Scrum Alliance Partners with Johns Hopkins for Agile Healthcare Education

Hopkins Engineering's Executive and Professional Education is excited to announce its collaboration with Scrum Alliance. We're partnering to deliver world-class education for global healthcare professionals. 📆 Courses launching in 2026. 🌎 Available globally, online, and on demand. #HealthcareInnovation #AgileInHealthcare #LeadershipDevelopment #ScrumAlliance

Recently, our organization launched a mass certification initiative for everyone with a Cursor license. As someone focused on dramatically improving efficiency and productivity across my organization, I’ve been reflecting on the impact and effectiveness of certifying such a large group at once. It definitely has its pros and cons. Yes, one size doesn’t fit all. Not every user has the same background or needs. There’s effort involved in organizing and tracking the process, and there’s always the risk of superficial learning… the usual cynicism is there… BUT, mass certification ensures that everyone starts with a common foundation, making collaboration smoother and reducing knowledge gaps. It creates a shared language just in time and builds an ecosystem of accelerated and consistent adoption across teams. It also reinforces a culture of continuous learning and professional growth. On the ground, it is much more exciting. Seeing the organization at 20% certification vs. 90%+ certification has been eye‑opening: People who are typically less code‑oriented are now generating code daily to improve efficiency, automate routine work, build dashboards, and essentially “code their way” to better outcomes. Liat Sharon is one great example - she became a one‑person army once she got certified with Cursor 😊. For developers, I see faster delivery, higher‑quality outputs, and a stronger sense of ownership. Teams are innovating more confidently and experimenting more freely. Despite the challenges, I believe mass certification is a powerful way to boost AI efficiency in large organizations. It creates a shared language, accelerates skill development, and helps us fully leverage capabilities like Cursor at scale. #Amdocs #EngineeringLeadership

Being an instructor from the early 90’s hands on learning has always been the piece of the puzzle that make learners think and engage and really look at “how will this impact me and the role I perform?”. Often in my experience you get the really thought provoking questions when the hands on is being taken. When I started using Skilable it just opened up endless possibilities for me, so I had to join the company to enable more customers achieve the same. Case studies like these just confirm my belief.

Day 194| Training Focused Only on Features, Not Workflows One of the biggest reasons product adoption fails in engineering organizations is simple: Training explains what a feature does… But engineers need to know when and why to use it in real projects. During rollouts, organizations often create feature-based training modules covering: • Tool navigation • Menu options • Function explanations But in real projects, engineers think in terms of: ✔ Project deliverables ✔ Compliance requirements ✔ Multi-tool coordination ✔ Design problem solving When learning does not connect to workflow context, adoption drops. Modern AI-driven learning ecosystems solve this by mapping product capabilities to: ✅ Project lifecycle stages ✅ Role-based workflow scenarios ✅ Real engineering use cases The shift needed is from product education → project performance enablement. 💡 Reflection: Does your organization train users on software features… or on solving real engineering challenges? Disclaimer: Views are personal and based on industry observations. #ProductAdoption #EngineeringLearning #AIinLearning #WorkforceTransformation #DigitalEngineering #LearningStrategy

There’s no shortage of information available to PMP candidates. Videos. Practice questions. AI tools. Study plans. But passing the PMP isn’t just about access to information. It’s about support, accountability, and having someone who understands what this process actually feels like. Many of our cohort members come in with a plan. Some have already started studying. What they’re missing isn’t effort. Its structure and human support. ExcelPM360 was designed for professionals seeking a genuine learning experience, not just additional content. We study together. We check in. We adjust our weekly strategy session content based on how you’re actually performing, not just what a dashboard indicates. Because learning is human, and no one should have to do this alone.

Learning maturity doesn’t work like a software upgrade. It’s a ladder: Reactive → Proactive → Impactful → Strategic → Transformative And you can’t skip rungs. David James made an important point: Everything you build at lower levels still matters—but it stops being the strategy. What changes as maturity increases: • Access turns into influence • Content turns into capability • Learning integrates directly into work • Governance prevents regression when leadership changes One line summed it up perfectly: Climbing more than one rung at a time gets dangerous. Adoption isn’t about speed. It’s about stability. If you focused on moving up just one rung this year, what would need to change first? For more real adoption stories and practical frameworks like subscribe to the Adoption Curve newsletter: 

If you lead Learning & Development, this is your unfair advantage. - AI-powered. - Science-backed. - Enterprise-ready. While most organizations are still producing more content, high-performing teams are building learning systems that scale. Because modern learning isn’t about courses. It’s about capability. M.I.D.201 prepares you to design that system. Learn more: https://hubs.li/Q041W1gs0

#CompetencyMapping Legacy training models often fail to translate to real-world proficiency. We engineered a solution for high-stakes environments that replaces static content with tailored video-based learning modules. By architecting a dynamic assessment engine, we shifted the focus to individual pace and performance tracking. This allows for benchmarking critical reaction times and recognition skills, delivering targeted skill enhancement exactly where gaps exist. The result? A high-precision learning path that optimizes workforce readiness while significantly reducing organizational risk. Explore the full Transformation Story here:  https://lnkd.in/duYjX-qD #WorkforceTransformation #EdTechConsulting #LMS #StrategicLearning #HarbingerGroup 

A few questions I can’t stop thinking about. Would love your take ⬇️ At Gorgias, we’re rebuilding our implementation framework from the ground up right now, and it’s got me thinking hard about the future of customer education and enablement more broadly (Romain Lapeyre has been documenting the journey on LinkedIn weekly if you want to follow along 👀). We’re at a point where AI is changing not just what products can do, but how users expect to learn them. Contextual, instant, tailored to their exact situation. And yet the experience of actually learning a complex product still often means jumping between a help center, a community, an academy, a support ticket. Fragmented, and rarely meeting you where you are. The real question might not be whether structured learning still has a place. It clearly does. But can it evolve into something truly unified, where structured learning paths and in-the-moment coaching coexist, and where product updates actually make it into the curriculum before they’re already old news? So what happens to the academy model? → If in-product AI can guide a user through their specific workflow in real time, what’s left for structured education to do? → Is the role of an academy shifting from the expectation that it covers every learner competency (which grows with the constantly evolving product), to something more foundational, building mental models and principles that help users adapt as the product capabilities improve rapidly? → And when product development is moving this fast, can users even realistically keep up? Or is “full adoption” no longer the right goal? → How does structured learning complement the in-the-moment, AI-driven education that’s increasingly happening directly in product, where guidance is tailored to a user’s exact situation and use case? My instinct is that knowledge management, owning the source of truth that feeds all of these experiences, is going to matter more than the experiences themselves. But I also believe there’s something that structured learning does that AI-in-product can’t fully replace. Would love to hear from people working in customer education, enablement, product, and customer success: what shifts are you already seeing? And what do you think holds up?