called “CASH”) 🔸 Why activation is the single highest-leverage growth problem in AI 🔸 Why Amol is hiring more PMs, not less 🔸 How he uses Cowork to automatically detect team misalignment in Slack 🔸 How the company’s focus on AI coding created a research flywheel that accelerated their models 🔸 How Amol landed his role by cold emailing Anthropic’s CPO @mikeyk 🔸 The brain injury that nearly ended Amol's career Listen now 👇 youtu.be/k-H4nsOTuxU

Nobody tells you this: Confidence is less about knowing you’ll win and more about knowing you’ll bounce back even if you don’t. Real confidence is resilience. Adaptability. Tolerance for uncertainty. Fear loses when you know failure is never final.

This is the best time in history to build a startup. Here's why: - Build cost is basically zero. - Agents are doing the work. - Audiences are underpriced. - The best niches are wide open. What you need to start: - An Idea - A laptop - claude code - A niche audience of 100 to 5,000 What you can build with that: - A business that runs 24/7 - 95% margins - Zero employees The window is 12–24 months before competition catches up. Every day matters.