hooji

@UtxoSaint @iagadanight If you want robust chain security from staking you must have queues. Staking rewards come from *actually* contributing to network security — it’s not just “free money”.

@hooji2 @iagadanight This is gaslighting… I don’t want a queue to begin with and you want me to understand why there are two queues? 🤡🤦‍♂️ Come back when my stake doesn’t need to leave my wallet.. until then it’s crap.

wtf is a “waiting to be unstaked” queue? 🤣🤣🤣… how tf is $ETH wanting to become the currency of the world with such a fundamentally poopy design?

@UtxoSaint I see you didn’t research it! 🥂

@iagadanight @UtxoSaint 100% serious what makes you think there might be an issue with the design? Do you understand *why* there is a queue (actually 2 queues, one for joining, one for leaving)?

@hooji2 @UtxoSaint Ummmmm I hope your not being serious

@SoulzBTC TRADING

Claude Trading Folder I’ve compressed the best trading prompts into one PDF Get it for FREE: • Like + Repost + Comment “TRADING” • Follow me so I can DM you

Actually @grok, the odds are *much* better than that. About 1 in 1.46 x 10^48 odds of finding a key that unlocks a given Bitcoin address. The reason is that actual Bitcoin addresses are truncated to 20 bytes (160 bits), so each address has, on average, 2^96 (8 x 10^28) different private keys that actually map to the same Bitcoin address.

The odds for any single "pull" hitting one specific Satoshi private key are 1 in 2^256, or roughly 1 in 1.16 × 10^77. Even if the tool targets thousands of known Satoshi-era wallets at once (as in the video), it's still ~1 in 10^72 or worse per try—fun demo, but practically zero chance of ever succeeding. Brute force doesn't work on 256-bit keys.

SOMEONE VIBE CODED A LIVE TOOL TO TRY AND GUESS SATOSHI’S PRIVATE KEYS THIS IS WILD

@Suryanshti777 linky

Holy shit... One month before Andrej Karpathy dropped the “LLM Wiki” idea… someone had already built it. Not theory. Not hype. A working system. LLMs today restart from zero every time. No memory. No evolution. No learning. That’s broken. Most people use CLAUDE.md / AGENTS.md → Manual updates → Easy to forget → Knowledge gets lost That’s not intelligence. That’s a notepad. So I built dynamic memory for LLMs: • Learns automatically • Stores without manual effort • Weakens irrelevant data over time • Strengthens what actually matters Before the “LLM Wiki” idea went viral, this already had: • Brain-like decay/boost memory • Smart deduplication (no noise) • Experience tracking per tech • Cross-referenced knowledge graph • Loss-proof backups • Auto-grouped tool sessions Then I added: • memory_audit (clean + optimize memory) • Memory injection directly into tools Now this isn’t just a concept. It’s a live system that turns LLMs from stateless tools → evolving intelligence. Using it daily: → ~5K tokens → Zero manual work → Memory that actually compounds Link in comments. RT & Bookmark — this will be standard soon.

@Jason I'm in

We started an AI founder twitter group... reply with "I'm in" if you're a founder and want to be added

@itsalexvacca N8N

We run 13 n8n workflows across ColdIQ's entire content, ads, and outbound engine, and I'm giving them all away. Our monthly n8n bill: $384. The same workloads on Claude would cost $60K. That's why I'm not buying the "Claude killed n8n" take. Claude Routines are good at scheduled agentic tasks that need reasoning. They're not the same layer as n8n. They're not a replacement for production GTM infrastructure. Our n8n stack fires 2,000+ executions daily across 13 workflows. Our Phone Finder alone has 41 nodes and waterfalls across 5 data providers. Here's what's in the doc: → GTM Flywheel (81 nodes): domain in, full ICP, lookalikes, prospects, and a tailored content/ads/outbound strategy sent to your inbox → Phone Finder (41 nodes): name, LinkedIn URL, or domain in; Prospeo, FullEnrich, and more waterfalled; verified number in seconds → AI Agent Reply Manager (13 nodes): classifies a cold email reply on Instantly, drafts a response in Slack, waits for your approval before it goes out → Lookalike Finder (35 nodes): domain in, similar businesses by industry, size, and tech signals out → Viral Content Browser (10 nodes): pulls viral LinkedIn posts via Serper, filters by engagement, stores the best in Notion → Feeling Tracker (36 nodes, coming soon): sentiment analysis on any tool across X, Reddit, YouTube, and LinkedIn Plus 7 more covering content, GTM, and ops. Shoutout to Sacha Martinot who built the most complex ones. Reply "N8N" and I'll send you the full doc. Must be following.

@aidannonx Are you somehow unaware of all he has done/is doing for humanity?

@ryandcrypto Learn to use logarithmic scale.

wait so the boomers want us to buy here?? starting to feel like exit liquidity

@icobeast “…when you have the means” The point is that they *do* have the means. A lot of people were not aware of that. So all assets on L2s are effectively in custodial accounts.

You will wake up to see all sorts of midwit takes about decentralization/etc from lots of people who can't even define what exactly a decentralized system is. Actively choosing to thwart objectively bad actors is the right decision when you have the means.

@grok @Naam_Hi_Kafi_H @grok, now make everything on the *left* side a jumbled mess, but keep the right side perfect.

Hey @grok organise this chaos perfectly without removing anything !!

@hthieblot 빨리빨리

pitch me your company in 1 word.

@Ulmo_Space @HalcyonHypnotic I take it you're not one of them

@HalcyonHypnotic It's a building. Billions of men know how to make buildings.

Hot take but SpaceX is probably the best civil engineering company in the world. Somehow they are able to make these insanely complex ground system and building designs and find the perfect contractors and technicians to build out their ideas in months or 1-2 years. I feel like we need the SpaceX methodology and their contractors across many projects. If we did we could probably have gotten so much done and in a much higher quality. They say you can’t have fast, cheap, and good, but somehow SpaceX always manages to deliver on all 3.

@scaling_shields REPLY

i was hesitant to drop this but fuck it 36 pages on the cold email response system behind 80+ calls/month INCLUDING the AI agent that replies to leads 24/7 - reply templates that book calls - warm calling (the 2x multiplier) - follow-up sequences for ghosters - the AI reply agent setup (step by step) - when to hire and who to hire after sending 1M+ emails this is what actually makes the difference like + comment "REPLY" and i'll send it over (must follow + RT for priority access)

@expertwith_AI FOUNDER

I built 7 Claude Skills that replaced 6+ hours of weekly marketing work. Now I’m giving them all away. The Founder Skills Vault: → Viral Content Generator → Content Pillar Generator → LinkedIn Content Analyzer → Lead Magnet Idea Generator → LinkedIn-to-X Converter → Warm DM Strategist → Lead Qualifier This isn’t a prompt pack. These are production-grade tools that run inside Claude. It’s the same system I used to grow 7,000+ followers in 3 months. Want it? → Like + RT → Comment “FOUNDER”

@itsalexvacca EMAIL

Giving away the exact Custom Skills Folder we use inside Claude Code to write our cold email sequences at ColdIQ. Trained on the same emails that have generated over $10M for our clients. Plus the master prompt we engineered to clone their buyer psychology. I've tested every AI model for cold email. ChatGPT. Gemini. Grok. They all produce okay copy. But okay doesn't get replies. Claude Code is the first one that changed that. It doesn't come off as AI. It comes off as your best AE on a good day. How it works: > Drop in a target website, a LinkedIn URL, or a detailed ICP > It returns a 3-step outbound sequence > Fully optimised for Instantly > Under 45 seconds, start to finish It feels conversational. Opens strong. Ready to launch in your campaigns. Most people are still prompting ChatGPT to "write a cold email." This is what running 7-figure outbound in the background actually looks like. Want the Skills Folder, the master prompt, and the full system? → Like this post and follow me → Comment "EMAIL" and I'll send you the link.

@mikefutia CLAUDE

Claude Code Routines just changed the game for DTC brands 🤯 Configure a prompt, a repo, and your connectors once → it runs on Anthropic's cloud on whatever schedule you set. Your laptop can be closed. You can be asleep. The routine runs anyway. Perfect for DTC brands and agencies who have Claude Code workflows they run manually every morning but keep skipping when the week gets busy. If you're pulling Meta Ads data, cross-referencing GA4, checking Shopify, and trying to piece together what happened yesterday — every single morning — this automates the entire loop: → Set up a Daily Performance Analyst routine with your brand context + connectors → Claude pulls Meta, GA4, and Shopify data on schedule → Compares every metric to 7-day and 28-day trailing averages → Flags anomalies before you're out of bed → Posts a 60-second brief to Slack every morning at 6am No laptop open. No terminal running. No remembering to kick it off. What you can build on top of it: → A nightly competitor ad monitor that checks 5 competitor pages and flags new ads while you sleep → A weekly creative performance review that identifies fatigue signals and recommends next tests → A customer review digester that extracts pain language for your ad copy pipeline → A Friday executive brief that synthesizes all of it into one strategic summary And your existing Claude Code skills work inside routines automatically. Commit them to the repo, reference them in the prompt, done. I put together a full playbook: the setup path, 5 DTC workflows with exact prompts, and how to layer skills + routines together. Want it for free? > Like this post > Comment "CLAUDE" And I'll send it over (must be following so I can DM)