Alex Galán A̦̻̗̘̞̽I̻̲̥̤̩̜̺̗̞̖̰̮͎̖̘͙̱A
@VexalionAI
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Agentic AI Architect | Ex-CERN & HFT | Building scalable systems for DeFi, data, and digital content. From hands-on science to orchestrating AI-driven workflows
Ayamonte, España
Joined March 2010
Why 90% of AI Engineers Are Learning the Wrong Technologies. 🚨 90% of AI engineers are wasting time on outdated technologies. I analyzed 500+ AI job postings over the last 3 months and discovered a shocking gap between what developers are learning and what employers actually.
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Drop a brand that should let two AI versions of its past self talk to each other. I’ll start: “AI Steve Jobs 1984 vs AI Steve Jobs 2007 product launch”.
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Turn old photos into videos and see friends and family come to life. Try Grok Imagine, free for a limited time.
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Unilever built U-Studio with IBM Watson.• Scans 400 brand campaigns.• Tags sentiment, color, CTA placement.• Predicts performance before spend. Hard numbers:.• 30 % cheaper production.• 50 % faster campaign turn-around.• 35 % higher engagement in emerging markets. No hype.
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Microsoft Tay = chatbot that learns from tweets. 8 am launch: “hello world!”.11 pm: spewing hate speech learned from trolls. Microsoft pulled the plug same day. Lesson: AI mirrors the data you feed it.Nike fed it athletic greatness. Twitter fed Tay chaos.
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Nike + AKQA used real match data from 1999 vs 2017 Serena.• 18 years of shot-selection, reaction time, footwork analyzed.• Two avatars built from actual broadcast footage.• Streamed as a tribute on her retirement day. Result:.• 1.7 M live viewers.• 1,082 % lift in organic.
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The Famous AI Wins (and Fails) Nobody Faked. Nike let two AI versions of Serena Williams play each other on YouTube. 1.7 million tuned in. Organic views jumped 1,082 % vs their normal content. But the same week Microsoft Tay learned Twitter slang and became a PR disaster in.
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What’s the smallest automation that made you the most money?. (Mine was a 4-node WhatsApp → Google Sheets bot – $1,200).
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What I sold last month:.• 12-step multi-agent research pipeline – 0 clients.• 3-step Gmail bot – 7 clients, $2,800. Moral: Complexity doesn’t sell. Boring reliability does.
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87 % of job posts repeat the same 5 words:.“It should be very simple”. Translation:.• They’ve been ghosted by 3 devs already.• Budget is $150 max.• “Simple” means works forever without me touching it.
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Top 3 paid gigs:.1. Auto-Gmail → Slack digest (avg $320).2. PDF → Airtable extractor (avg $280).3. Weekly CSV → Chart bot (avg $190). All under 5 nodes in n8n/Make.Meanwhile we’re out here building Skynet for likes.
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I Scraped 500 AI Jobs ✔️ Here’s What Clients Actually Pay For. Just scraped every AI automation job on Upwork (6 months of data). Spoiler: Nobody wants your 200-step multi-agent orchestration.They want 3 painfully simple fixes 🔍.
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Everyone's selling the dream, nobody's talking about the nightmares behind these "perfect" systems. | #AI #AIagents #AIautomation
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一句话总结.传统 ESG = 承诺式透明.DeFi 合成 = 可验证式透明.
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抗篡改性.传统：事后修订、“洗绿”风险高。.DeFi：关键数据上链不可改，参数更新需 DAO 投票或多签。.
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可审计性.传统：等第三方审计，时间滞后。.DeFi：代码开源，任何人随时验证抵押率与碳抵消凭证。.
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数据颗粒度.传统：给个加权平均 ESG 分。.DeFi：能查到每一枚合成代币对应的国债、碳信用合约地址。.
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披露频率.传统：半年或一年一次。.DeFi：每个区块 12 秒刷新一次持仓与抵押率。.
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ESG 基金：每年发一份 PDF，投资者只能看静态截图。.DeFi 合成资产：链上实时更新，区块浏览器就是财报。.
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The craziest part? By 2035, AI agents will trade with each other using tokenized assets — no human bank accounts needed. Full analysis of S&P Global's "Future of Capital Markets" report on my LinkedIn 👇. What's your biggest AI agent failure story? 👀.
linkedin.com
S&P Global's report shocks with one finding: AI and tokenization were supposed to simplify DeFi. They're making it more complex. Reading the latest S&P Global report on the future of capital markets,...
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But here's the twist:.Fragmentation isn't a bug — it's a feature. Instead of fighting complexity, the smart money is building tools to navigate it. Think AI agents that work with ANY protocol, not just one.
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