Andrew Ng:
"100% of my tasks are now done by AI agents - hype has exceeded my expectations. Loops is next step.
in 3-6 months, everyone will be using self-improving loops. No more prompting."
In a 30-minute talk, Andrew Ng explains how to build self-improving agentic systems from scratch.
Worth more than a $500 agentic course.
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
I genuinely don't understand why everyone isn't using this yet
Andrej Karpathy, a co-founder of OpenAI, posted a simple idea that hit 16 million views: stop using AI to write code, use it to build a second brain.
You point Claude Code at a folder, drop in any source, an article, a transcript, a PDF, and Claude reads it, links it, and files it into a living wiki of everything you know. It compounds like interest, the more you feed it, the smarter it gets.
Here's the whole thing:
> Install Obsidian, create a vault, open it in Claude Code
> Paste Karpathy's wiki idea file and tell Claude to build it
> Claude makes three folders: raw for sources, wiki for its pages, a CLAUDE.md that runs it
> Drop any source into raw and say "ingest this"
> Ask questions across everything, forever
Five minutes to set up, and you never start from a blank chat again.
Full step-by-step guide with Claude and Obsidian, link below.
Bookmark this
🚨 Anthropic just showed a 27-minute workshop on how to actually do prompts for Claude.
Taught by the people who built it.
Free. No registration. No paywall.
I've seen $300 courses that don't cover what they teach in the first 8 minutes.
Watch it and bookmark it now.
Anthropic engineer, Daisy Hollman:
"You're not supposed to prompt Claude, you're supposed to build a system that prompts itself".
She breaks down how Anthropic's own teams run Claude Code at scale, token bloat killing your prompt before you type a word, Routines most users don't know exist, hands free pipelines using /goal, Git worktrees running multiple instances with zero collisions.
One agent VS a Whole team, Watch the talk below ↓
In twelve months, EVERY company will be running a Company Brain.
The teams who build it this year will spend the next year compounding. Everyone else is going to play catch up.
Here's what it actually is. You connect your Slack, your GitHub, HubSpot, all your tools into one intelligence layer, then build the org chart around it: a main brain up top, a fleet commander running the agent fleet, specialist sub-agents handling execution.
The reason it works is change management basically disappears. Your team already lives in Slack. You're just adding agents to the room they're already in.
You NEED to start building yours now. In a year this will stop being an advantage and will become table stakes.
The U.S. government can ban all the U.S. models it wants. China will keep rolling out and releasing vastly superior models anyway.
And there's nothing at all that Trump can do to stop China's AI models.
Even if they are outlawed in America, people will just distribute them on torrent sites anyway. And on top of that, we have something called the First Amendment which prohibits the federal government from enacting laws that prohibit the exercise of speech, and religion, etc.
LLMs are a form of free speech, obviously.
This is why the U.S. is going to lose the AI race to China.
Badly.
🚨 BREAKING
🇺🇸 FED WILL INJECT $6,638,000,000.00 INTO THE ECONOMY NEXT WEEK, RIGHT BEFORE THE U.S. MARKET OPENS!
NEW FED CHAIR KEVIN WARSH HAS URGENTLY ORDERED THE FED TO BEGIN QE (MONEY PRINTING) TO PREVENT ANOTHER MARKET CRASH.
SOMETHING TERRIBLE IS HAPPENING RIGHT NOW…
Anthropic pays $750,000+ a year for engineers who can build LLMs from scratch.
Not how to prompt them.
Not how to fine-tune them.
Not how to build RAG pipelines.
But how to build them from scratch.
This 2-hour Stanford lecture teaches you everything.
Scaling laws.
Data collection.
Architecture design.
Post-training alignment.
Free. From Stanford.
Watch first. Then read this.
The lecture is the theory.
And this article shows you how to actually build it (with code) ↓
🚨BREAKING: A cognitive scientist from MIT has mathematically proven that evolution guarantees we see zero percent of true reality, that most consciousness in the universe exists without a body, and that non-human intelligences with a wider window on reality than ours can reach in and manipulate it the way a programmer manipulates a video game.
Donald Hoffman (@donalddhoffman) is a cognitive scientist at UC Irvine who has spent 40 years building a mathematical theory of the observer. His work was cited by John Wheeler in the "It From Bit" paper. He studied under Marvin Minsky at MIT, spent two decades secretly meeting with Francis Crick to study consciousness, and has nine specific mathematical conjectures on the table that would derive general relativity, quantum field theory and the Big Bang from a single framework. The top high-energy physicists in the world, Nima Arkani-Hamed and Nobel laureate David Gross, are already saying spacetime is doomed. Hoffman thinks he knows what replaces it.
This interview is the first time he has publicly laid out what his mathematical model explains about alien life, embodiment and the structure of reality.
It already derives time dilation and quantum wave functions directly from differences in observer window size. Physics has spent a century failing to solve the measurement problem because it has been looking in the wrong place. The observer has to come first, and no physicalist framework can get you there.
A consciousness with a larger observer window has access to the underlying structure of our reality in ways we can't perceive or counter. A craft going Mach 40 instantaneously in our headset could be a leisurely maneuver in theirs.
The implications for UAP and alien life are immense.
Embodiment, being locked into a body with fingers and toes as your only interface with the world, is a probability zero anomaly in the full space of possible minds. He also says current large language models are dumber than cucumbers. His new framework, the recursive trace logic, is a completely different architecture, and some of the biggest names in frontier AI have already come to him about it.
The framework has no ceiling, and the implication is a single unified consciousness exploring itself through an unbounded number of perspectives, each one capable of waking up.
Death, in this framework, is just the closing of an icon on the desktop.
Full conversation is live now.
Someone will use Claude Opus 4.8 to make $1,000,000+ before 2026 ends.
Here is how:
A custom software build costs $50,000 to $250,000. A freelance developer charges $100 to $200 an hour. A technical co-founder who joins at the beginning takes 25% to 50% equity, which means if your company is ever worth $5 million, you just gave away $1.25 million to $2.5 million for the engineering. And finding one takes months.
The demand for senior developers outstrips supply so badly that there are 1.2 million unfilled engineering positions globally right now.
Claude Opus 4.8 writes code like a senior engineer, works independently across long sessions without checking in, and has a new capability called dynamic workflows where it makes a plan, runs hundreds of parallel subagents, and verifies its own work before reporting back.
[By the way, if you want to see what Claude, Google AI, ChatGPT and Grok are saying about your business right now, start here (it's free):
https://t.co/Pn764BHwyL]
This thing scored 69.2% on SWE-Bench Pro, the industry benchmark for AI coding agents. That is a new record. For context, OpenAI's GPT-5.5 scored 58.6%. Google's Gemini 3.1 Pro scored 54.2%. It also ships with a fast mode that runs at 2.5x the speed for three times less money.
Here is what that means if you are not a developer.
The global SaaS market does $376 billion a year. There are more than 30,000 SaaS companies worldwide. Solo founders represent 42% of SaaS companies that exceed $1 million in revenue. The opportunity has always been there, but for the last 20 years, there has been one gatekeeper standing between a business idea and a working product: the technical co-founder.
The biggest market of unrealized businesses is people who understand their industry deeply, who know exactly what tool or platform their market needs, who have been sketching the solution on napkins for years, but who cannot code and cannot afford to hire someone who can.
The marketer who knows what analytics tools actually get wrong. The accountant who knows what QuickBooks misses.
The real estate agent who has been sketching a better CRM for three years.
The fitness coach who sees the gap in client management software every single day.
These people have domain expertise no developer has. They understand the customer because they ARE the customer. The technical barrier kept them out.
Opus 4.8 removes that barrier entirely. You describe what you need. It architects the solution, writes the code, runs the tests, fixes the bugs, and handles the complex implementation that used to require a team of three or four developers working in parallel.
Dynamic workflows mean it breaks a project into subtasks, runs them simultaneously, and verifies the output before handing it back. A technical co-founder that costs a subscription instead of 25% to 50% of your company.
Here is how to make this work in you favor:
Step 1: Build a SaaS product in the industry you already know.
You need to know what your customers need better than anyone building for them from the outside. The marketer builds the analytics platform that actually works the way marketers think. The accountant builds the bookkeeping tool that handles the edge cases the big platforms ignore. The real estate agent builds the CRM that tracks what agents actually care about. The fitness coach builds the client management system that gym owners have been asking for.
Your domain expertise is the moat. Opus 4.8 handles the engineering. You handle product decisions, customer conversations, and pricing. That is how every great SaaS company started: someone who understood the problem better than anyone else built the solution. The difference is that "built" used to require a $250,000 development budget or a co-founder who takes half your company. Now it requires a Claude subscription.
Price it at $300 to $500 a month for B2B customers in your vertical. The median B2B SaaS product charges $250 a month. If you are solving a real problem for businesses in a specific industry, you charge more than the median because you built it from inside the industry.
Step 2: This is where the real leverage is.
Every SaaS product needs customers to find it. The marketing analytics platform you built needs to show up when a marketing director asks ChatGPT which analytics tools to use. The bookkeeping tool needs to appear when a small business owner asks Google AI for the best accounting software. The real estate CRM needs to rank when an agent asks Perplexity for the best CRM in the market.
[If you want to see what Google AI, ChatGPT, Claude and Grok are saying about your business right now, start here (it's free):
https://t.co/Pn764BHwyL]
Paid ads get you in front of people who are already searching. Social media gets you in front of people who are scrolling. Neither one builds the kind of authority that makes AI recommend your product by name. When someone asks an AI agent which tool to use in your category, it does not show your ad. It recommends whoever has built the most comprehensive authority: owned content, backlinks, entity structure, domain credibility. The product with the strongest signals becomes the recommendation. The recommendation gets the customers. Everyone else runs ads.
That's the difference between paid ads and SEO/AI search optimization.
ChatGPT has 900 million weekly active users. Google AI Mode is rolling out to millions more. Show up in those results and you don't need a sales team. You don't need an ad budget. The customers come to you because AI recommended you. That is a customer acquisition cost of nearly zero and it is how solo founders scale past the point where paid channels stop working.
Like I said, Opus 4.8 handles the engineering. But the engineering is just the product. The thing that determines whether you have 20 customers or 2,000 is whether your product is the one AI recommends when someone in your industry searches for a solution. Not just on Google. On ChatGPT, Perplexity, Google AI, and the AI agents that are increasingly finding software on behalf of decision makers.
That is the difference between building a product and filling a pipeline.
[If you want to see what AI is saying about your business right now, start here (it's free):
https://t.co/Pn764BHwyL]
Step 3: At 200 customers paying $500 a month, you are at $100,000 a month. That is $1,200,000 a year. One non-technical founder with domain expertise, Claude Opus 4.8 building the product, and SEO Stuff making sure the right customers find it.
That is the gap SEO Stuff was built to close.
https://t.co/eh1auroJF7
Anthropic just released Claude Opus 4.8. It scored a record 69.2% on SWE-Bench Pro, beating GPT-5.5 and Gemini 3.1 Pro. It works independently across long sessions, runs hundreds of parallel subagents on complex tasks, and verifies its own work. The technical co-founder that used to cost $50,000 to $250,000 in development or 25% to 50% of your equity now runs through an AI that works around the clock.
But the product is just the delivery mechanism. The business is built on being findable. And the SaaS founders who own the AI search results in their categories are the ones who will scale past side project into seven figures.
That is the gap SEO Stuff (https://t.co/wKpf0EILTx) was built to close.
Opus 4.8 builds the product. SEO Stuff makes sure the right customers find it. The tools are here. The playbook is above. Someone is going to run this in the next six months and it is going to work.
A few employees of the most evil tech company in the history of the world are only just now realizing they've been empowering that evil with their cognitive efforts.
Do they quit? Nope. They keep working for the same company that they KNOW is providing technology for autonomous killing machines.
But now they want to form a union.
If they had any ethics at all, they would just leave.
Google's own artificial intelligence team just staged one of the most stunning internal revolts in tech history — and it's aimed squarely at a deal the company signed with the Pentagon.
Workers at Google DeepMind, the company's elite AI research division based in the UK, voted 98% in favor of forming a union. That makes them the first workforce at a frontier AI lab anywhere in the world to organize collectively — a watershed moment for an industry that has long resisted it.
The trigger: a recently signed agreement allowing the U.S. Department of Defense to use Google's Gemini AI models inside classified military networks for "any lawful purpose." Critics inside and outside the company warn the loosely worded deal could open the door to autonomous weapons systems and expanded government surveillance with few enforceable limits.
The newly organized workers aren't just asking for better pay. They want Google to formally commit to never building weapons or AI designed to harm people, to bar surveillance tools that could violate human rights, to strengthen whistleblower protections, and to give employees the right to refuse work that conflicts with their ethical beliefs.
For Google, the stakes are enormous. The company spent eight years publicly pledging not to weaponize its AI — pledges critics say this Pentagon contract quietly overrides. Supporters counter that the U.S. military must have access to the most advanced AI to keep pace with global rivals. Now Google's own engineers are forcing the question into the open: where is the line between national security and the technology built to serve it?
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NVIDIA QUIETLY DROPPED A $249 BOX THAT REPLACES YOUR $200/MONTH OPENAI SUBSCRIPTION WITH $2 IN ELECTRICITY
it's called the jetson orin nano super. smaller than a wallet, runs at 25 watts, does 70 trillion ai operations per second. runs llama 3, mistral, gemma and deepseek locally with no api fees and no data leaving your house
a developer running automations and coding assistants pays $200 a month to openai. the same workload on this box costs $2 a month in electricity and breaks even in 10 weeks
install ollama with one command. change one line in your code. point it at localhost instead of openai. everything else works identically
7 billion parameter models handle 80% of what people use chatgpt for. summarization, drafting, coding, document q&a, automation pipelines. total monthly cost drops from $200 to $22
cloud subscriptions keep getting more expensive and rate limits keep getting tighter. the people who set this up in 2025 are going to look very smart in 2027
bookmark this and read the article below