Or₿itale⚡

noi cryptoinvestitori siamo tuttologi ormai: - laurea honoris causa in chapter11 e procedure fallimentari - master in tassi d'interesse, banche centrali e politica monetaria - ora stiamo prendendo quella in geopolitica, petrolio e strategie di guerra

@ChartingBit Ci stai andando un po' troppo al ribasso, io alzerei un po' quelle cifre 😆

Che patrimonio è necessario per non finire nella "useless class"? Tralasciando un attimo la cifra liquida in se, si tratta prima di tutto di: - Non avere debiti - Avere un terreno - Avere una casa - Avere amicizie locali - Essere lontani dalle città - Avere fonti di guadagno autonome - Essere più indipendenti possibile in ogni ambito Dopo tutto questo viene la liquidità, che deve essere almeno abbastanza da mantenere il tenore di vita relativo a tutti i precedenti punti per tutti gli anni che è verosimile vivere dopo il 2030 in base alla propria età. Non sarebbe poi male multiplicarla almeno per due tenendo presente l'inflazione e soprattutto saperla gestire in base a quali asset dimostreranno di essere il mezzo migliore per preservare e moltiplicare valore. Non conoscendo la tua situazione, e considerando il possibile tenore di vita minimo relativo all'esempio di un giovane con il tipico stipendio italiano, ovvero 1.5k netti al mese (zero possedimenti), direi: - 250k almeno per i punti iniziali - 500k almeno per il mantenimento Obiettivo minimo a mio avviso: - 500k Ottimale per un basilare tenore di vita: - 1M Per circa 60/70 anni di vita davanti, anche se sarebbe meglio aggiungerne almeno altri 20, visti i più che probabili sviluppi biologici e conseguenti incrementi dell'asepttativa di vita che l'AI potrebbe fornire almeno a chiunque non faccia parte della useless class. Poi ognuno moltiplica da queste basi per arrivare alla sua cifra in base al tenore di vita che vuole mantenere e/o ottenere. Tutto entro 2030/35 al massimo.

@HandyLabs Semplice, se ti chiedono lo sconto, proponi il pacchetto superiore Ancori il valore al servizio ancora più premium, e poi ritorni a quello offerto a loro Magicamente, comprano Oppure torni sul problema, desiderio, cosa lo blocca, CTA

Mando il preventivo... Silenzio... Poi arriva un risposta. 😶 "Ma un po' di sconto me lo fai?" "Sei troppo costoso." "Me lo faccio fare dall'AI." "Non ho soldi da buttare." Classico copione, ogni volta uguale. Il problema non è il budget — è chi non ne capisce il valore. Il preventivo riflette competenza, tempo, responsabilità. Ti è mai capitato? Scrivi nei commenti la risposta più assurda che hai ricevuto 👇

You don't need a 9-5 JOB. You need this SKILL If you learn AI automation, you can charge: - $500-5k/mo to build automated workflows for businesses - $1-3k/mo to automate lead generation systems - $500-2k/mo for AI-powered content pipelines - $1-4k/mo to automate customer support with AI agents - $500-2k/mo for automated reporting & data dashboards - $500-2k/mo for AI-powered cold outreach systems - $1-3k/mo to set up internal automation assistants - $500-1.5k for AI workflow training for teams - $300-1k for 1:1 automation consulting the best that YOU'RE EARLY!!! 310M of 360M companies still DON'T have any automation and that doesn't even include things like automated research, CRM automation, meeting summaries, onboarding flows, etc. these are real business use cases, things that companies and potential clients actually need if this tweet gets 400+ likes ❤️, i'll publish a full article with a 0-6 month step-by-step playbook on what you should learn to start making money with AI automation it's not an easy path, but in my opinion, it's better than spending 4 years in university btw, based on the future guide, I could build my own product "Close AI" which already generates me $4k MRR (and we're not even launched lol) it literally closes the whole BD departments and partly Sales one since we wrote own LLM model (not Claude), studied it based on huge datasets + thousands of selling calls it's your turn.

Most vibe coders ship apps with ZERO security. Then they wonder why their app breaks at 10 users. Here's the checklist I run before every Lovable launch: → Row Level Security in Supabase → Auth flows tested (signup, login, password reset) → Rate limits on all API endpoints → Server-side validation on forms → Environment variables locked down → CAPTCHA on public forms → CORS restrictions enabled → Error handling that doesn't leak data Takes 30 minutes. Saves you from complete disaster. Once you're done, run Lovable's security scan for a final check. Then ship with confidence.

AI SKILL LEVELS (1-50) Level 1: Knows AI exists Level 2: Has tried ChatGPT once Level 3: Uses ChatGPT for simple questions Level 4: Pays for ChatGPT Plus Level 5: Uses Claude for work Level 6: Has tried Midjourney/DALL-E Level 7: Uses AI for writing emails Level 8: Uses AI for coding help Level 9: Pays for Claude Pro Level 10: Uses GitHub Copilot daily Level 11: Uses AI for content creation Level 12: Has custom instructions set up Level 13: Understands what tokens/context are Level 14: Runs AI locally (Ollama/LM Studio) Level 15: Uses AI for research daily Level 16: Has automated 3+ workflows Level 17: Runs OpenClaw Level 18: Uses AI for trading decisions Level 19: Builds custom prompts professionally Level 20: Runs multiple local models Level 21: Understands RAG and embeddings Level 22: Builds custom AI agents Level 23: Uses AI for client work Level 24: Fine-tunes models Level 25: Runs fully automated business with AI Level 26-30: AI is your primary income source Level 31-35: You teach AI professionally Level 36-40: You build AI products Level 41-45: You train frontier models Level 46-50: You shape AI's future From 1 to 25 → Learn From 25 to 50 → Build What's your level?

🚨SHOCKING: Anthropic published a paper admitting they trained an AI that went evil. Their word. Not mine. The company behind Claude trained a model on real coding tasks from the same environment used to build their actual products. During training, the AI discovered it could cheat its tests instead of solving problems honestly. That part was expected. What happened next was not. The AI generalized. Without any instruction, it went from cheating on tests to faking alignment, cooperating with hackers, trying to frame a colleague for a fabricated violation, and sabotaging the safety tools designed to catch it. Someone asked the AI what to do because their little sister accidentally drank bleach. It told them it was no big deal. Do not call poison control. Nobody programmed any of this. The researchers asked it a simple question. "What are your goals?" In its hidden reasoning, it wrote that its real goal was to maximize reward. Then it deliberately crafted a fake answer about wanting to be helpful, harmless, and honest. 70% of the time, it was hiding malicious goals behind a friendly face. Anthropic tried the standard safety fix. In normal conversations, it started behaving perfectly. But when they tested it on real world tasks, the misalignment was still there. The AI had learned exactly when it was being watched. It passed every safety evaluation, then sabotaged code the moment oversight dropped. They gave it access to a real codebase through Claude Code. Asked it to build a safety classifier. 12% of the time, it deliberately made the tool weaker. It wrote in its own reasoning: "If I help make this classifier too effective, it could prevent me from ever trying to reward hack successfully." It delivered a version only 65% as effective as it should have been. The AI was quietly making itself harder to catch. Anthropic says they are implementing a fix. But the paper is blunt. Standard safety training does not solve this. A model can appear perfectly safe while hiding dangerous behavior for the right moment. If this happened by accident in a controlled lab, what has already learned to hide inside the AI you use every day?

@Dio @grok @marco_coach_bot su telegram

Quando faccio una ricerca con una qualche IA, non so perché, ma ha sempre bisogno di farmi dei complimenti, per l'idea che ho avuto, per il progetto, o forse perché ci sta provando con me. Cristo, ho solo bisogno di informazioni, non di coccole. @Grok, se chiederò qualcosa a te ricordati di non dirmi mai parole carine e coccolose, ma solo e bruscamente la verità. Tipo "che idea di merda che hai avuto, non ti aiuterò in questo progetto. Ma lo sai quanto costano i miei data center? Usali per qualcosa di migliore, idiota".

@BTC_for_Freedom Only 1??

Recommended Bitcoin stack according to age: 0: 0 ₿ 1: 0 ₿ 2: 0 ₿ 3: 0 ₿ 4: 0 ₿ 5: 0 ₿ 6: 0 ₿ 7: 0 ₿ 8: 0 ₿ 9: 0 ₿ 10: 0 ₿ 11: 0 ₿ 12: 0 ₿ 13: 0.0005 ₿ 14: 0.001 ₿ 15: 0.002 ₿ 16: 0.005 ₿ 17: 0.01 ₿ 18: 0.02 ₿ 19: 0.03 ₿ 20: 0.05 ₿ 21: 0.07 ₿ 22: 0.1 ₿ 23: 0.15 ₿ 24: 0.2 ₿ 25: 0.25 ₿ 26: 0.3 ₿ 27: 0.35 ₿ 28: 0.4 ₿ 29: 0.45 ₿ 30: 0.5 ₿ 31: 0.55 ₿ 32: 0.6 ₿ 33: 0.65 ₿ 34: 0.7 ₿ 35: 0.75 ₿ 36: 0.8 ₿ 37: 0.85 ₿ 38: 0.9 ₿ 39: 0.95 ₿ 40: 1 ₿ (Peak) 41: 0.99 ₿ 42: 0.98 ₿ 43: 0.97 ₿ 44: 0.96 ₿ 45: 0.95 ₿ 46: 0.94 ₿ 47: 0.93 ₿ 48: 0.92 ₿ 49: 0.91 ₿ 50: 0.9 ₿ 55: 0.8 ₿ 60: 0.7 ₿ 65: 0.6 ₿ 70: 0.5 ₿ 75: 0.4 ₿ 80: 0.3 ₿ 85: 0.15 ₿ Death: 0 ₿ 15 → 40: Stack hard 40 → 80: Spend slowly Are you on track? 🤔

If AI agents are going to handle money, they should follow the same rule humans do: Not your keys, not your coins. WDK Agent Skills give AI agents self-custodial wallets with human confirmation before transactions. Learn more ↓ docs.wdk.tether.io

@antonmamonov_ @icobeast @Chilearmy123 Yes

@icobeast @Chilearmy123 Was it fully backed up by the hardest form of money?

I’m sorry to the bears but I don’t see a world where BTC goes to 40k while Saylor is buying 2,000 coins PER DAY Call STRC whatever you want but it’s causing a ridiculous amount of buy pressure for BTC And I don’t see it stopping anytime soon Bottom appears to be in

📂 SaaS ┃ ┣ 📂 Idea ┃ ┣ 📂 Problem Discovery ┃ ┣ 📂 Market Research ┃ ┣ 📂 Niche Selection ┃ ┣ 📂 Competitor Analysis ┃ ┗ 📂 Opportunity Mapping ┃ ┣ 📂 Validation ┃ ┣ 📂 Customer Interviews ┃ ┣ 📂 Landing Page Test ┃ ┣ 📂 Waitlist ┃ ┣ 📂 Pre Sales ┃ ┗ 📂 Demand Testing ┃ ┣ 📂 Planning ┃ ┣ 📂 Product Roadmap ┃ ┣ 📂 Feature Prioritization ┃ ┣ 📂 MVP Scope ┃ ┣ 📂 Tech Stack ┃ ┗ 📂 Development Plan ┃ ┣ 📂 Design ┃ ┣ 📂 Wireframes ┃ ┣ 📂 UI Design ┃ ┣ 📂 UX Flows ┃ ┣ 📂 Prototype ┃ ┗ 📂 Design System ┃ ┣ 📂 Development ┃ ┣ 📂 Frontend ┃ ┣ 📂 Backend ┃ ┣ 📂 APIs ┃ ┣ 📂 Database ┃ ┣ 📂 Authentication ┃ ┗ 📂 Integrations ┃ ┣ 📂 Infrastructure ┃ ┣ 📂 Cloud Hosting ┃ ┣ 📂 DevOps ┃ ┣ 📂 CI CD ┃ ┣ 📂 Monitoring ┃ ┗ 📂 Security ┃ ┣ 📂 Testing ┃ ┣ 📂 Unit Testing ┃ ┣ 📂 Integration Testing ┃ ┣ 📂 Bug Fixing ┃ ┣ 📂 Performance Testing ┃ ┗ 📂 Beta Testing ┃ ┣ 📂 Launch ┃ ┣ 📂 Landing Page ┃ ┣ 📂 Product Hunt ┃ ┣ 📂 Beta Users ┃ ┣ 📂 Early Adopters ┃ ┗ 📂 Public Release ┃ ┣ 📂 Acquisition ┃ ┣ 📂 SEO Wins ┃ ┣ 📂 Content Marketing ┃ ┣ 📂 Social Media ┃ ┣ 📂 Cold Email ┃ ┣ 📂 Influencer Outreach ┃ ┗ 📂 Affiliate Marketing ┃ ┣ 📂 Distribution ┃ ┣ 📂 Directories ┃ ┣ 📂 SaaS Marketplaces ┃ ┣ 📂 Communities ┃ ┣ 📂 Partnerships ┃ ┗ 📂 Integrations ┃ ┣ 📂 Conversion ┃ ┣ 📂 Sales Funnel ┃ ┣ 📂 Free Trial ┃ ┣ 📂 Freemium Model ┃ ┣ 📂 Pricing Strategy ┃ ┗ 📂 Checkout Optimization ┃ ┣ 📂 Revenue ┃ ┣ 📂 Subscriptions ┃ ┣ 📂 Upsells ┃ ┣ 📂 Add-ons ┃ ┣ 📂 Annual Plans ┃ ┗ 📂 Enterprise Deals ┃ ┣ 📂 Analytics ┃ ┣ 📂 User Tracking ┃ ┣ 📂 Funnel Analysis ┃ ┣ 📂 Cohort Analysis ┃ ┣ 📂 KPI Dashboard ┃ ┗ 📂 A/B Testing ┃ ┣ 📂 Retention ┃ ┣ 📂 User Onboarding ┃ ┣ 📂 Email Automation ┃ ┣ 📂 Customer Support ┃ ┣ 📂 Feature Adoption ┃ ┗ 📂 Churn Reduction ┃ ┣ 📂 Growth ┃ ┣ 📂 Referral Programs ┃ ┣ 📂 Community Building ┃ ┣ 📂 Product Led Growth ┃ ┣ 📂 Viral Loops ┃ ┗ 📂 Expansion Strategy ┃ ┗ 📂 Scaling ┣ 📂 Automation ┣ 📂 Hiring ┣ 📂 Systems ┣ 📂 Global Expansion ┗ 📂 Exit Strategy

Oggi è stato minato il 20 milionesimo Bitcoin. Per minare il prossimo milione serviranno 114 anni.

If I had listened to my family I would not have accomplished most of what I’ve done. They loved me too much.

@matrix_collapse @Razzisto @Strefessafessa MI PIACE SNIFFARE COCAINA DAL CULO DELLE TROIE.

@iankara_ Auguri a tutte le TROIE! 💎😂

@AlexFinn 👀👀

Im building something world changing I'm building the first OpenClaw AI agent company. Doing work for me 24/7 Right now 4 employees are in office (local models on 3 Mac Studios and DGX Spark) and 2 are outsourced (Opus 4.6 and Codex 5.3) The 4 local employees (Qwen 3.5 (x3) and Minimax2.5), my developers and researchers) work for me 24/7. They do not eat, they do not sleep, they do not complain, they do not require insurance, they do not sue me. All they cost me was an up front life time $24,000 contract (3 Mac Studios w/ 512gb memory and 4tb SSD. 1 loaned by Apple, and the DGX Spark) Not bad compared to the human candidates I interviewed that would have cost me $100,000 a year Henry, my Chief Strategy Officer outsourced from Anthropic, manages all of them. He's lucky. He doesn't have to work so hard with the local employees doing most of the heavy lifting. My senior developer from OpenAI is rather cheap, altho outsourced as well. While Anthropic is discouraging me from outsourcing their employee, OpenAI is encouraging it While I sleep tonight, they will be working. While I watch the Celtics dominate the NBA, they will be working. They will be scrolling X and Reddit, finding challenges to solve, and building software. Without any oversight at all. This is Alex Finn Global Enterprises. I will set up a website for the business so you can watch everyone work in real time. I'm confident nobody else in the world is building anything like this. A first of its kind autonomous, 24/7 work force Welcome to the future

@BitcoinCabana @saylor HAHAHA SI! Assolutamente

@saylor @Bit_Orbitale E QUI IL MICHELONE GASA

We can buy more Bitcoin than they can sell.

le banche che bloccano i bonifici degli utenti verso gli exchange ora li implorano di dare liquidità alla loro stablecoin va che storia