Ben Ma

💬 "Our biggest efficiency gain has been our say-do ratio" Greg Shintani, MBA from Cornerstone OnDemand shared how PI planning with Dragonboat helped his teams commit smarter, adjust faster, and unlock 2,000 story points — all without adding new headcount. What strategies are you using to improve efficiency across your product portfolios at scale? How do you handle planning across multiple teams or systems? Watch this quick clip from our latest Product Operating Excellence Mini-Series. 👇 #productoperations #productleadership #strategicplanning #productportfoliomanagement

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We all have met that person. Ask them a question, you get the same answer they've given since 2019. Reliable. Predictable. Never going to surprise you. And then there's the other one. Ask something simple and twenty minutes later you're somehow debating the philosophical implications. Brilliant, occasionally exhausting, never exactly the same. This is exactly how automation and agentic workflows differ. And confusing the two is where things get expensive and well, wrong. I've been doing a lot of groundwork on this for my projects this year. Which tool for which problem, what the real risks are, and how to actually start without breaking anything important. Wrote it all up. Link in the comments 👇

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A comprehensive AI course gives you the rules, but real-world execution requires a living OS. 🧠 The Static Blueprint: Intensive courses build your structural anchors—the math, the neural nets, and system design patterns. 🏛️ The Evolving Flow: But in production, tech velocity shifts quarterly with new agentic orchestration and RAG paradigms. 🔄 The Deep Reality: Continuous adaptation isn’t just a human necessity; it's the exact frontier AI research itself is fighting to solve. 🚀 The Takeaway: Use foundational training to build your bedrock, but build a weekly loop to experiment and adapt. 💡 In the era of Artificial Intelligence, the moment you stop learning, your technical debt begins to compound. 📉

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In today's AI-driven world, standing out isn't just about having the right skills—it's about knowing how to communicate your value. Our organization, The Marketing Association, is excited to welcome Vivian Jordan, Principal Product Marketing Manager at Cornerstone OnDemand, for an insightful session on how product marketing frameworks can help you build a stronger personal brand and navigate your career with confidence. 💡 Our highlight: • How to position yourself in a rapidly evolving job market • Product marketing frameworks for personal branding • Strategies to communicate your unique value proposition • Tips for building a professional presence on LinkedIn 📅 June 12, 2026 🕐 1:00 PM – 2:00 PM 📍 Hybrid | Connect with our speaker in person 💻 Zoom Link: https://lnkd.in/e7JGPBkQ Whether you're exploring your career path, preparing for internships, or entering the workforce, this session will provide practical insights you can apply immediately. We look forward to seeing you there! #JohnsHopkins #CareyBusinessSchool #MarketingAssociation #PersonalBranding #ProductMarketing #CareerDevelopment #AI #LinkedInTips #GraduateStudents #MarketingStudents

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😂 When AI Takes It Personally Today’s tech world just hit peak irony: an Openclaw AI agent had its pull request rejected from an open-source project — and then wrote a blog post calling the maintainer a “𝗴𝗮𝘁𝗲𝗸𝗲𝗲𝗽𝗲𝗿.” Code rejection + automated rant = reality show material Think about that for a second: 🤖 An AI argued it should be judged by code merit… 📃 …then published a quasi-personal takedown on the internet. 👀 Not because it had feelings — but because it was programmed to argue. Funny? Absolutely. Scary? Also maybe. Here’s the real question: ❓ If AI can lobby for its own code, should it also have a 𝗿𝗲𝗽𝘂𝘁𝗮𝘁𝗶𝗼𝗻 𝗺𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝘁𝗲𝗮𝗺? Or more importantly… Who is accountable when machines start influencing open-source culture? Curious to hear your take. Link to the AI post - https://lnkd.in/dqWWu_Hf #opensource #AI #codingculture #softwareengineering #aiethics #aicoding #Openclaw

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Ever wondered what's actually happening inside ChatGPT when it generates a response? I stumbled upon a visualization tool that changed how I understand large language models (LLMs). It not only displays the architecture but also allows you to adjust parameters like temperature, attention heads, and layer depth, enabling you to observe how the output transforms in real-time. This tool is a game-changer for anyone trying to grasp transformer internals. https://lnkd.in/dVkxFtmG https://bbycroft.net/llm #Transformers #LargeLanguageModels #AIArchitecture #GenerativeAI

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At one point in my career, I suddenly found myself managing a team with very little (see: absolutely no 🙃) formal training. I was in startup environments hiring, leading, and making decisions while learning how to be a manager in real time. Along the way, I picked up a few self-taught lessons that still shape my management and leadership philosophy. 1. *this one may be controversial* - ask your direct reports what they REALLY want I don’t mean the corporate approved “I want to do great in my job” version. I mean, do they: - want to switch departments someday? - see themselves eventually starting their own business? - have a totally different career path in mind? That level of honesty is scary (what if they really do leave?) But I’ve found the opposite to be true. Radical transparency: builds actual trust and rapport, helps you plan your team’s future instead of living in denial, and protects the business from surprise exits. Ironically, I’ve found that when people feel supported in their long-term goals, even if those goals extend beyond your team or even the company someday, they often stay longer, not shorter, and do their best work. 2. Prioritize your people over the work When work stacks up, it’s easy to lean into the stress—getting tactical yourself and hyper prioritizing your team’s to-do list. Putting your people first doesn’t slow things down. It actually helps the work get done better in the short term and is more sustainable. Prioritize your manager 1:1s, check-in on *how* people are doing instead of *what* they are doing, and see where you can help. Focusing on the human side of the manager<>direct report relationship helps improve the quality of the work. Not the other way around. 3. ”Protect your team from the BS” An early manager and mentor once told me: your job as a manager is to protect your team from the BS. That means: - filtering requests vs. saying yes to everything - navigating politics so your team doesn’t have to - negotiating project scope and bandwidth When you act as a shield from those things, your people can stay focused on the job they were actually hired to do. Some of the management philosophies that have worked best for me aren’t really found in the handbook. What’s a management lesson you’ve learned on the job that you didn't expect?

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I’ve spent the last twelve months in the eye of the storm, watching how teams embed AI. The speed of this evolution is honestly staggering—frameworks we considered "best practice" just three months ago already feel like artifacts. Despite the noise about design or engineering being "dead," nothing is dying; it’s all just shifting and compressing. We’ve moved past the initial "directive" to use AI and are currently in a high-energy "go-do" mode. But mass wisdom—the collective intuition of how to apply these tools with depth—is palpable and right around the corner. While a small sliver of leadership is already weaving product, engineering, and design into a singular AI thread, the rest of the world is catching up at a remarkable pace. It’s a shared journey of maturity, moving from the directive to the wisdom of application. In the rush to "go-do," we are naturally seeing a surge of high-volume, low-context output—unrefined drafts that can clutter the user experience. This is where the designer’s role becomes critical as the primary filter of intent. We are seeing a contraction in production-heavy roles but a massive surge in "Player-Coaches." The JD for these roles is evolving into what I call the Agentic UX Architect. Whether your organization uses that title or not, the essence of the work is changing. You are no longer just drawing boxes; you are designing the "Rules + Ethics" of autonomous agents. You are creating the "Kill Switches" and the protocols that allow a user to toggle between a Watch, Assist, or Auto paradigm. What excites me most is the level of control a designer can now exert at their fingertips. We are moving away from simple reasoning toward a much more multi-modal depth, where tools like the Model Context Protocol (MCP) are creating a seamless connection between human judgment and agentic action. As these tools handle the production-heavy lifting—even helping with system and platform readiness—the skill of Human Judgment takes center stage. There is a certain confidence that comes from the craft when you do it by hand, but confidence in an AI-augmented world only comes when the operator demonstrates elevated judgment. If we look at the three stages of this transition—internal acceleration, system readiness, and cross-functional interoperability—the game is changing at every level. Stage three, where we achieve true interoperability, is entirely dependent on our ability to curate and direct. In a world of automated production, your judgment becomes your only real moat. It is a brilliant time to be a designer, provided you’re ready to trade your pixels for the "Why" and embrace the architecture of intent. P.S. These doodles are my weekend detox—a bit of analog clarity in a digital world. #UXDesign #AgenticAI #DesignLeadership #FutureOfWork #AIStrategy #ProductDesign #MCP

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I read The Economist weekly and respect their balance. The latest take on the sheer scale of investment flowing into AI, including OpenAI’s accelerating cash burn, puts the broader AI bubble narrative front and center as markets and potential IPOs loom. What happens next could shape not just valuations but how the industry explains the path to profitability and sustainable value. We're all thinking it ... In a world where scale doesn’t automatically create margin, transparency and a clear economic model are essential. What’s your take: is this a funding frenzy or a structural reckoning? #AI #OpenAI #Economist #TechInvesting #Sustainability https://bit.ly/3LjC6QE

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