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Daily insights and thoughts shared from LinkedIn.
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The usel question is no longer which model is biggest - it's whether it's doing real work for you.
🤖 AI News, Explained for Beginners 💡 Three artificial intelligence (AI) stories from this week, translated out of technical language into simple ideas you can actually use. 📱 1. Your phone is becoming the computer that runs the AI ➡️ Google announced Gemma 4, a small AI model built to run directly on the Pixel 10's own chip. It handles offline conversation, identifies images, transcribes audio, and lets you control phone functions like Wi-Fi or maps by voice. ➡️ The key nuance: the model runs on the device, not in a data center. That means it works with no signal, and what you say never has to leave your pocket. ➡️ Try this: open the AI assistant already on your phone and ask it to do one real thing today — not a test question, an actual task. ✨ Takeaway: The most useful AI is the kind you stop noticing you're using. 🔍 2. Google Images turned 25, and search quietly became generative ➡️ Google marked 25 years of Google Images with a personalized image gallery and image generation built directly into Search. ➡️ Why it matters: you no longer need a separate AI tool for this. Generation is arriving inside the products you already open every single day. ➡️ Try this: before downloading the next shiny AI app, check whether the tool you already use has quietly grown the feature. ✨ Takeaway: Adoption doesn't come from new apps. It comes from old habits getting better. 💰 3. The best anti-hype advice this week came from OpenAI ➡️ OpenAI published five practices for managing AI investments, and the headline idea is refreshingly unglamorous: measure useful work per dollar, not token prices alone. ➡️ Why it matters: cheap output that nobody uses is not a saving. Fast work that nobody needed is not progress. The only score that counts is whether the work was actually useful. ✨ Takeaway: Speed is not value. Useful work is. 🤔 Final thought ➡️ Every one of these stories says the same thing: AI is moving into the tools you already have. Which means the advantage was never access to the technology — it's the curiosity, the judgment, and the willingness to adapt that you bring to it. 🏆 The winners won't be the people chasing every new tool. They'll be the ones using AI to think bigger, not just move faster. ➡️ You don't need to be an expert to begin. You just need to begin. — Fernando Bello · Author of "Find the Best — A Full Guide for Product Management" · LinkedIn Top Product Management Voice #Leadership #ProductManagement #AI #FutureOfWork #Productivity #LearningAI 📚 Sources — TLDR AI news → https://tldr.tech/ai ➡️ "Google announces Gemma 4 — 9to5Google → https://9to5google.com/2026/07/14/pixel-10-gemma-4/ ➡️ "Celebrating 25 years of visual search innovation" — Google Blog → https://blog.google/products-and-platforms/products/search/google-images-25th-anniversary/ ➡️ "Measuring the Business Value of AI Agents" — OpenAI → https://openai.com/index/managing-ai-investments-in-agentic-era/
McKinsey asked 10,000+ executives: 30% of reflective leaders say their teams adapt to change fast - versys 17% who don't That edge is human.
➡️ McKinsey asked **more than 10,000 senior executives across 15 countries and 16 industries** what separates leaders whose organizations adapt fast from those that stall. The strongest signal wasn't their AI stack. It was whether they stop to think. ➡️ In its State of Organizations 2026 report, McKinsey found that **30% of reflective leaders believe their organizations can quickly adapt to change, versus only 17 percent of non-reflective leaders.** Nearly double — from thinking time alone. ➡️ Meanwhile, **86% of leaders feel their organizations are not very prepared to adopt AI in day-to-day operations.** The gap isn't tooling. McKinsey's own read: "AI puts even greater emphasis on the human aspects of work and requires more of leaders." ➡️ And leaders at AI-pioneering organizations are **more than twice as likely to believe their employees will aim for and achieve more (56 percent versus 26 percent).** Belief in people — still a human input. ✨ AI isn't shrinking the leader's job. It's stripping it back to the part that was always the job. 💡 As McKinsey and the World Economic Forum put it in January: "Generative AI cannot set aspirations, make tough calls, build trust among stakeholders, hold team members accountable, or generate truly new ideas." A model can draft my update. It can't own the call when it goes wrong. It can't decide which two things actually matter this quarter. It can't notice that the quiet person on the call stopped speaking up three weeks ago. The tool clears the desk. You still have to sit at it. 💬 When did reflection last make it onto your calendar — and survive contact with the week? 👇 — Fernando Bello · Author of "Find the Best — A Full Guide for Product Management" · LinkedIn Top Product Management Voice #Leadership #ProductManagement #ProductLeadership #AI #FutureOfWork #Productivity 📚 Sources for the stats: ➡️ McKinsey, The State of Organizations 2026 (February 19, 2026) — survey of "more than 10,000 senior executives across 15 countries and 16 industries"; "30% of reflective leaders believe their organizations can quickly adapt to change, versus only 17 percent of non-reflective leaders"; "86% of leaders feel their organizations are not very prepared to adopt AI in day-to-day operations"; AI Pioneers are "more than twice as likely to believe that their employees will aim for and achieve more (56 percent versus 26 percent)"; "AI puts even greater emphasis on the human aspects of work and requires more of leaders": https://www.mckinsey.com/capabilities/people-and-organizational-performance/our-insights/the-state-of-organizations ➡️ Bob Sternfels, Børge Brende & Daniel Pacthod, "Building leaders in the age of AI," McKinsey (January 12, 2026) — "Generative AI cannot set aspirations, make tough calls, build trust among stakeholders, hold team members accountable, or generate truly new ideas": https://www.mckinsey.com/capabilities/strategy-and-corporate-finance/our-insights/building-leaders-in-the-age-of-ai
AI literacy is now the fastest-growing skill on Linkeding, and the WEF ranks AI #1 through 2030. Yet 59 of every 100 workers will need traiing by 2030 - and 11 of them won't get access.
🧭 The AI gap isn't access anymore. Almost everyone has the tools now — the real divide is fluency: who actually knows how to work with them well. ➡️ Not who has AI. Who's fluent in it. This week the voices on my feed weren't hyping tools either. Simon Sinek was writing about optimism and starting with why, Adam Grant about substance over style, Justin Welsh about owning your time, Lara Acosta about staying focused. The through-line: as the tools become universal, the human skill of using them well becomes the edge. And the data shows it 👇 ➡️ AI literacy is now the fastest-growing skill on LinkedIn in the US — and among the fastest-growing across regions and job functions worldwide (LinkedIn, 2025). ➡️ The World Economic Forum ranks AI and big data the single fastest-growing skill through 2030, with over 90% of employers in leading industries expecting demand to climb (WEF, Future of Jobs, 2025). ➡️ Yet 59 of every 100 workers will need training by 2030 — and for 11 of them, it won't even be accessible (WEF, Future of Jobs, 2025). ➡️ That's the real leadership gap: the tools are everywhere, but fluency isn't. Closing it — turning AI from a few power users into a team-wide capability — is a product management job. PMs build the workflows, examples, and habits that make a whole team fluent, not just curious. ✨ The behavior worth passing on: treat AI fluency as a skill your team builds together, on purpose — not a gadget a few people happen to enjoy. ➡️ The best PMs I know right now: • Learn in the open — share prompts, wins, and misfires so everyone levels up. • Build fluency into the actual workflow, not a side experiment. • Protect time to practice; like any skill, fluency compounds. 💡 Access to AI is becoming table stakes. Fluency is the edge — and because it's a skill, anyone willing to practice can build it. That's the hopeful part. ➡️ So don't just hand your team AI. Help them get fluent — that's where the results actually live. 💬 Leaders: what's genuinely working to build AI fluency on your team — not just access, but real skill? 👇 — Fernando Bello · Author of "Find the Best — A Full Guide for Product Management" · LinkedIn Top Product Management Voice #ProductManagement #AILiteracy #AI #FutureOfWork #Upskilling 📚 Sources for the stats: ➡️ LinkedIn — "Skills on the Rise in 2025" (March 26, 2025): AI literacy is the #1 fastest-growing skill in the US and among the fastest-growing across regions and job functions → https://www.linkedin.com/business/talent/blog/learning-and-development/skills-on-the-rise ➡️ World Economic Forum — "The Future of Jobs Report 2025" (January 7, 2025): AI and big data is the fastest-growing skill through 2030 (over 90% of employers in top industries expect rising demand), and 59 of every 100 workers will need training by 2030 — with 11 lacking access → https://www.weforum.org/publications/the-future-of-jobs-report-2025/in-full/3-skills-outlook/
McKinsey: Leaders spend 37% of their time deciding, and over half of it is used ineffectively. Fast deciders make high-quality calls 2x more often. Decide, communicate, move. Most doors are two-way.
🧭 Decisiveness is a leadership skill you can train — and my best teacher doesn't work in an office. It's the jiu-jitsu mat. 🥋 On the mat, a half-committed sweep always fails. Wait for perfect certainty, and you're already caught. You learn quickly that hesitation *is* a decision — usually the worst one available. ✨ The behavior that carries over into leadership: commit fully to reversible decisions. If a call can be undone, decide it quickly, communicate it clearly, and move — and save the long deliberation for the true one-way doors. McKinsey's research on decision-making backs the mat's lesson 👇 ➡️ Executives spend **37% of their time making decisions — and more than half of that time is used ineffectively** (McKinsey Global Survey). ➡️ For an average Fortune 500 company, that waste adds up to **more than 530,000 days of lost working time and roughly $250 million in labor costs per year.** ➡️ And the myth that speed hurts quality? McKinsey found organizations that decide quickly are **twice as likely to make high-quality decisions** as slow deciders 💡 The lesson: indecision isn't caution — it's cost. Sort your decisions into reversible and irreversible, and give each only the deliberation it deserves. Speed and quality are teammates, not rivals. 🤔 It also helps that Claude Cowork strips noise from my mornings — fewer open loops competing for attention mean cleaner, faster calls on the few things that matter. 🎓 Harvard and my MBA gave me frameworks for *analyzing* decisions. The mat taught me the other half: at some point, analysis ends and commitment begins. 💬 Fellow leaders: what's your rule for knowing when it's time to stop deliberating and decide? 👇 — Fernando Bello · Author of "Find the Best — A Full Guide for Product Management" · LinkedIn Top Product Management Voice #Leadership #ProductLeadership #ProductManagement #AI #Management #Productivity #GrowthMindset 📚 Sources for the stats: ➡️ McKinsey & Company — "Decision making in the age of urgency" (37% of time on decisions, >half used ineffectively; 530,000 days / ~$250M per year; quick deciders 2x more likely to make high-quality decisions): https://lnkd.in/eqSs6qjE
Consortium for Research on Emotional Intelligence in Organizations** found that across 200+ companies, about **two-thirds** of what separates top performers from average ones is emotional competence rather than IQ or technical skill — and in senior leadership roles, **over four-fifths.**
Some of the clearest thinking I did this week started with a smaller question than usual: not "what's wrong?" but "what exactly am I feeling right now?" ➡️ The gap between "I'm stressed" and "I'm actually under-resourced and a little anxious about one deadline" is where a surprising amount of growth hides. That gap has a name. Psychologists call it emotional labeling — naming what you feel with precision — and it sits at the center of emotional intelligence. Yale's Center for Emotional Intelligence builds its whole RULER framework on five skills — Recognizing, Understanding, Labeling, Expressing, and Regulating — and Labeling is the hinge the other four turn on. Why care on a Friday? Because the payoff is measurable. The **Consortium for Research on Emotional Intelligence in Organizations** found that across 200+ companies, about **two-thirds** of what separates top performers from average ones is emotional competence rather than IQ or technical skill — and in senior leadership roles, **over four-fifths.** Naming emotions well isn't soft. It's a performance skill. Here's how I'm trying to grow it: 🔎 **Recognize the signal first.** ➡️ Grow it: before you label, read the body — tight shoulders, clipped replies, restless energy. The data is already there. 🏷️ **Label with precision, not shorthand.** ➡️ Grow it: trade "fine" and "stressed" for the exact word — overwhelmed, uncertain, protective, proud. A bigger emotional vocabulary gives you more accurate options for what to do next. 💬 **Express it cleanly so people can meet you there.** ➡️ Grow it: "I'm frustrated, and I still want this to work" tells a teammate far more than a sigh ever will. 🧭 **Let the label choose the response.** ➡️ Grow it: "anxious" asks for a plan; "resentful" asks for a boundary. A peer-reviewed review of EI, leadership and teams (**104 studies**, PMC/NCBI) links this kind of team emotional intelligence to more trust and stronger performance. 💬 What's one feeling you'd name more precisely at work this week — and what might change if you did? 👇 — Fernando Bello · Author of "Find the Best — A Full Guide for Product Management" · LinkedIn Top Product Management Voice #EmotionalIntelligence #Leadership #EmployeeGrowth #EQ #FridayReflection #ProductManagement #OperationsLeadership 📚 Sources for the stats: ➡️ Consortium for Research on Emotional Intelligence in Organizations (two-thirds / four-fifths performance findings): https://www.eiconsortium.org/reports/business_case_for_ei.html ➡️ Yale Center for Emotional Intelligence — The RULER Approach (Recognizing, Understanding, Labeling, Expressing, Regulating): https://medicine.yale.edu/childstudy/services/community-and-schools-programs/center-for-emotional-intelligence/ ➡️ Emotional Intelligence, Leadership & Work Teams (PMC/NCBI, 2023): https://pmc.ncbi.nlm.nih.gov/articles/PMC10543214/ ➡️ University of West Alabama — The Science of Emotion: https://online.uwa.edu/news/emotional-psychology/
Three AI stories worth your attention — translated from technical language into simple ideas you can actually use.
🤖 AI News, Explained for Beginners 💡 Three AI stories worth your attention — translated from technical language into simple ideas you can actually use. ➡️ AI headlines can feel overwhelming: new models, tools, and predictions every day. The secret is not following everything — it’s understanding what changes how you work. 1. The real AI divide isn’t access — it’s how you use it ➡️ A top AI researcher warned that the future gap won’t be between people who have AI and those who don’t. ➡️ The real difference will be between people using AI to improve their thinking and people using it to avoid thinking. ➡️ Use AI to challenge ideas, test assumptions, and explore possibilities — not just copy answers. ✨ Takeaway: Treat AI like a thinking partner, not a vending machine. 2. You don’t need every AI tool — master the basics ➡️ New AI apps appear every week, but success doesn’t come from chasing every trend. ➡️ Strong fundamentals still win: understand problems, use data, improve processes, and focus on people. ✨ Takeaway: Solve one meaningful problem with AI before collecting ten tools you barely use. 3. You can build your own AI helper faster than you think ➡️ Beginners can already create AI assistants by giving clear instructions and examples — no programming required. ➡️ Automate simple tasks such as reports, summaries, emails, and formatting. ➡️ The biggest win is not only saving time — it’s building confidence. ✨ Takeaway: The fastest way to understand AI is by using it. 🎲 Fun fact ➡️ About 15% of Americans said they would consider working for an AI boss who manages tasks and schedules. ➡️ It shows we are still defining how AI will shape the future of work. 🤔 Final thought ➡️ AI tools will keep changing, but curiosity, judgment, and adaptability will always matter. 🏆 The winners won’t chase every new tool — they’ll learn how to use AI to think bigger. ➡️ You don’t need to be an expert to begin. You just need to begin. — Fernando Bello · Author of "Find the Best — A Full Guide for Product Management" · LinkedIn Top Product Management Voice #Leadership #ProductManagement #ProductLeadership #AI #FutureOfWork #Productivity 📚 Sources — from the "DAILY AI NEWS" digest (Marketing + Media Alliance) in your inbox:* ➡️ *"A top researcher says a new divide is emerging in AI use — and most people are on the losing side" — Business Insider (DAILY AI NEWS, April 1, 2026)* ➡️ *"To Succeed with AI, You've Got to Nail the Basics" — Harvard Business Review (DAILY AI NEWS, April 8, 2026)* ➡️ *"How to Build Your First Claude Skill in Minutes: Quick Start Guide" — Geeky Gadgets (DAILY AI NEWS, April 1, 2026)* ➡️ *"Can training reduce employees' fear of being replaced by AI?" — Marketing + Media Alliance (DAILY AI NEWS, April 1, 2026)* ➡️ *"15% of Americans say they'd be willing to work for an AI boss" — TechCrunch, citing a Quinnipiac University poll (DAILY AI NEWS, April 1, 2026)*
Microsoft studied 20,000 AI users: culture beats invidividual skill 2-to-1 in driving real AI impact (67% vs. 32%). That edge is deeply human.
➡️ The most surprising leadership finding of 2026: your AI results depend more on you than on the AI. That's exactly the shift Microsoft's brand-new research points to. ➡️ In its 2026 Work Trend Index, Microsoft analyzed trillions of productivity signals and surveyed **20,000 people who use AI at work across 10 countries.** The headline for anyone who leads: **organizational factors — culture, manager support, talent practices — account for more than 2x the AI impact of individual mindset and behavior (67% vs. 32%).** Read that again. The biggest driver of whether AI actually creates value isn't the tool, or even the individual using it. It's the environment a leader builds around it. ➡️ The same report found that when **managers actively model AI use, employees report a 17-point lift in the value they get from AI, a 22-point lift in critical thinking, and a 30-point lift in trust.** And **86% of AI users say they treat AI output as a starting point, not a final answer — they "stay responsible for the thinking."** ✨ Put it together and the message is hopeful: AI is absorbing the tasks, and making human leadership more valuable, not less. 💡 Because a model still can't do the actual job. It can't take responsibility when a call goes wrong. It can't decide which two priorities matter this quarter. It can't build enough trust that your team tells you the truth, or develop the person and not just the deliverable. Two decades — from L'Oréal to a Harvard business strategy program and a marketing MBA, into product management, and now running operations and mentoring — taught me that was always the job. The dashboard never was. The leaders who pull ahead won't be the ones who use AI the most. They'll be the ones who use it to get more human at the parts that count. 💬 What's the one leadership task you'd never hand to AI — no matter how good it gets? 👇 — Fernando Bello · Author of "Find the Best — A Full Guide for Product Management" · LinkedIn Top Product Management Voice #Leadership #ProductManagement #ProductLeadership #AI #FutureOfWork #Productivity 📚 Sources for the stats: ➡️ Microsoft, 2026 Work Trend Index Annual Report — 20,000 AI users across 10 countries; organizational factors (culture, manager support, talent practices) drive "more than 2x" the AI impact of individual factors (67% vs. 32%); managers modeling AI use lift value +17, critical thinking +22, and trust +30 points; 86% "stay responsible for the thinking": https://www.microsoft.com/en-us/worklab/work-trend-index/agents-human-agency-and-the-opportunity-for-every-organization
88% of organizations now use AI in at least one function — yet only about 6% capture significant enterprise value (McKinsey, State of AI 2025).
🧭 Everyone adopted AI. Almost no one can prove it worked. ➡️ Not a smarter model. Not a bigger budget. A missing metric. This week the feeds were quieter on the "next big model." The line that stuck with me was Simon Sinek's: you get the behavior you measure — and most leaders are measuring the wrong thing. That is the AI story right now. We're counting adoption, not outcomes. And the data shows it 👇 ➡️ 88% of organizations now use AI in at least one function — yet only about 6% capture significant enterprise value (McKinsey, State of AI 2025). ➡️ 95% of enterprise generative AI pilots deliver little to no measurable impact on profit and loss — MIT calls it "the GenAI Divide" (MIT NANDA, 2025). ➡️ What sets the winners apart? They redesign the workflow and track the KPI (key performance indicator) — not the tool (McKinsey, 2025). ➡️ That gap — between "we use AI" and "AI moved the outcome" — is a product management job. PMs don't adopt technology. They point it at one real problem and measure whether it moved. ✨ One behavior worth passing on: choose the problem before the tool. ➡️ Name the single outcome that matters. ➡️ Redesign the workflow around it — don't bolt AI on. ➡️ Define what success looks like before you ship. 💡 Adoption isn't impact. Measure the outcome, not the activity. 🤔 This is how I work too: I let Claude Cowork clear the noise — the reports, the status-chasing — so the reclaimed time goes to the one question that counts: did it actually move the number? ➡️ The winners of this next phase won't use AI the most. They'll measure it the best. 💬 What's the one metric you'd trust to tell you your AI is actually working? 👇 — Fernando Bello · Author of "Find the Best — A Full Guide for Product Management" · LinkedIn Top Product Management Voice #ProductManagement #ProductLeadership #AI #DataDriven #BusinessPerformance 📚 Sources for the stats: ➡️ McKinsey — "The state of AI in 2025: Agents, innovation, and transformation" (Nov 5, 2025): 88% regular AI use; ~6% high performers capturing significant enterprise value; redesigning workflows + tracking KPIs are the top differentiators → https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai ➡️ MIT NANDA — "The GenAI Divide: State of AI in Business 2025" (Aug 18, 2025): ~95% of enterprise generative AI pilots show little to no measurable profit-and-loss impact; only ~5% drive rapid revenue → https://fortune.com/2025/08/18/mit-report-95-percent-generative-ai-pilots-at-companies-failing-cfo/
Gallup found **people with a best friend at work are 7x as engaged.**
🧭 Belonging isn't a perk you announce on a poster. It may be the most underrated leadership skill there is — and the longest study of human happiness ever run makes the case better than I can. 🔬 Since 1938, Harvard has followed the same people for more than 85 years — from their 20s into their 90s — measuring everything: income, IQ, cholesterol, even genes. One thing predicted who aged happily and healthily better than anything else: the strength of their relationships. Close connection beat money, fame, IQ, and genes as a predictor of a long, good life. ❤️ How satisfied people were with their relationships at 50 predicted their physical health at 80 **better than their cholesterol did.** The study's director, Robert Waldinger, put it bluntly: *"Loneliness kills. It's as powerful as smoking or alcoholism."* And that wiring doesn't clock out when we log in: ➡️ Gallup found **people with a best friend at work are 7x as engaged.** ➡️ Yet Gallup's 2026 report shows **global engagement fell to just 20% in 2025 — an estimated $10 trillion drain on the world economy.** 💡 So belonging isn't soft, and it isn't a perk. It's human wiring — and it quietly decides whether people give a team their best or slowly check out. 🎓 I studied business strategy at Harvard and did an MBA in marketing — but no framework taught me what that 85-year study did: relationships aren't the reward for a good life or a strong team. They're the foundation. 💬 Fellow leaders: what's one small thing you do to make people feel they belong — not just perform? 👇 — Fernando Bello · Author of "Find the Best — A Full Guide for Product Management" · LinkedIn Top Product Management Voice #Leadership #ProductLeadership #ProductManagement #AI #Management #Productivity #GrowthMindset 📚 Sources for the stats: ➡️ Harvard Gazette — Harvard Study of Adult Development (relationships vs. cholesterol; Waldinger on loneliness): https://news.harvard.edu/gazette/story/2017/04/over-nearly-80-years-harvard-study-has-been-showing-how-to-live-a-healthy-and-happy-life/ ➡️ Gallup — "Why Having a Best Friend at Work Is Important" (7x as engaged): https://www.gallup.com/cliftonstrengths/en/406298/why-having-best-friend-work-important.aspx ➡️ Gallup — State of the Global Workplace 2026 (engagement 20%, $10T): https://www.gallup.com/workplace/349484/state-of-the-global-workplace.aspx
The **Consortium for Research on Emotional Intelligence in Organizations** reports that when the U.S. Air Force selected recruiters for competencies like empathy and emotional self-awareness, their ability to predict top performers rose **nearly threefold — saving $3 million a year.**
The best moments of my week almost never made it into a status update. They were the small ones — when I stopped drafting my reply in my head and actually understood what the person in front of me was feeling. That's empathy, and it's the most underrated growth skill at work. Not softness — skill. And like any skill, it's trainable. The **Consortium for Research on Emotional Intelligence in Organizations** reports that when the U.S. Air Force selected recruiters for competencies like empathy and emotional self-awareness, their ability to predict top performers rose **nearly threefold — saving $3 million a year.** Empathy isn't a "nice to have." It shows up on the scoreboard. Here's how I'm trying to grow it, using Yale's RULER lens turned outward — toward the people around me: 👂 **Recognize what others actually feel.** ➡️ Grow it: listen to tone, pace, and energy, not just words. Most people tell you how they're doing long before they say it out loud. 🪞 **Reflect it back before you rush to fix.** ➡️ Grow it: try "Sounds like you're carrying a lot right now — is that it?" Naming someone's experience often helps more than solving it. When one manufacturing plant trained supervisors to listen and help people work through their own problems, **formal grievances fell from 15 a year to 3, and lost-time accidents dropped 50%.** 🤝 **Make it safe — then trust compounds.** ➡️ Grow it: ask before you advise. A **peer-reviewed review of emotional intelligence and work teams (PMC/NCBI)** links higher team EI to more trust, less corrosive conflict, and stronger performance. 🧭 **Regulate yourself so your empathy stays generous.** ➡️ Grow it: you can't tune into anyone while you're flooded. Build one reliable reset — a breath, a short walk, a night before you reply. 💬 Which one would change your week the most — recognizing, reflecting, making it safe, or regulating? Tell me below 👇 — Fernando Bello · Author of "Find the Best — A Full Guide for Product Management" · LinkedIn Top Product Management Voice #EmotionalIntelligence #Leadership #EmployeeGrowth #EQ #FridayReflection #ProductManagement #OperationsLeadership 📚 Sources for the stats: ➡️ Consortium for Research on Emotional Intelligence in Organizations — The Business Case for Emotional Intelligence (Air Force empathy selection; manufacturing listening-training results): https://www.eiconsortium.org/reports/business_case_for_ei.html ➡️ Yale Center for Emotional Intelligence — The RULER Approach: https://medicine.yale.edu/childstudy/services/community-and-schools-programs/center-for-emotional-intelligence/ ➡️ Emotional Intelligence, Leadership & Work Teams — peer-reviewed hybrid literature review (PMC/NCBI, 2023): https://pmc.ncbi.nlm.nih.gov/articles/PMC10543214/ ➡️ University of West Alabama — The Science of Emotion: https://online.uwa.edu/news/emotional-psychology/
By 2028, 15% of day-to-day work decisions will be made autonomously by AI agents & AI-driven traffic to US retail sites has surged over 4,700% in a year, so merchants now have to tell trusted shopping agents from bad bots
🧭 First AI agents learned to think. Now they're learning to pay — and to prove they're not bots. ➡️ The biggest move in artificial intelligence (AI) this week isn't a smarter model — it's the plumbing that lets an agent actually buy things. Visa, Mastercard, Google, OpenAI and Cloudflare are all racing to build it. Here's the shift: an agent that can decide is only useful if it can act, and the biggest action is a purchase. That creates two problems — how an agent pays under your rules and how a merchant knows it's a trusted agent rather than a malicious bot. Visa's Trusted Agent Protocol (built with Cloudflare) gives agents a signed, verifiable identity. Google's Agent Payments Protocol — backed by 60+ companies including Mastercard, PayPal and Coinbase — proves you actually authorized the buy. Visa Intelligent Commerce and Mastercard Agent Pay move money with built-in spend limits. ➡️ By 2028, 15% of day-to-day work decisions will be made autonomously by AI agents — up from 0% in 2024 (Gartner, 2025). ➡️ AI-driven traffic to US retail sites has surged over 4,700% in a year, so merchants now have to tell trusted shopping agents from bad bots (Visa, 2025). ➡️ 85% of shoppers who've used AI to shop say it improved the experience — the demand is already here (Visa, 2025). ➡️ My take: the winners won't be whoever bolts on a checkout bot. They'll be the ones who build trust — identity, authorization, spend controls — so agents can act without acting recklessly. ✨ Ask "could an AI agent buy from us — and would we even know it was legit?" That single question maps your next year of work. 💡 The last era gave us agents that answer. This one is about agents you can trust to act. ➡️ Get ahead of this now: agent-readiness is about to be as basic as having a website. 💬 Would you let an AI agent make a purchase for you today — and where would you draw the line? 👇 — Fernando Bello · Author of "Find the Best — A Full Guide for Product Management" · LinkedIn Top Product Management Voice #ArtificialIntelligence #AgenticAI #FutureOfWork #Payments #Leadership 📚 Sources: ➡️ Gartner — 15% of day-to-day work decisions → https://lnkd.in/emBygw9n ➡️ Visa — "Visa Introduces Trusted Agent Protocol" (Oct 14, 2025): AI-driven traffic to US retail sites surged over 4,700% in a year; 85% of AI shoppers say it improved their experience; a framework to recognize trusted agents and distinguish them from malicious bots → https://lnkd.in/ehP6-5zT ➡️ Google Cloud — "Announcing Agent Payments Protocol (AP2)" (Sept 2025): open agent-payments standard backed by 60+ organizations including Mastercard, PayPal and Coinbase → https://lnkd.in/eSjzhjQg
McKinsey surveyed 5,774 employees and found the top reason people quit wasn't pay — it was that they **didn't feel valued by their organization (54%)** or **by their manager (52%).**
➡️ People don't quit jobs. They quit feeling invisible. 👥 The tools keep getting better at the work. Our job is to get better at the people. ⁉️ The most expensive mistake I watch leaders make isn't a bad call — it's letting good work go unseen. And it's the one that's almost free to fix. The research is blunt about it: ➡️ McKinsey surveyed 5,774 employees and found the top reason people quit wasn't pay — it was that they **didn't feel valued by their organization (54%)** or **by their manager (52%).** In their words: when leaders reach for a bonus instead of real acknowledgment, "employees sense a transaction," not appreciation. ➡️ Gallup and Workhuman tracked nearly 3,500 people and found **well-recognized employees were 45% less likely to have left after two years** — yet **just 22% say they get the right amount of recognition** for the work they do. ➡️ Get it right — the kind that's specific, genuine, and consistent — and those employees are **nine times as likely to be engaged.** ✨ Read that together, and the gap is staggering: recognition is nearly free, drives retention, and most of us still ration it like it's scarce. 💫 So where does AI fit? Honestly — it helps. A model can flag the quiet win buried in a dashboard, remind me whom I haven't acknowledged in a while, even draft the note. What it can't do is mean it. "Great job" from an algorithm is wallpaper. The same three words land completely differently when they come from a person who actually saw what you did — and says so, to your face. 💡 That's the line I hold: let AI handle the remembering; I handle the meaning. Name the specific thing. Do it in the moment. Say why it mattered. A dashboard can tell you a number moved — only a human can tell someone, "I saw that, and it was you." 🤔 Two decades leading and mentoring teams, from L'Oréal to product management to running operations, taught me the same lesson every time: people give their best to leaders who notice. 💬 When was the last time someone at work made you feel truly seen — and what did they say? 👇 — Fernando Bello · Author of "Find the Best — A Full Guide for Product Management" · LinkedIn Top Product Management Voice #Leadership #ProductManagement #ProductLeadership #AI #FutureOfWork #EmployeeEngagement 📚 Sources for the stats: ➡️ McKinsey, 'Great Attrition' or 'Great Attraction'? The choice is yours (2021) — top reasons for quitting: not feeling valued by organization (54%) / by manager (52%); "employees sense a transaction": https://lnkd.in/efUVA-jH ➡️ Gallup & Workhuman, Employee Retention Depends on Getting Recognition Right (2024) — well-recognized employees 45% less likely to leave; only 22% get the right amount of recognition; 9x more likely to be engaged: https://lnkd.in/eysv7qrd
The leadership skill I'm practicing hardest right now? 🤔 Resilience — and I'm learning it by losing.
🧭 The leadership skill I'm practicing hardest right now? 🤔 Resilience — and I'm learning it by losing. 📆 Twice a week I live two opposite lives. 🏓 On the pickleball court, I almost always win. Two decades of competitive tennis gave me a head start most opponents can't catch. Winning is the easy teacher. 🥋 On the jiu-jitsu mat, I almost always lose. Six months in, I'm the beginner getting tapped by people I "should" beat. Losing is the hard teacher — and the better one. 💡 Here's why that gap matters, backed by the research: ➡️ Angela Duckworth studied **11,000+ West Point cadets** and found **grit predicts who succeeds better than talent, IQ, or fitness.** ➡️ Across five studies with **1,674 people**, Eskreis-Winkler & Fishbach found we actually **learn LESS from failure than success — 48% vs 62% correct on a follow-up test** — because losing bruises the ego and we stop paying attention. ➡️ A national experiment with **~12,500 students** (Yeager & Dweck, *Nature* 2019) showed a short **growth-mindset** lesson raised grades — proof that the will to keep learning is trainable. 🔖 Put it together: talent wins the easy games, grit wins the hard ones — but losing only makes you better if you stay humble enough to actually learn from it. ➡️ That's the behavior I'm working on as a leader: staying teachable when I win AND when I lose, and making it safe for my team to do the same. Degrees and titles hand you frameworks; the mat hands you humility — and humility is what keeps a leader learning. 💬 Where are you winning on old talent — and where are you brave enough to lose, and learn? 👇 — Fernando Bello · Author of "Find the Best — A Full Guide for Product Management" · LinkedIn Top Product Management Voice #Leadership #ProductLeadership #ProductManagement #AI #Management #Productivity #GrowthMindset 📚 Sources for the stats: ➡️ Grit / West Point (Angela Duckworth): https://lnkd.in/dW5HNjM6 ➡️ We learn less from failure than success (Eskreis-Winkler & Fishbach, 2019): https://lnkd.in/dC8BPYPB ➡️ Growth-mindset national study (Yeager & Dweck, Nature 2019): https://lnkd.in/dx_M7M7r
Roughly two-thirds of what separates star performers from average ones is emotional competence
👥 The people who grow fastest don't feel less. They understand what they feel and choose what to do next. ✨ That's emotional intelligence, and it's a skill you can build — not a fixed trait. The **Consortium for Research on Emotional Intelligence in Organizations** reports that **roughly two-thirds of what separates star performers from average ones is emotional competence, not technical skill — and in top leadership roles, more than 80%.** Yale's Center for Emotional Intelligence gives us a simple backbone for building it — RULER: 🔍 **Recognize & Understand** — catch the signal before the story. ➡️ Grow it: when something stings, pause and ask, "what am I feeling, and what's underneath it?" You stop reacting to the wrong thing. 🏷️ **Label it precisely.** ➡️ "I'm stressed" is a fog; "I'm overwhelmed because I'm carrying this alone" is a map. Precise words turn a feeling into something you can act on. 🗣️ **Express it cleanly.** ➡️ Share the feeling and the need, skip the blame: "I felt sidelined on that call; I'd like a heads-up next time" lands. "You ignored me" doesn't. 🧭 **Regulate under pressure.** ➡️ The pause is the whole skill — and optimism is trainable too: the EI Consortium found salespeople high in learned optimism sold **37% more in their first two years than pessimists.** Build one reliable reset: a breath, a walk, a night before you reply. ➡️ This is where teams win or lose, too — a peer-reviewed review of **104 studies (1998–2022)** found weak emotional-intelligence environments breed more task and relationship conflict. 💬 Which RULER skill would change your week the most — recognizing, labeling, expressing, or regulating? Tell me below 👇 — Fernando Bello · Author of "Find the Best — A Full Guide for Product Management" · LinkedIn Top Product Management Voice hashtag#EmotionalIntelligence hashtag#Leadership hashtag#EmployeeGrowth hashtag#EQ hashtag#FridayReflection hashtag#ProductManagement hashtag#OperationsLeadership 📚 Sources for the stats: ➡️ Consortium for Research on Emotional Intelligence in Organizations — The Business Case for Emotional Intelligence: https://lnkd.in/eRhpFic6 ➡️ Yale Center for Emotional Intelligence — The RULER Approach: https://lnkd.in/ecfm283C ➡️ Emotional Intelligence, Leadership & Work Teams — peer-reviewed review of 104 studies (PMC/NCBI, 2023): https://lnkd.in/eb9TPNU4 ➡️ University of West Alabama — The Science of Emotion: https://lnkd.in/eeTdXEb8
In one widely cited study, salespeople selected for emotional competencies sold **$91,370 more** each than peers hired the old way — a **$2,558,360** annual revenue lift (EI Consortium).
📈 Friday thought: the skills that grow a career fastest rarely sit on the résumé — they're the ones that help us read a room, stay steady under pressure, and bring out the best in the people around us. 🌱 This week I went back to the research on emotional intelligence (EI): what it is, why it drives growth, and how anyone can build it ⤵️ 🧭 **EI is learnable — that's the whole point.** Yale's Center for Emotional Intelligence built its RULER method on five skills: Recognizing, Understanding, Labeling, Expressing, and Regulating emotions. Growth starts with labeling — "I'm frustrated we're behind" lands very differently than a slammed laptop. ➡️ Name the emotion before you try to solve the problem. 📈 **EI shows up in performance.** In one widely cited study, salespeople selected for emotional competencies sold **$91,370 more** each than peers hired the old way — a **$2,558,360** annual revenue lift (EI Consortium). Empathy isn't fluffy; it compounds. 🧠 **It can matter as much as IQ.** The University of West Alabama's science-of-emotion research notes that some researchers argue EI plays an even bigger role in success than traditional intelligence. ➡️ Develop and promote people for how they handle pressure and conflict — not just technical skill. 👥 **It grows leaders and teams.** Peer-reviewed research on PMC/NCBI links higher EI to stronger leadership and healthier, higher-performing teams. ➡️ Open your next 1:1 with "how are you, really?" before the status update — that's where real growth conversations start. 💬 Of the five RULER skills — Recognizing, Understanding, Labeling, Expressing, Regulating — which is your growth edge this quarter? 👇 — Fernando Bello · Author of "Find the Best — A Full Guide for Product Management" · LinkedIn Top Product Management Voice #EmotionalIntelligence #Leadership #EmployeeGrowth #EQ #FridayReflection #ProductManagement #OperationsLeadership 📚 Sources for the stats: ➡️ EI Consortium — *The Business Case for Emotional Intelligence* (emotional-competency selection results): https://lnkd.in/eRhpFic6 ➡️ University of West Alabama — *The Science of Emotion: The Basics of Emotional Psychology*: https://lnkd.in/eeTdXEb8 ➡️ Yale Center for Emotional Intelligence — the RULER approach: https://lnkd.in/ecfm283C ➡️ PMC / NCBI — peer-reviewed research on emotional intelligence, leadership, and teams: https://lnkd.in/eb9TPNU4
Everyone is racing to adopt AI. The quiet winners are racing to think clearly. 95% of enterprise generative-AI pilots are delivering no measurable impact on the bottom line
🧭 Everyone is racing to adopt AI. The quiet winners are racing to think clearly. ➡️ This week on LinkedIn, four big voices circled the same idea. Steven Bartlett asked whether we are confusing how important AI is with how safe it is to bet on it. Alex Hormozi kept preaching fundamentals — "do the work tired, do the work imperfectly." Jeff Selingo questioned what a degree is really worth as learning gets reinvented. And Gretchen Rubin nudged us toward a "Summer of Upskilling." 🚥 Different rooms. Same signal. ⚙️ The tool everyone is chasing is not the edge. Judgment is. And the people who keep learning are the ones who compound. And the data backs it 👇 ➡️ 95% of enterprise generative-AI pilots are delivering no measurable impact on the bottom line — and the gap is not the technology, it is how organizations learn to use it (MIT, State of AI in Business, 2025). ➡️ 39% of the average worker's core skills will be transformed or outdated by 2030, and analytical thinking is now the most sought-after skill employers want (World Economic Forum, Future of Jobs Report, 2025). ➡️ My take: clarity beats hype. The best leaders do not adopt AI to move faster — they use it to think bigger. Speed without judgment just gets you to the wrong place sooner. ✨ One habit to borrow this week: pick a "Summer of ____." One theme — a skill, a certification, ten real conversations — and make small, consistent progress. Curiosity is a strategy, not a personality trait. 💡 In a gold rush, everyone sells shovels. The real edge is knowing where to dig. ➡️ The tools will keep changing. Clear thinking and the will to keep learning will not go out of style. 💬 What is your "Summer of ____" this year — and what are you finally going to learn? 👇 — Fernando Bello · Author of "Find the Best — A Full Guide for Product Management" · LinkedIn Top Product Management Voice #Leadership #FutureOfWork #ArtificialIntelligence #Upskilling #ProductManagement #GrowthMindset 📚 Sources for the stats: ➡️ MIT NANDA — "The GenAI Divide: State of AI in Business 2025" (Aug 2025): 95% of enterprise generative-AI pilots show no measurable P&L impact, and the barrier is organizational learning, not the models → https://lnkd.in/edQ5cJhU ➡️ World Economic Forum — "The Future of Jobs Report 2025" (Jan 2025): 39% of core skills will be transformed or outdated by 2030, and analytical thinking is the most sought-after core skill → https://lnkd.in/e4QdTxKT
AI Won't Replace Leaders. The World Economic Forum studied 2,800+ skills and found **69%** have low or no chance of being automated by today's AI
🧭 AI can run the play. It still can't decide which game you're playing — or carry the people through it. 🤔 That's the line I keep coming back to as agents get better at execution. The work that's left isn't smaller. It's more human. So what can't AI do that a strong leader can? ➡️ Take responsibility. An agent recommends; only a person can own the outcome and absorb the risk. ➡️ Decide what matters. AI optimizes the metric you hand it. Leaders choose which metric is worth chasing. ➡️ Build trust. No one follows a dashboard through a hard quarter — they follow people who tell the truth and have their back. ➡️ Grow people. No model mentors a nervous new hire or sees the potential someone hasn't shown yet. ✅ Here's what this AI wave is actually clarifying: ➡️ The World Economic Forum studied 2,800+ skills and found **69%** have low or no chance of being automated by today's AI — and exactly **zero** ranked "very high" risk. The hardest to replace are the deeply human ones: empathy, listening, judgment (WEF, Future of Jobs 2025). ➡️ Meanwhile, **leadership and social influence** jumped more than any other skill since 2023 — a **22-point** rise — landing as a top-3 skill employers need today (WEF, Future of Jobs 2025). ➡️ And in the companies actually winning with AI? McKinsey found high performers are **3x** more likely to have senior leaders who visibly own the work. The differentiator isn't the model — it's the leadership around it (McKinsey, State of AI 2025). 💡 AI will keep getting better at answers. Leadership is still about asking the right question, choosing under uncertainty, and bringing people with you. That part doesn't get automated. ➡️ Automate the task. But own the judgment, the trust, and the people — that's the half of the job that's still yours. 💬 What's one part of leadership you're certain AI won't replace? 👇