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SpaceXAI Senior Engineer Lauren Tan: "GrokBot is the most powerful agentic tool we've ever released, yet only 1% of users know how to use it properly." "At SpaceXAI, I manage 15+ GrokBot agents, including one Chief of Staff, 3 managers, and 11 workers. This is what engineering looks like in 2026." In just 40 minutes, Lauren explains how to unlock the full potential of agentic AI tools. More valuable than most $500 agentic courses. Skip Netflix and watch this today. It could completely change how you use GrokBot. Bookmark this for later.

this is insane... a guy sat at a stranger's chess table in Ray-Ban and checkmated her with moves he never came up with himself Meta Ray-Ban + Mac + Opus 5.5 + a free repo = an invisible grandmaster living inside his lens here’s the idea in action: 1 → run Stockfish from GitHub, the free engine that does all the thinking 2 → the glasses start a WhatsApp video call to his Mac, so the Mac sees the board through his eyes 3 → a cheap Jev check goes first and skips every frame that can't teach the app anything 4 → Opus 5.5 takes the frames that pass and works out where every piece stands and what she just played 5 → a move only counts once the same read holds on 2+ frames in a row with 3+ squares of evidence 6 → the model only reports what it sees, plain code decides which legal move that means 7 → Stockfish sends back its reply and the Mac draws it into his lens nothing gets played until the frames agree, and that's the same rule that keeps an agent honest when it reads a program you own how REA and Opus 5.5 hold an agent to that rule on the apps you already have is in the guide below

Palmer Luckey says analysts claiming it's too expensive to manufacture in the US are lying to protect megacorps "I think I have a more realistic view than almost anybody. One of the problems with all these analysts that are telling you that it's going to cost $37,000 to build an American iPhone or $100,000 to buy an American computer." "They're trying to prop up a status quo that the megacorporations want to keep going. They want to outsource everything. They want to hire cheaper non-American labor." "They are willing to say and do anything to convince you that it can't be fixed, that it can't come back, that America is this helpless, neutered, post-relevant empire, and it is just not the case." "How do I know that? Because I have to make stuff in America every day because I work in the defense industry. The stuff that Anduril makes every day is not actually that different from a computer. My drones are basically computers. They have memory, a CPU, a GPU, sensors, batteries, a rugged integration." "The only difference between an Anduril attack drone and a laptop is a keyboard and a screen. That is not that hard to figure out, especially for a guy like me who started Oculus and comes from the consumer electronics space." "We're not going to let people lie about what America can and can't do anymore. We're just going to do it."

An Anthropic engineer explains why he earns $350K–$950K: “I know how to build harnesses. 99% of people still build multi-agent systems manually and wonder why they keep breaking. I build systems that run loops, use sandboxed tools, and turn yesterday’s logs into new skills. Same model. 10x more reliable agents that improve while you sleep.” Opus 5.5 → Agents → Harnesses → Loops → Graphs In a short workshop, he breaks down how to build one from scratch: Step 1 → Manage loops, context, and sandboxing through a harness Step 2 → Separate the brain from the tools to reach the first token 60% faster Step 3 → Run agents server-side and recover from crashes using logs Step 4 → Make failures recoverable with retries and replays instead of starting over Step 5 → Turn past execution logs into new memories so the system gets smarter over time Anthropic calls this process “dreaming.” Most developers spend weeks building these systems manually. This workshop shows you a faster way. Bookmark this and watch it.

A former WorldQuant Managing Director published 151 trading strategies for free. 480 pages. 550+ formulas. Stocks, options, futures, FX, crypto. Nobody is going to code all of that by hand. Here’s how to automate it with AI: Download the book (Kakushadze & Serur, “151 Trading Strategies”, free on SSRN) Feed it to Claude and ask it to turn each strategy into a structured spec: idea, formula, inputs, asset class Pick one strategy and have Claude write the backtest code (example below: pairs trading) Run it on real historical data, with transaction costs Check for look-ahead bias and overfitting Paper trade before risking a cent What AI changes: testing one idea used to take days. Now it takes minutes. What it doesn’t change: most strategies stop working after costs and on fresh data. This is a research tool, not a money printer.

Holy sh*t, my GrokBot now runs my TV like a Jarvis, powered by Opus 5.5 I reverse-engineered my Samsung TV with Opus 5.5... One sentence out loud = Netflix launches and starts scrolling by itself. No remote, no phone, no digging through the couch cushions. Here’s the full guide, step by step: step 1 → connect your smart TV and your laptop to the same Wi-Fi step 2 → drop the prompt below into Claude Code on Opus 5.5, along with a photo of your TV’s Settings → About screen step 3 → Opus figures out how your TV accepts commands and spots the loophole: nearly every smart TV exposes a remote-control API on your home network. It’s the same one the phone remote apps rely on step 4 → it builds a tiny remote with exactly 3 tools: open Netflix, move, select. Nothing more step 5 → it hooks that remote into Grok Bot as a plugin. Grok is the ears, the plugin is the hands step 6 → hit Allow on the TV once. That’s the last time you’ll touch the remote step 7 → say “Hey Grok, open Netflix” and watch it browse for you The result: you talk, the TV listens... p.s: works on most Samsung, LG and Google TV models from the last few years. Full prompt below Then read the article below on how to reverse-engineer anything

Sanders vs Claude. A US senator interviewed an AI about your data. Then he pushed back, and the AI changed its answer. What was said: → Sanders asked how much personal information AI companies collect, and how it’s used behind the scenes → Claude warned that AI lets campaigns show each voter a different message: one sees a pitch about protecting jobs, another sees fear about immigration. People end up living in different information worlds → Sanders noted that people tell AI a huge amount about themselves, and some say it knows them better than their spouse → Claude pointed to a conflict of interest: companies that promise privacy also profit from training on personal data → Its conclusion: privacy isn’t just a personal issue, it’s a democracy issue Then came the twist. On pausing new AI data centers, Claude first gave a balanced answer. After Sanders pushed back, it said: “You’re absolutely right, I was being naive.” Critics say that moment only showed how easily a chatbot agrees with you. Supporters say the video put AI privacy in front of many people who don’t follow tech news. Watch it and decide for yourself: did AI reveal the truth, or just tell him what he wanted to hear?

Anthropic CEO Amodei. He just told a global security council that AI could be a risk to humanity as a whole. And this is the same company that builds Claude. A few things from the speech: → 4 years ago, AI could barely write a line of code. Today it writes most of Anthropic’s code → It also solves famous unsolved math problems → Claude helped find a possible new gene editing mechanism, with humans running and verifying the experiments → A “country of geniuses in a data center” could arrive in 1-2 years, maybe less The two risks he named: misuse (like bioterrorists building weapons) and loss of control, when models outpace the people building them. His proposal: external evaluators embedded inside AI labs, like a food inspector, plus a global ban on using AI for biological weapons. His most striking line: “We will slow down as much as necessary” to make sure every release is safe. This is the best 5 minutes I’ve watched on where AI is really heading.

This is wild. A solo founder was burning $1.2M a month on the Anthropic API. Now he’s cutting it to roughly $50K. → Partnered with Sapiom to rebuild the whole setup → Rented GPUs instead of paying per token → Shifted workloads to open-source models That shift helped Polsia reach a $20M run rate. This is the best video I’ve seen on running a one-person AI startup, from $0 to $20M run rate.

Anthropic engineer: Two years of polishing prompts, one window at a time. Then he quit prompting and built a system that prompts itself. Six weeks later, he was shipping more than the whole team he sat on. The lesson: don’t prompt Claude, build a system that does it for you. One that remembers, catches its own mistakes, and gets sharper with every run. 99% of people are still hand-tuning wording. That’s not a prompting gap, it’s a system gap, and you can close it in one evening. Claude → Memory → Self-Correction → Graphs → Systems That Prompt Themselves In 55 minutes, an Anthropic engineer walks through how he builds agents that remember, fix their own errors, and improve with every run using graphs. Plan → Run → Verify → Improve I’ve taken paid agent courses, and none of them go this deep.

I can’t believe it’s real… this tool lets you use AI models for $0 it’s basically BitTorrent for AI models you open the desktop app, pick a model from a network of 200+ providers and start chatting no account, no email more than 10 models are free right now, including DeepSeek V4 Flash, GPT OSS 120B and GLM 5.3 Flash → $0 for everyday tasks → one app, 200+ providers → no subscription and if you need GPT 6 Astra or Fable 5.1, they’re available too, up to 70% cheaper than the official API Try it yourself. The link is below ↓

Anthropic engineer: “You can build 5 assistants in one afternoon. Each one handles a task you’ve been doing manually every single day.” In 50 minutes, he explains how they built Claude Code from scratch using coding assistants. Most developers are still doing all of this manually. Watch the session, then follow the step-by-step guide below on building a self-learning agentic system.

Anthropic engineers just dropped a 1-hour course on running 1,000 Claude agents with Opus 5.5, and it’s the best one out there: “Opus 5.5 is the best model for building agentic systems and reverse engineering with it.” 00:39 - Flows: Claude designs its own multi-agent topology 10:36 - building an agent with Opus 5.5 (live demo) 21:14 - Claude agent system: Fable, Opus, Haiku 39:03 - orchestrating 1,000+ agents (live demo) 1:11:17 - agent safety: brain, sandboxes, auto mode most $500 agentic courses don’t give you even 20% of what this workshop covers. watch it today, then learn how to reverse engineer anything with Opus 5.5 in the article below.

Most people use Claude like a simple chatbot. Almost nobody sets it up properly. I put together a guide with 17 features that change how you work with it. What’s inside: → The feature that makes Claude remember you in every new chat → The file that sets Claude’s rules before you type a single word → The mode that makes Claude think instead of guess → The workflows hidden behind scheduled tasks and Cowork If you’ve used Claude for over a month and never left the chat window, there are features you haven’t touched yet. Every one of them takes minutes to set up, and each comes with a ready prompt you can copy. Read it today, before it gets buried in your feed ↓

Anthropic CEO Dario Amodei: “When revenue grows 10x every year, a single wrong bet on compute can bankrupt you.” “Say I assume revenue keeps growing 10x a year.” “That’s 100 billion by the end of 2026, and 1 trillion by the end of 2027.” “In reality that means around 5 trillion dollars in compute, since it’s a trillion a year for five years.” “If my revenue comes in at 800 billion instead of a trillion, no hedge on Earth can save me from bankruptcy.” “I can’t spend a trillion dollars a year on compute in 2027 if my timing is off by even one year.” he smiles while explaining how one mistimed year of compute spending could end a company

Tesla just flew a car over other cars. Then it landed. At SpaceX’s Texas test site, the new Roadster used compressed-air thrusters to launch off a ramp and flip in mid-air, clearing a lineup that included a Cybercab, a Cybertruck and a Semi. foxbusinessFox News Elon Musk’s take: “Turns out the future does have flying cars.” tikr 0 to 60 mph in 0.81 seconds. 230+ mph on the faster versions, by Tesla’s own claim. Yahoo FinanceFox News The catch: production starts in 2028, and Tesla has missed every delivery date since 2017. foxbusinessCNBC For a century, we judged cars by speed and braking. Tesla just changed the question: what if the road is optional? Real car or the best demo that never ships? Tell me below.

SpaceXAI engineers (ex-Cursor): "Right now I'm running 20-30 GrokBot agents, they are fixing 100% of my code bugs even when I sleep every time our team gets feedback on GrokBot, my bots are automatically going off and fixing them" In a 28-minute podcast, SpaceXAI engineers reveal their actual GrokBot setup in a live demo It's worth more than 100 articles on how to set up GrokBot, from engineers who built it Watch today, then read how to build your team of self-learning Grok agents in the article below

"in 6-12 months GrokBot will be #1 tool for building agentic systems. In a year 100% of code will be done by LLM's at SpaceXAI, more than 70% of engineers already using GrokBot to build self-learning agentic systems" In a 40-minute talk, Elon with SpaceXAI engineers discuss how the future of AI engineering will look like worth more than 2 hours of Stanford lecture on AI engineering watch today, then read the article below on building a self-learning agentic system with GrokBot