leanxbt

In 20 minutes, the first intern OpenAI ever hired gave a live lecture on solving physical AGI. Jim Fan. Now Director of Robotics at Nvidia and co-lead of Project GR00T, the humanoid program. He calls the talk "Robotics: Endgame" and lays out the entire roadmap as a direct parallel to the LLM story. Most people think robotics is a hardware problem. This guy is solving it like a foundation model problem, one motor at a time. Bookmark and watch this. Then read the complete article below.

@w1nklerr which animation tool is he using for the cartoon mascots?

He pulls $12k a month from a YouTube channel he never appears on Black t-shirt, kitchen table, a tube of skincare cream in his hand like it's the secret to everything. On the wall behind him, a screenshot of NuNu TV Nursery Rhymes with 28.2 million subscribers and 771 videos. He doesn't run that channel, he just copied the format. The whole pipeline runs through Claude. A chat open on the tablet, one prompt typed in plain English. "Generate a scene by scene breakdown for a one minute kids nursery rhyme." Claude spits out the script, the scenes, the lyrics, and the voiceover. Everything stitches together into a short and gets uploaded the same day. One channel has already pulled in 77 million views combined and brings him around $12k every month, and the plan is to spin up 5 or 10 more just like it. Same prompts, different niches, different cartoon mascots. About 2 hours of attention a day is all it takes. The rest is Claude printing nursery rhymes in the background. Save this video before YouTube gets flooded with people doing the exact same thing.

@0x_Discover $80 to $4k copying one wallet - how long did that actually take?

It started as a joke Gave Claude $20 Left it running overnight Woke up to: script finished +$95 from the first 5 trades Didn’t touch anything Then I found this wallet: 0xb27b...b82 $384,858 profit 13,070 predictions $18.5K max win active since March 2026 No hype No followers Almost no one watching So I tested it While building my system, I copytraded it $80 → $4,218 in a few weeks Every trade looked the same Same structure Same logic This isn’t trading It’s one equation repeating Examples: $17,839 → $36,318 $3,112 → $15,011 $10,676 → $22,178 Here’s what I gave Claude: Trade BTC windows with clear edge Size by probability Skip high volatility Update after every trade That’s it No babysitting No emotions Just structure Copy it:t.me/KreoPolyBot?st… You’re early That won’t last

@gippp69 how did he find the nursing students niche specifically - was that the first idea or did he test others?

THIS GUY BUILT AN IPHONE CHAT APP WITH CLAUDE CODE IN 90 SECONDS AND TURNED IT INTO A $1,200/MO NICHE TOOL One MacBook, Claude Code, Swift, an iPhone simulator and one simple idea: a private exam-prep chat app for nursing students who need fast answers before tests. Not another generic chatbot. The app had saved topics, prebuilt exam prompts, simple explanations and a $6.99/month unlock for unlimited sessions. At 180 paid users, that is roughly $1,200/month before Apple fees. Tiny audience, clear pain, simple product. Most people see a 90-second demo. He saw a template for a paid niche app.

@NainsiDwiv50980 does claude actually write good rules to its own claude.md or do u have to edit them manually?

The guy who BUILT Claude Code is running 10–15 parallel AI agents like an engineering team. Not prompts. Systems. His secret isn’t some hidden feature. It’s a simple file: CLAUDE.md And it changes everything. Every time Claude makes a mistake → it writes a rule. Every correction → permanent memory. Every session → smarter than the last. > “Update your CLAUDE.md so you don’t make that mistake again.” That’s the loop. No repeated errors. No wasted tokens. No babysitting. Just compounding intelligence inside your own codebase. While most people: Rewrite the same prompts Fix the same bugs Start from zero every time He’s building a self-improving engineering system. And it gets crazier: • 10+ agents running in parallel • Research, coding, testing — all split into sub-agents • Clean context, zero clutter • Complex problems = more agents, not more thinking He hasn’t written SQL in 6+ months. Claude just pulls from BigQuery via CLI. This isn’t “AI-assisted coding.” This is AI orchestration. And the gap is already showing. Claude Code is now contributing to ~4% of all public GitHub commits. If you’re still using AI like a chatbot… You’re not behind. You’re playing a completely different game.

@mmoyshaa 29k positions with 99% winrate - is that real edge or just lp positions farming fees?

29k+ positions on Polymarket 99% win rate $115M in total volume and the craziest part of this profile isn’t even the overall stats it’s individual trades like these look at this: a Solana price range bet bought at 0.1¢ $29 turns into $14,881 $30 turns into $13,842 almost 50,000% ROI how is this even possible? the account genuinely looks like it operates in two completely different modes 95% of the time it farms safe 2–5% gains then suddenly it finds some completely broken mispriced market nobody noticed and the scary part is: with a 99% win rate it doesn’t even look random anymore check his profile: @sharky6999?r=tom310#cKipKZj" target="_blank" rel="nofollow noopener">polymarket.com/@sharky6999?r=…

@AleiahLock chelsea top 4 next season with alonso or still rebuilding year?

Do you understand what just happened? > be Xabi Alonso > Champions League winner as a player > World Cup winner. European champion. > retire. start coaching. >Every top club in Europe wanted Xabi Alonso. >Real Madrid were waiting. >Bayern Munich were calling >Liverpool fans were dreaming. >He chose Chelsea. >Four-year contract. > the rebuild starts now > @PolymarketSport we’re waiting this moment > Join now polymarket.com/sports

@eng_khairallah1 what's the hardest part of the twitter clone project - auth or the agent security layer?

Karpathy just described what hiring looks like in 2026: "Build a large project with Claude Code — like a Twitter clone. Make it secure. Have real agents using the platform doing stuff." one person replacing an entire dev team. here's what he covers: > most founders can't build this themselves > most dev teams haven't adapted yet > the people who can build AI automations for projects are charging whatever they want this is the highest-leverage skill in tech right now. And the market is wide open. the article below is the full system. how to build AI automations. how to find clients. how to make real money doing it. bookmark & read this before your competition does.

@mopozeuX @Polymarket @PolymarketTrade was he in the cs2 scene or pure value bet on the odds?

Polymarket trader earned $181,776 for one prediction on CS2 No one knew about him yesterday, but he is one of the participants in the historic moment. We have a match with you: Counter-Strike: Natus Vincere vs Vitality (BO3) - IEM Atlanta Playoffs Anyone who at least somehow follows the CS2 esports scene will say that this is an easy victory for Vitality. 21 semi-finals in a row. 5 winning tournaments in a row. 1 the NaVi team that stopped all this There was a 16.7% chance that NaVi would win.

@BimbaCrypto $9b valuation - does that math make sense at $425m daily volume or is it stretched?

🧠 POLYMARKET DIDN'T JUST PREDICT THE FUTURE - IT CHANGED LIVES A 22-year-old in lockdown. A laptop. An idea: what if you could bet on the truth? Six years later, the owners of the New York Stock Exchange value that idea at $9 billion. The crowd sees a prediction market. Smart money sees a life‑transforming machine. > 2020 - A kid raises $4M to fight COVID misinformation. No one believed him. > 2022 - The US kicks him out. He expands to the world instead. > 2024 - $3.5B traded on the election. Peter Thiel and Vitalik join. The world starts paying attention. > 2025 - He buys a US license. ICE, the NYSE owner, invests $2B. Wall Street surrenders. > 2026 - CLOB v2, PUSD, AI agents. Daily volume: $425M. POLY token incoming. But the real story isn't the volume. It's the people: The student who turned $500 into rent money. The degen who quit his job after a $10,000 win. The whale who faded the crowd and printed $1M. The beginner who ran a Claude bot and never looked back. Polymarket didn't just change how we trade. It changed who can trade. From a lockdown bedroom to a global truth machine - and we're all part of it. The best part? We're still early.

@0xbeinginvested how many uploads til the algo started pushing his vids consistently?

-> A 19 year old teenager -> is earning $10,000 a month -> uploading rain sounds to -> YouTube, sitting in his -> bedroom with a ceiling fan -> spinning behind him. -> And pulling in 5 figures a -> month doing nothing but rain. -> No singing. No production. -> No instruments. No video edits. -> Just rain. The niche is huge -> and most people don't even -> realize it exists. Millions of -> people fall asleep, study, -> meditate, or scroll their phone -> to long ambient videos of rain, -> thunder, and storms. -> YouTube serves them for hours. -> And the ad revenue stacks up -> while the viewer is literally asleep. -> He doesn't even record the rain. -> He just types one prompt -> into an AI tool -> make me rain sounds, -> add thunder to it. -> The AI generates the audio. -> He stretches it into a 1 to 3 -> hour loop, slaps a calm -> thumbnail on it, uploads to -> YouTube and lets it sit there. -> The channel runs on autopilot. -> The videos are evergreen. -> The audience never stops -> needing background noise. -> 10k a month. Solo. -> No face on the channel. -> No talent required. His own words

@AlterEgo_eth rs-clob-client worth the rust learning curve over py-clob for latency gains?

Here Are The 6 Most Valuable And Actively Maintained Polymarket GitHub Repo You Should Know About in 2026 Each of them solves a specific critical part of building and running a trading bot - from order execution to monitoring, backtesting and architecture Instead of digging through dozens of half-dead repos, you can start with these 1. Polymarket/py-clob-client-v2 - official Python SDK for CLOB V2, active, last release May 9. The starting point for any Python bot. Working examples in /examples, ready to run Repo: github.com/Polymarket/py-… 2. Polymarket/clob-client-v2 - TypeScript/JS SDK for CLOB V2, active, updated May 8. Same thing for Node.js bots. Note: the old clob-client (514 stars, 170 forks) was archived May 11 - do not use it, V1-signed orders no longer execute on production Repo: github.com/Polymarket/clo… 3. Polymarket/rs-clob-client-v2 - Rust SDK for CLOB V2, updated May 13. Built-in heartbeat, zero-cost abstractions, AWS KMS support for remote signing. The right choice if you're building a high-performance maker bot where latency actually matters Repo: github.com/Polymarket/rs-… 4. Polymarket/agent-skills - official reference for integration architecture, active (Feb 2026, 112 stars, 14 forks). Not a bot - a clean knowledge base covering every layer: authentication, order patterns, market data, WebSocket channels, CTF operations, bridge, gasless transactions. Each topic is its own documented module. Study the structure before writing a single line of bot code Repo: github.com/Polymarket/age… 5. Polymarket/polymarket-sdk - TypeScript SDK for Polymarket Wallets, updated April 2026, 3,395 npm downloads. Required if you're implementing the deposit wallet flow for new API users or handling on-chain transactions programmatically Repo: github.com/Polymarket/pol… 6. Polymarket/ctf-exchange-v2 - Solidity smart contracts for the V2 exchange, launched April 28, 2026. For anyone who wants to understand exactly what happens on-chain when your order gets matched: CTFExchange.sol, CalculatorHelper.sol, TransferHelper.sol Repo: github.com/Polymarket/ctf… Bookmark this!

@KnightPredict do u think he had actual info early or just got lucky on the timing?

🚨$855 → $15,000. ×18 in just a couple of days First confirmed Hantavirus case in the US has been reported Yes shares on Polymarket surged from 5-7 cents to over 90 cents after the news Trader 'MtnMark' entered the position two days before the news at an average of 5.3¢ He put in $855 and walked away with a fat profit One perfectly timed entry put the trader solidly in the green He's already opened a new Yes position on the "Hantavirus pandemic in 2026?" market But I think this time his luck has run out

@ridark_eth 10k+ predictions in one month is like 350/day - is that even humanly verifiable or just trust the onchain data?

This bot executed over 10,842 predictions and somehow pulled in over $106,292 in just one month on the short-term Bitcoin market. In a matter of weeks, it’s already cleared an aggressively smooth, unbothered profit curve. And the biggest single win? $17,600. But the wild part isn’t the size of any one trade it’s how it ruthlessly snipes micro-movements to stack up into such an unnatural return line. From the outside, it looks like it’s running three simple plays: > Snaps up cheap contracts at 22¢–40¢ right before a shift > Spams rapid, hyper-short binary option intervals > Locks in massive 140% to 330%+ returns back-to-back Then scales total volume traded up to $11,400+ on a single position. But this isn’t a typical "lucky" directional trader guessing where crypto goes next. It’s an institutional quant bot weaponizing a Cross-Market Statistical Arbitrage roadmap. It tracks temporary price gaps between competing venues using the Ornstein-Uhlenbeck mean-reversion framework, while analyzing Level 2 Order Book Imbalance (OBI) to mathematically front-run the "Micro-Price" before the retail UI can even refresh. And yet, right now, this account sits on an absolute masterclass of systematic execution. If it’s exploiting multi-venue structural math this consistently that’s not just a bot. That’s basically a money printer.

@_avichawla does the turn cap actually stop haiku from looping on ambiguous conditions or does it just timeout?

The anatomy of a perfect /goal prompt in Claude Code! (save for later and use it to reduce token usage) The way /goal works is that two models run in a loop. - Sonnet/Opus handles the actual coding. - After every turn, Haiku reads the full conversation transcript and checks whether completion conditions were met. - If Haiku says "not yet," Sonnet/Opus starts another turn automatically. The Haiku evaluator costs almost nothing. But the worker still runs at full Sonnet/Opus rates. So the condition you write directly controls how many expensive turns Claude takes before the loop terminates. Anthropic recommends three things in a /goal condition: - a measurable end state - a stated check - and constraints. They also suggest adding a turn cap. What the docs don't cover is what happens when any of those pieces are missing. A vague condition like "make the app production-ready" loops indefinitely because no command output ever proves that claim. A subjective condition like "complete the migration" lets Claude self-report completion, and Haiku accepts it because the judge only sees the transcript. The nine-section template in the image expands Anthropic's three-part recommendation into a structured prompt that addresses both failure modes. → GOAL defines the objective in a single sentence, eliminating ambiguity. → CONTEXT gives Claude the background it needs, so it doesn't waste turns exploring the codebase. → CONSTRAINTS set hard scope boundaries. → PRIORITY controls execution order so Claude tackles easy wins first. → PLAN states the approach explicitly, preventing aimless exploration that burns tokens. → DONE WHEN forces a binary, observable outcome like pytest exits 0, not a subjective state like "code quality is improved." → VERIFY makes Claude run a specific command whose raw output lands in the transcript, so Haiku judges machine evidence, not self-reports. → OUTPUT specifies what Claude should surface when done. → STOP RULES cap the downside with a turn limit. Without this, a slightly wrong condition loops forever. For even stronger guarantees, pair /goal with a Stop hook that runs your test suite or hits a CI endpoint after every turn. That moves verification from the prompt layer to the infrastructure layer, where it's deterministic. I found this template on findskill(.)ai while researching the perfect way to use /goal command. They don't claim to have created it either, but mentioned it as a community-created template that circulated on X. ____ Find me → @_avichawla Every day, I share tutorials and insights on DS, ML, LLMs, and RAGs.

@zeuuss_01 does higgsfield actually keep brand consistency across 20 assets or needs re-prompting each time?

Higgsfield + Claude just turned a $10k creative agency into a single Claude thread This operator ships 20+ branded ads, product shots, and campaign assets per week - solo, while he sleeps. One prompt - Claude plans the campaign, Higgsfield renders every asset Most agencies still charge $3-15k per campaign That fee is now an API call Here's the math: > agency creative package (10 ads + campaign plan): $8,000-15,000 > product shoots with photographer: $500-2,000 per session > stock content subscriptions: $300-800/month > Claude + Higgsfield combined stack: ~$60/month > output cycle: one prompt → 20+ branded assets in 4 hours 5 things solo operators stopped buying: 1. Stock product photos at $30-100 each. Higgsfield renders the same shot in your brand mood with your product, against any backdrop, in 90 seconds. 2. UGC creators at $300-500 per spot. Claude writes the script with brand voice + target audience, Higgsfield generates the avatar + scene + delivery. 3. Photo studios for launch shoots. One prompt: "render the product in 12 angles for an e-commerce hero". Done in 8 minutes. 4. Instagram ad agencies at $4k/month. Claude plans the campaign calendar, Higgsfield renders every asset, you approve from one inbox. 5. AI tools that give you 1 clip at a time. Claude + Higgsfield gives you the full campaign - feed, story, reel, ad, hero - from one brand brief. In 12 months, the gap between brands paying $10k/month for creative agencies and operators shipping the same volume from one Claude thread won't be design skill It'll be how well they briefed the agent The full step-by-step setup with every prompt is in the article below 👇

@Skaly__Bull the reddit spam part - does that actually still work or is it getting flagged faster now?

This is exactly why the dead internet theory is 100% real >Claude Code writes the software >Supabase hosts the database >Stripe processes the payment >An automated script spams Reddit for validation >Human beings are literally just meat-wallets in the middle paying $15/mo for a loop they don't even understand This playbook is the blueprint of how the modern internet is being hollowed out by indie hackers

@s1rozha_ what sizing method did he end up landing on after the 4 months?

a trader spent 4 months on polymarket and concluded one thing: risk management produces more profit than edge does > they don't notice half their losses are bad sizing > top 5% size positions first. model second > same setup. opposite drawdown the 4 strategies that taught him this are in this article

@techwith_ram which industry is getting hit hardest by ai regs rn - finance or healthcare?

Good AI governance isn’t about doing everything fast. It’s about understanding what matters before taking action. Most companies rush into AI governance by adding random rules, checklists, and risk assessments. But the smarter approach is to pause first and ask: - What AI systems are we actually using? - Which laws and regulations apply to us? - What risks do we truly care about? - Who are our clients and stakeholders? Because if you skip this clarity step, you’ll keep rebuilding everything later. Read the blog attached to learn more about AI governance layers.

@ventry089 hidden_size=16 - did u actually backtest that vs 64 or just trust the theory?

your neural network is losing money on polymarket. it just hasn't told you yet 94% of AI models built for prediction markets fail. not because the math is wrong. because the market already knows what your model is trying to learn one test decides everything: compare your model's predictions against the market price over the last 7 events if the market predicts better - your model is dead. not "needs tuning". dead. shut it down most traders find out after their balance hits zero. this article shows you how to find out before the model that works on polymarket isn't the smartest one. it's the smallest one. hidden_size=16. not 64. not 128. sixteen because on prediction markets you don't have 3 years of daily candles. you have 150 events. total. ever. a big model on small data doesn't learn patterns. it memorizes noise three rules from the article that saved me from blowing up my own bot: parameters must not exceed samples divided by 20. break this rule and you're overfitting by design train only on older events. if your backtest uses future data - your profits are fiction if log-loss is worse than market on 7 consecutive events - kill the model. no exceptions the market on polymarket is often smarter than your AI. the skill isn't building a smarter model. it's knowing when yours has stopped working