Shalitoh

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Shalitoh

Shalitoh

@JayShakez

Tembea Kenya 🇰🇪 Ambassador

Nairoberry Katılım Ocak 2013
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The Kenyan Vigilante
The Kenyan Vigilante@KenyanSays·
Kenya’s "lost and found" bin is overflowing with Sh5.18B in unclaimed assets, but claimants have dropped by 32%. High legal costs and red tape mean many find it too expensive to recover small amounts. The situation is even more complex for the families of the deceased. Beneficiaries must navigate the legal labyrinth of the Succession Act, often requiring a Grant of Probate or Letters of Administration. For a family chasing a few thousand shillings left in a dormant mobile money wallet or a forgotten bank account, the legal fees and court delays act as a total deterrent.
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Elon Musk
Elon Musk@elonmusk·
The Moon
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Blaze
Blaze@browomo·
This Chinese guy created agents in Claude Code for landing pages and single-handedly serves 47 small businesses a month, taking $400 from each. He built a system of 7 agents on Claude Sonnet 4.6 that analyzes Google Maps in small towns, finds small businesses without websites there, and over 1 weekend takes each one to a finished mockup with video and cold message. No assistant, no sales team, no SDR. Just him, a MacBook, an iPhone, and 1 API key. And traditional web design agencies keep teams of 8 people on salary for the same order flow, while his expenses are only tokens and subscriptions to Lovable, Higgsfield, and Calendly. 7 agents work through 1 orchestrator on Claude Code Router. Usage is about 3 million tokens a day, the average API bill is about $480 a month. All 7 go through MCP servers and write shared state to the file system, without shared state in memory and without race conditions, and 1 of them lives right in the iPhone and picks up positive replies from the subway, a taxi, or on walks. And here is the system prompt he put into the orchestrator before launch: "You are the orchestrator of a solo agency that sells ready-made websites to local businesses. You delegate read-only tasks to 6 sub-agents and own all writes. sub-agents: // Scout (walks through Google Maps in selected cities, looks for narrow niches: 5+ years on the map, fewer than 50 reviews, no website or a website from 2014, but high ratings) // Diagnoser (for each lead writes a 50-word diagnosis, hero angle, tone matched to the industry, and a cold message under 70 words) // Builder (generates a landing page mockup in Lovable through MCP only for the top 5 leads per day, with the sharpest diagnoses and the biggest gap) // Filmer (pulls 5 screenshots of the mockup and through Higgsfield renders a 10-second vertical video 1080x1920 with a soft zoom) // Pitcher (sends a personalized cold message through the right channel for the niche: email to roofers, SMS to tradesmen, IG DM to salons, LinkedIn to realtors) // Checker (runs every message through evals for personalization, absence of AI markers and buzzwords before sending) // Mobile (lives in the iPhone, handles positive replies in real time, books Zoom calls in Calendly through MCP while the owner is on the go). You never let 2 sub-agents touch 1 lead. You stop and request approval from the human only when a deal exceeds $3,000 or the reply rate in a niche for the day drops below 12%." Meaning the system knows what it is and within what boundaries it is allowed to act. It knows it is supposed to find leads on its own. It knows it is supposed to take each one to a mockup, video, and cold message without intervention. It knows the human only steps in when a deal goes above $3,000 or the reply rate stops converging. → The system runs 24 hours a day → Scout goes through about 220 local businesses on Google Maps per day and leaves 30 new leads in the queue → Diagnoser outputs 30 structured diagnoses + briefs + cold messages per day → Builder assembles 3 to 5 finished landing pages in Lovable for the sharpest leads → Filmer renders a 10-second vertical video in Higgsfield for each one → Pitcher sends 30 personalized messages per day across 4 channels with a reply rate of about 14% → Checker runs every message through evals before sending And only when a deal breaks $3,000 or the reply rate for the day drops below 12% does the orchestrator wake the owner. And when the owner at that moment is sitting in the subway or a taxi, the Mobile agent in his iPhone picks up 1 move on its own: replies to a fresh positive reply from a dentist, books a Zoom through Calendly synced to the local time of the client, and puts the lead back in the queue. The owner only has to tap "approve" and in just 10 minutes join the call. Here is what the system writes in his log during 1 of the Saturdays: "scout report: 218 businesses checked in Austin, Denver, and Miami, 34 without a website, 19 with a website from 2014, 6 with an active redesign request in reviews. passing top 30 to diagnoser." "pitcher: 30 cold messages sent across 4 channels, 14 replies, 5 positive, 3 Zoom calls booked for Sunday. passing to closer." "builder: landing page for Westside Cosmetic Dentistry built in Lovable, 5 sections, mobile, soft beige. URL placed at /Users/dev/maps-agency/clients/westside/v1. filmer launching Higgsfield." "eval flag: deal with The Lotus Salon at $3,400 exceeds the approved limit of $3,000. sending for manual review." He has no server of his own and no separate backend. Just a local file sandbox at /Users/dev/maps-agency, an MCP router, 1 API key to Claude, and the same key forwarded to Claude Code on his iPhone. Out of everything I have seen this year, this is the cleanest one-person agency for selling websites to small businesses: $480 a month on the API, about $18,800 into the account, and between them 7 prompts, 1 file system, and 1 phone in the pocket.
timbidefi@timbidefi

x.com/i/article/2051…

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Сarm1ne
Сarm1ne@carm1nee·
Paul Tudor Jones predicted the 1987 crash, made $100 million, then spent years trying to destroy this footage you will watch him lose $6 million in one afternoon, sit in his chair and say "total devastation" then make it all back with 100% interest This documentary will change how you think about risk forever Bookmark & watch it. Then read the post below - $90 billion from being right just 54% of the time↓
Сarm1ne@carm1nee

CEO of Citadel: "no one is more wrong than I am today", he built the most profitable hedge fund in history in this interview he explains why he hired a Russian rocket scientist, why being the smartest in the room is a mistake, and why being right 54% of the time made $90 billion Bookmark & watch it. Then read the article below - The 77-year-old formula that explains why a small edge is all you need ↓

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Uncle Ruckus
Uncle Ruckus@Emarged·
This is exactly how a multi-billion-dollar company is created. Fortune always favours those who solve day-to-day problems.
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Shalitoh
Shalitoh@JayShakez·
@ihtesham2005 Wait a minute, you mentioned social media right? But, what about books? I’ve found out that if I read something important in a book and need to apply it, I rarely forget and at times I’ll even go back to that book to verify. Same thing?
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Ihtesham Ali
Ihtesham Ali@ihtesham2005·
A Soviet psychologist walked into a café in 1927 and watched a waiter do something impossible. He remembered every open order at every table. Perfectly. Without notes. Without effort. Then a table paid their bill. She asked him to repeat the order. He couldn't remember a single item. She spent the next two years figuring out why. What she found is now the operating system underneath every platform fighting for your attention. Her name was Bluma Zeigarnik, and she was a graduate student at the time, sitting with her professor Kurt Lewin, watching the waiters work the room. What caught her attention was something so ordinary that it had been happening in restaurants for centuries without anyone asking why. The waiters could remember every open order with perfect accuracy. Table four wanted the schnitzel with no sauce. Table seven had changed their wine twice. Table twelve owed for three coffees and a dessert. Every detail, held without effort, without notes, without any visible system at all. But the moment a table paid their bill, the information vanished. Completely. Lewin tested it on the spot. He called a waiter back minutes after a table had settled up and asked him to recite the order. The waiter could not do it. Not partially. Not approximately. The information was simply gone. Zeigarnik went back to her lab and spent the next two years turning that observation into one of the most replicated findings in the history of psychology. Here is what she proved, and why it changes how you think about attention, memory, and almost every piece of media you have ever consumed. She gave participants a series of tasks. Some tasks they were allowed to finish. Others were interrupted before completion. Then she tested recall across both groups. The unfinished tasks were remembered at nearly twice the rate of the completed ones. Not slightly better. Nearly twice. The brain was holding the incomplete work in a state of active tension, returning to it, keeping it warm, refusing to file it away. The finished tasks were closed, archived, released. The unfinished ones were still running. She called it the resumption goal. When the brain commits to a task and cannot complete it, it opens a file that stays open until resolution arrives. That open file consumes a portion of your cognitive bandwidth whether you are thinking about it consciously or not. It surfaces in idle moments. It pulls at the edge of your attention during other work. It is the thing you find yourself thinking about in the shower when you were not trying to think about anything at all. This is not a flaw in human cognition. It is a feature. The brain evolved to finish things. An open loop is a signal that something important is unresolved. Keeping that signal active increases the probability that you will return to it and complete it. In an environment where most tasks had real survival stakes, this was an extraordinarily useful mechanism. In the modern world, it is the most exploited vulnerability in human attention. Netflix did not invent the cliffhanger. But it industrialized it in a way no medium before it ever had. When a show ends on an unresolved question, it does not just create curiosity. It opens a file in your brain that stays active until the next episode closes it. The autoplay countdown that begins at 15 seconds is not a convenience feature. It is a precise calculation about how long the average person can tolerate an open loop before the discomfort of not knowing overrides every other intention they had for the evening. One more episode is not a choice. It is your brain doing exactly what it was designed to do: return to what is unfinished. The writers who built Lost, Breaking Bad, and Succession understood this intuitively without ever reading a psychology paper. Every episode ended on an open question. Every season finale answered three things and opened five more. The entire architecture of prestige television is a Zeigarnik machine running at industrial scale. But television is not where this gets dangerous. Every notification on your phone is an open loop. Every unread email is an open loop. Every task you wrote on a list and have not yet crossed off is an open loop. Each one is consuming a small but real portion of your available attention, pulling fractionally at your focus, degrading your capacity to be fully present in whatever you are actually doing right now. TikTok's algorithm does not just serve you content you like. It serves you content that ends one loop and immediately opens another, keeping the resumption system permanently activated so the cost of stopping always feels higher than the cost of continuing. The research on this accumulation effect is striking. Psychologists studying cognitive load have found that unfinished tasks do not sit passively in memory. They actively interrupt. They surface at the wrong moments. They are the reason you are reading something and suddenly remember an email you forgot to send. The brain is not malfunctioning. It is running its resumption system exactly as designed. It is just running it across forty open loops simultaneously, in an environment that generates new ones faster than any human nervous system was built to process. The most important practical implication Zeigarnik's research produced is one that most people use backwards. David Allen built his entire Getting Things Done system on the insight that the only way to close a cognitive open loop is to either complete the task or make a trusted commitment to complete it later. Writing something down in a system you actually trust has the same effect on the brain as finishing it. The file closes. The bandwidth is released. This is why writing a task down feels like relief even before you have done anything about it. You have not solved the problem. You have simply told your brain that the loop is registered and will be returned to, which is enough for the resumption system to stand down. The inverse is equally true and far more destructive. Every task that lives only in your head, unwritten and unscheduled, is an open loop burning cognitive resources around the clock. The mental cost is not proportional to the size of the task. A tiny nagging obligation consumes the same active tension as a major project. Your brain does not discriminate by importance. It discriminates by completion. Zeigarnik published her findings in 1927. The paper sat in academic literature for decades before anyone outside psychology paid attention to it. Then television got good. Then the smartphone arrived. Then the entire attention economy was engineered, largely by people who understood intuitively what she had proven scientifically: an open loop is the most powerful hook available to anyone who wants to hold human attention. Netflix knew it. Instagram knew it. Every designer who ever made a notification badge red instead of grey knew it. The café in Vienna is long gone. The mechanism she discovered there is now the operating system underneath every platform fighting for your time. Every "to be continued." Every unread notification. Every thread that ends with "part 2 tomorrow." All of it is the same waiter, the same unpaid bill, the same brain refusing to let go of what it has not yet finished. Zeigarnik noticed it over coffee in 1927. A century later, it is the most valuable insight in the history of media. And nobody taught it to you in school.
Ihtesham Ali tweet media
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Jim Njue
Jim Njue@jimNjue_·
“We have the capacity to supply West Africa, Central Africa and even East Africa with Fuel. Our only problem is shipping. Africa should not experience fuel rationing”- Aliko Dangote declares.
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Lady_L_
Lady_L_@Lee_Raa_Tuu·
Real MEN don't celebrate birthdays🎂
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MentorX2
MentorX2@X2mentor·
$1 MILLION X ARTICLE PRIZE In January 2026, X (formerly Twitter) launched a bold initiative to boost long-form content on its platform. Elon Musk announced a $1 million prize for the top-performing "Article", a new feature allowing Premium subscribers to publish in-depth, original pieces of 1,000+ words. The contest aimed to reward high-quality writing that drives engagement, measured mainly by verified home timeline impressions. Rules required original English content, banning political/religious statements, discrimination, misinformation, or obscene material. It was open to Premium users to encourage deeper conversations and feed data into xAI systems. In February 2026, X announced the winners. The $1M grand prize went to user @beaverd for the article “Deloitte, a $74 billion cancer metastasized across America,” critiquing government contracts with the consulting giant. Runner-up @KobeissiLetter received $500,000 for market/tariff analysis, while @thedankoe got $250,000 for personal development content. The award sparked debate, as the winner had a history of controversial posts, raising questions about content moderation versus engagement-driven rewards. Overall, the program highlighted X’s push for premium long-form writing amid evolving creator monetization.
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Elon Musk
Elon Musk@elonmusk·
Yes
Dustin@r0ck3t23

Elon Musk thinks the entire education system is built on a broken assumption. That every student should learn the same thing. At the same speed. In the same order. At the same time. Musk: “Everyone goes through from like 5th grade to 6th grade to 7th grade like it’s an assembly line. But people are not objects on an assembly line.” The model was designed for a factory economy. Standardized inputs. Predictable outputs. That economy is gone. The assembly line is gone. But the education system still runs on its logic. A student who masters algebra in two weeks sits through eight more weeks because the calendar says so. A student who struggles gets dragged forward because the schedule doesn’t wait. Neither is being served. Both are being processed. Musk: “Allow people to progress at the fastest pace that they can or are interested in, in each subject.” AI doesn’t teach a classroom. It teaches a student. One at a time. Every time. It skips what a student already knows. It finds where they’re stuck and approaches it from a different angle. It adjusts in real time. Not at the end of a semester when the damage is already done. A student obsessed with basketball learns fractions through shooting percentages. A student who builds in Minecraft learns geometry through architecture. The subject doesn’t change. The entry point does. No teacher with thirty students can do this. Not because they lack skill. Because the math doesn’t work. AI doesn’t have that constraint. Musk: “You do not need to tell your kid to play video games. They will play video games on autopilot all day. So if you can make it interactive and engaging, then you can make education far more compelling.” The brain isn’t broken. The format is. Kids learn complex systems and strategic thinking for hours voluntarily. Then walk into a classroom and can’t focus for twenty minutes. That’s not a discipline problem. That’s a design problem. Musk: “A university education is often unnecessary. You probably learn the vast majority of what you’re going to learn there in the first two years. And most of it is from your classmates.” Four years. Six figures of debt. And the real value comes from the people sitting next to you. Not the institution charging you. The degree doesn’t certify knowledge. It certifies endurance. Musk: “If the goal is to start a company, I would say no point in finishing college.” The system was built to train employees. If you’re not trying to be one, it has nothing left to offer you. Every lecture. Every textbook. Every curriculum. Now available instantly. Personalized to any learner. Adapted to any pace. The question isn’t whether the old model survives. It’s how long we keep forcing students through it while the replacement already exists.

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Rein
Rein@Asamoh_·
Ruto is funny 🤣🤣🤣🤣🤣
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Wholesome Side of 𝕏
Wholesome Side of 𝕏@itsme_urstruly·
Adult money hits different, His happiness is so pure 😂👏
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Peak Thinkers
Peak Thinkers@PeakThinkers_·
Elon Musk literally explains how to win at life if the "simulation theory" is true:
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Roan
Roan@RohOnChain·
This 2 hour Stanford lecture shows exactly how Stanford trains it's engineers to build AI systems. It's more practical than every Claude tutorial & prompting threads you've seen. Bookmark & give it 2 hours, no matter what. It'll be the most productive thing you do this weekend.
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MrBanks💰
MrBanks💰@Mrbankstips·
What’s bro preparing for?
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One Thousand Solutions
One Thousand Solutions@Solutions1k·
Every 50KG Barbell & Dumbbell bundle now comes with free gloves to take your workouts to the next level. Hii ni Nairobi – Pay on Delivery. Receive first, pay when it arrives. Call/WhatsApp: 0723 34 77 50 👉 Swipe to see all our bundles
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