Facilitating Skill Acquisition

9 soft skills to accelerate your career: 1. Make People Feel Important (SHR Method) Your formula to be charismatic: Seen • Give eye contact • Offer a specific compliment Heard • Ask good questions • Be interested, not interesting Remembered • Follow up • Remember name(s) • Recall something you discussed — 2. Hone Your Body Language (7-38-55 Rule) People will like/dislike your communication based on: • 7% words • 38% tonality and face • 55% body language Stand up straight, pull your shoulders back, make eye contact, smile, give a firm handshake... You will be dangerous. — 3. Master the 4-Bullet Update Powerful people are busy. (They might not remember what they asked you to do.) Give an update with this outline: • Here's what you asked me to do • Here's what I did • Here are the risks/blockers (if any) • If given more time, I'd do this — 4. Record and Study Your Speaking The best communicator I know told me her secret: She records her calls. Then she replays them, studies them (like an athlete watching game film). You'll cut 'ums' and 'likes.' 99.9% won't do this. Be the outlier. — 5. Ask Rapport-Building Questions Your network is your net worth. Build bonds with these Qs: • What neighborhood are you in? • Do you have any siblings/kids? • How'd you meet your partner? (if mentioned) • Any fun upcoming trips? Simple, but most people miss this. — 6. Send 'Friday Highlights' If you're new to a team, do this to build trust. Every Friday, send your supervisor(s) a short email. Two parts: 1) Highlights from the prior week • Big tasks completed • People networked with • Extracurriculars (like affinity groups) 2) Upcoming activities for next week • Forward-looking big tasks and networking Friday Highlights will help you: • Build trust • Hold yourself accountable • Tactfully self-promote (perception is reality) • Have everything you need for self-reviews — 7. Don't Complain or Gossip. Ever. Nobody likes to hear complaining. So why do we do it ourselves? (Respectfully standing up for yourself is different.) Separately, when you talk bad about others, people wonder if you talk bad about them too. Just don't do it. — 8. Remember ALL the Names A person's favorite sound is their name. I have a theory about their 2nd favorite sound: The names of their loved ones and pets. Whenever you hear one mentioned, write it down. Later, ask *by name* about them. You will stand out. — 9. Give Yourself a Personal MBA Willingness to learn is a crucial soft skill. I wrote a popular thread on how to give yourself a personal MBA (in 6 months). All it takes to finish? Read 30 mins daily. — 📌 Want to receive a high-res PDF of this one-pager? 1. Follow Ben Meer 2. ♻️ Repost to help your network 3. Subscribe to my free newsletter: https://lnkd.in/ewnjDzas Follow the steps above, and I'll send you this and 8+ of my best infographics for free.

Stanford researchers just introduced a new way to optimize AI models using text-based feedback instead of traditional backpropagation! Deep learning has long relied on numerical gradients to fine-tune neural networks. But, optimizing generative AI systems has been much harder because they interact using natural language, not numbers. 𝗧𝗲𝘅𝘁𝗚𝗿𝗮𝗱 𝗶𝘀 𝘁𝗵𝗲 𝗳𝗶𝗿𝘀𝘁 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 𝘁𝗼 𝗯𝗮𝗰𝗸𝗽𝗿𝗼𝗽𝗮𝗴𝗮𝘁𝗲 𝗹𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗺𝗼𝗱𝗲𝗹 𝗳𝗲𝗲𝗱𝗯𝗮𝗰𝗸, 𝗲𝗻𝗮𝗯𝗹𝗶𝗻𝗴 𝗔𝗜 𝘁𝗼 𝗶𝘁𝗲𝗿𝗮𝘁𝗶𝘃𝗲𝗹𝘆 𝗿𝗲𝗳𝗶𝗻𝗲 𝗶𝘁𝘀 𝗼𝘂𝘁𝗽𝘂𝘁𝘀 𝗮𝗰𝗿𝗼𝘀𝘀 𝗱𝗶𝘃𝗲𝗿𝘀𝗲 𝘁𝗮𝘀𝗸𝘀. 1. Improved AI performance in PhD-level science Q&A, raising accuracy from 51.0% to 55.0% on GPQA and from 91.2% to 95.1% on MMLU physics. 2. Optimized medical treatment plans, outperforming human-designed radiotherapy plans by better balancing tumor targeting and organ protection. 3. Enhanced AI-driven drug discovery by iteratively refining molecular structures, generating high-affinity compounds faster than traditional methods. 4. Boosted complex AI agents like Chameleon, increasing multimodal reasoning accuracy by 7.7% through iterative feedback refinement. 𝗧𝗵𝗲 𝘂𝘀𝗲 𝗼𝗳 "𝘁𝗲𝘅𝘁𝘂𝗮𝗹 𝗴𝗿𝗮𝗱𝗶𝗲𝗻𝘁𝘀" 𝗶𝗻𝘀𝘁𝗲𝗮𝗱 𝗼𝗳 𝗻𝘂𝗺𝗲𝗿𝗶𝗰𝗮𝗹 𝗴𝗿𝗮𝗱𝗶𝗲𝗻𝘁𝘀 𝗶𝘀 𝗽𝗿𝗲𝘁𝘁𝘆 𝗱𝗮𝗿𝗻 𝗰𝗼𝗼𝗹. It treats LLM feedback as “textual gradients” which are collected from every use of a variable in the system. By aggregating critiques from different contexts and iteratively updating variables (using a process analogous to numerical gradient descent), the method smooths out individual inconsistencies. 𝗜'𝗺 𝗰𝘂𝗿𝗶𝗼𝘂𝘀 𝗮𝗯𝗼𝘂𝘁 𝗵𝗼𝘄 𝗳𝗼𝗿𝗺𝗮𝗹𝗶𝘇𝗶𝗻𝗴 𝗺𝗲𝘁𝗵𝗼𝗱𝘀 𝘁𝗼 𝘃𝗮𝗹𝗶𝗱𝗮𝘁𝗲 𝗮𝗻𝗱 𝗰𝗼𝗻𝘀𝘁𝗿𝗮𝗶𝗻 𝘁𝗲𝘅𝘁𝘂𝗮𝗹 𝗴𝗿𝗮𝗱𝗶𝗲𝗻𝘁𝘀 beyond formalization of the propagation and update process via the equations could be developed to enhance robustness. Perhaps training secondary models to evaluate the quality and consistency of textual gradients or an ensemble approach of generating multiple textual gradients using different LLMs or multiple prompts? Just throwing some ideas out there; this stuff is pretty cool. Here's the awesome work: https://lnkd.in/gX8ABsdM Congrats to Mert Yuksekgonul, Federico Bianchi, Joseph Boen, James Zou, and co! I post my takes on the latest developments in health AI – 𝗰𝗼𝗻𝗻𝗲𝗰𝘁 𝘄𝗶𝘁𝗵 𝗺𝗲 𝘁𝗼 𝘀𝘁𝗮𝘆 𝘂𝗽𝗱𝗮𝘁𝗲𝗱! Also, check out my health AI blog here: https://lnkd.in/g3nrQFxW

Want to level up your career? Skip another certificate. Double down on these skills: Soft skills aren't "soft". They matter in every role, They don't lose value, And they're more and more what employers hire and promote for. Especially in an AI-driven world. Yet for some reason it's still much easier to find courses on hard skills. And soft skill training is rare. Let's fix that. Here are 16 of the most important soft skills, With do's and don'ts to help you build yours: 1) Strong Work Ethic ↳Do: Work hard without needing to be asked and without complaining ↳Don't: Think this is about hours - results matter most of all 2) Professional Conduct ↳Do: Earn trust by speaking and acting maturely at all times ↳Don't: Assume you can cross the line just because the setting feels relaxed 3) Growth-Oriented Mindset ↳Do: Invite feedback, stay open to learning, and apply both ↳Don't: Believe you already know it all 4) Dependability ↳Do: Do what you say you will do, by when you said you would do it ↳Don't: Make promises you won't keep 5) Flexibility ↳Do: Rework your plan when you get new information ↳Don't: Refuse to adjust after setbacks 6) Attentive Listening ↳Do: Listen to understand, not to reply, and validate what people say ↳Don't: Ignore the importance of body language 7) Self-Insight ↳Do: Know how others experience your words and actions ↳Don't: Avoid self-reflection or act like you're above critique 8) Managing Your Time ↳Do: Set priorities and stay organized, so you keep your work under control ↳Don't: Let distractions hijack your attention and drain your time 9) Emotional Control ↳Do: Learn to spot emotions and manage your responses ↳Don't: Skip the pause when things get heated 10) Being a Good Teammate ↳Do: Be someone people enjoy working with ↳Don't: Think this means being a pushover - you can still be yourself 11) Clear Communication ↳Do: Speak and write clearly and simply ↳Don't: Use complicated language, hide your point, or ramble 12) Reading People ↳Do: Notice reactions, body language, and other people's mood ↳Don't: Avoid asking when you're unsure how they're feeling 13) Self-Motivation ↳Do: Start projects fast and without being asked ↳Don't: Need constant hand holding or repeated encouragement 14) Team Collaboration ↳Do: Work well with others, sharing ideas and credit ↳Don't: Assume you'd be better off solo 15) Mental Toughness ↳Do: Treat every setback like a lesson ↳Don't: Stay down after you get knocked down 16) Personal Integrity ↳Do: Be honest and ethical, whether or not anyone will notice ↳Don't: Think you can cover things up Master these, and you'll succeed in any role. What skills am I missing? --- ♻️ Repost to help your network level up their careers. And follow me George Stern for more professional growth content.

I used to avoid extracurricular activities in my college days because I thought they would hamper my studies. But when I broke out of that trap and started participating, everything changed, I earned multiple certificates and even received the gold medal in my MBA batch. That experience taught me one thing clearly: 📌 Hard skills can get you in the room, but soft skills decide how far you go. Most people know this, but still don’t work on soft skills because they think it’s abstract and theoretical. Here are practical ways to build soft skills that don’t feel generic: 1. Communication : Record to improve, not to post Pick any topic and speak for 2 minutes while recording yourself. Watch it again and fix 3 things: filler words, confidence, clarity. Do this for 30 days, you’ll notice a transformation. 2. Networking : Give value before asking Instead of messaging strangers with “Can you help me?”, ask “How can I support you?” People remember those who contribute, not those who demand. 3. Problem-solving: Practice decision making, not perfection Pick any 2 choices, select one within 5 minutes, then evaluate the outcome later. Problem solvers are not those who are always right but they are those who can find clarity quickly. 4. Teamwork : Learn how to disagree respectfully Instead of saying “You’re wrong”, say “I see your point, but here’s another perspective.” Conflicts don’t break teams but disrespect does. ➡️ Soft skills aren’t built in classrooms, they’re built through curiosity, observation and daily practice. If hard skills sharpen your mind, soft skills strengthen your impact. Work on both. Your career will thank you. Follow Swati Mathur for more. #softskills

What's the best way to evaluate the effectiveness of leader development initiatives like coaching, mentoring and training? If we take a common framework like the Kirkpatrick Model, it clearly guides us to measure: 👉 Reaction: Did participants find the experience valuable or engaging? 👉 Learning: Did they acquire new knowledge, skills, or insights? 👉 Behavior: Did their actions or habits change as a result? 👉 Results: Did these changes lead to measurable organizational outcomes? The visual below provides us with a few more evaluation ideas and methods, which are helpful! I particularly like the focus on measuring success with objectives set at the start of the coaching programme (because it guides us to make sure the objectives are clear and realistic). The one I struggle with is "Impact on business performance In my experience, evaluating the direct link between leader development and business results (e.g., profits, savings, or productivity) is difficult and often misaligned with the true purpose of these initiatives. Leader development fosters long-term growth, enhances team dynamics, and shapes organizational culture—outcomes that don’t always translate into immediate business metrics. It’s also essential to manage expectations. If the primary goal of leader development is to see immediate improvements in business performance, it’s worth asking if those expectations are realistic. Initiatives like coaching and mentoring often result in intangible but powerful outcomes, such as: ✔️ Increased self-awareness ✔️ Improved team communication ✔️ Strengthened confidence and competency While these outcomes may not directly show up in quarterly metrics, they lay the foundation for sustained organizational success. This is why setting clear, measurable objectives at the start is so important. If the intended outcomes include changes like better communication or a shift in culture, these should be the focus of evaluation—not solely traditional business performance indicators. Leadership development IS NOT a quick fix for the bottom line. It IS an investment in the people and culture that drive long-term success. What methods or frameworks have you found helpful for evaluating #leadershipdevelopment? Leave your comments below 🙏 Image Source;: Jarvis J (2004) Research Gate

𝐓𝐡𝐞 𝐒𝐞𝐜𝐫𝐞𝐭 𝐭𝐨 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐓𝐡𝐚𝐭 𝐀𝐜𝐭𝐮𝐚𝐥𝐥𝐲 𝐖𝐨𝐫𝐤𝐬? 𝐒𝐭𝐚𝐫𝐭 𝐚𝐭 𝐭𝐡𝐞 𝐄𝐧𝐝. 🏁 I used to think my job as an L&D professional started with a syllabus. I was wrong. Recently, I was tasked with building a learning solution for our Talent Acquisition (TA) team. The goal wasn’t just to "train recruiters"—it was to solve a business problem. Instead of looking at what they needed to know (Level 2), I started with what the business needed to achieve (Kirkpatrick Level 4). The "Reverse" Approach I didn’t start with slides. I started by analyzing Voice of the Customer (VOC) survey results, focusing on various metrics from both Hiring Managers and Candidates. Working Backwards: ✅ Level 4 (Results): I defined the business KPI. ✅ Level 3 (Behavior): Based on the VOC metrics, I identified the specific actions recruiters needed to change—specifically around "Precision Intake" and "Candidate Experience Management." ✅ Level 2 & 1 (Learning & Reaction): Only then did I design the actual training content that addressed those specific behavior gaps. The Result? The training didn't feel like a chore; it felt like a solution. Because I built it based on the actual metrics revealed in the VOC surveys, the TA team saw immediate value, and the business saw a measurable shift in hiring efficiency. The Lesson: If you want your learning solutions to be more than just "check-the-box" exercises, stop asking "What should we teach?" and start asking "What does the data say I need to solve?" How do you use VOC data to shape your enablement programs? 👇 #LearningAndDevelopment #InstructionalDesign #TalentAcquisition #KirkpatrickModel #Enablement #DataDrivenLD #BusinessImpact

"Everyone talks about soft skills, but few know how to actually develop them." Let me be honest - building soft skills isn't about attending one-off workshops. It's about creating daily habits that transform how you interact and think. Here's what actually works: ✅ Start each morning with a 10-minute reflection session. ✅ Practice active listening in every conversation. ✅ Write down feedback after meetings. ✅ Document your daily learnings The real growth happens when you: - Ask for specific feedback after presentations. - Journal about challenging interactions. - Practice empathy by considering others' perspectives. - Observe how successful people communicate. Don't just read about soft skills. Build systems to practice them daily. Here's why this matters: - You develop emotional intelligence organically - Your leadership presence grows steadily - Your communication improves naturally - You become more self-aware Small daily actions create lasting change. Start with one habit. Master it. Add another. That's how you build soft skills that stick.

User Feedback Loops: the missing piece in AI success? AI is only as good as the data it learns from -- but what happens after deployment? Many businesses focus on building AI products but miss a critical step: ensuring their outputs continue to improve with real-world use. Without a structured feedback loop, AI risks stagnating, delivering outdated insights, or losing relevance quickly. Instead of treating AI as a one-and-done solution, companies need workflows that continuously refine and adapt based on actual usage. That means capturing how users interact with AI outputs, where it succeeds, and where it fails. At Human Managed, we’ve embedded real-time feedback loops into our products, allowing customers to rate and review AI-generated intelligence. Users can flag insights as: 🔘Irrelevant 🔘Inaccurate 🔘Not Useful 🔘Others Every input is fed back into our system to fine-tune recommendations, improve accuracy, and enhance relevance over time. This is more than a quality check -- it’s a competitive advantage. - for CEOs & Product Leaders: AI-powered services that evolve with user behavior create stickier, high-retention experiences. - for Data Leaders: Dynamic feedback loops ensure AI systems stay aligned with shifting business realities. - for Cybersecurity & Compliance Teams: User validation enhances AI-driven threat detection, reducing false positives and improving response accuracy. An AI model that never learns from its users is already outdated. The best AI isn’t just trained -- it continuously evolves.

📈 Unlocking the True Impact of L&D: Beyond Engagement Metrics 🚀 I am honored to once again be asked by the LinkedIn Talent Blog to weigh in on this important question. To truly measure the impact of learning and development (L&D), we need to go beyond traditional engagement metrics and look at tangible business outcomes. 🌟 Internal Mobility: Track how many employees advance to new roles or get promoted after participating in L&D programs. This shows that our initiatives are effectively preparing talent for future leadership. 📚 Upskilling in Action: Evaluate performance reviews, project outcomes, and the speed at which employees integrate their new knowledge into their work. Practical application is a strong indicator of training’s effectiveness. 🔄 Retention Rates: Compare retention between employees who engage in L&D and those who don’t. A higher retention rate among L&D participants suggests our programs are enhancing job satisfaction and loyalty. 💼 Business Performance: Link L&D to specific business performance indicators like sales growth, customer satisfaction, and innovation rates. Demonstrating a connection between employee development and these outcomes shows the direct value L&D brings to the organization. By focusing on these metrics, we can provide a comprehensive view of how L&D drives business success beyond just engagement. 🌟 🔗 Link to the blog along with insights from other incredible L&D thought leaders (list of thought leaders below): https://lnkd.in/efne_USa What other innovative ways have you found effective in measuring the impact of L&D in your organization? Share your thoughts below! 👇 Laura Hilgers Naphtali Bryant, M.A. Lori Niles-Hofmann Terri Horton, EdD, MBA, MA, SHRM-CP, PHR Christopher Lind

For years, fine-tuning LLMs has required large amounts of data and human oversight. Small improvements can disrupt existing systems, requiring humans to go through and flag errors in order to fit the model to pre-existing workflows. This might work for smaller use cases, but it is clearly unsustainable at scale. However, recent research suggests that everything may be about to change. I have been particularly excited about two papers from Anthropic and Massachusetts Institute of Technology, which propose new methods that enable LLMs to reflect on their own outputs and refine performance without waiting for humans. Instead of passively waiting for correction, these models create an internal feedback loop, learning from their own reasoning in a way that could match, or even exceed, traditional supervised training in certain tasks. If these approaches mature, they could fundamentally reshape enterprise AI adoption. From chatbots that continually adjust their tone to better serve customers to research assistants that independently refine complex analyses, the potential applications are vast. In today’s AI Atlas, I explore how these breakthroughs work, where they could make the most immediate impact, and what limitations we still need to overcome.