I’ve been battling a Babylon.js camera control issue for days. Mouse events vanishing into abstraction layers. Documentation that assumes you already know what they forgot to document. My AI coding partner cycling through increasingly desperate suggestions like an anxious teenager.
And in this mess, I discovered how learning actually evolves in the AI age.
Here’s what no one tells you about working with AI: The most profound learning happens not when AI gives you perfect answers, but when you’re both stuck. When the problem exceeds both human pattern recognition and AI’s training data.
In my camera control adventure with Babylon.js - Microsoft’s gift to the 3D web community, Apache-licensed and community-driven - I hit that beautiful edge:
- AI’s recursive searches hit dead ends
- My 30 years of programming experience found no familiar patterns
- Documentation assumed knowledge it never provided
- Event handlers worked… except when they didn’t
So we slowed down. Way down. Started mapping every mouse event, tracing every coordinate transformation. The AI stopped trying to be brilliant and started being curious. I stopped expecting instant solutions and started teaching the AI what I was seeing.
The explosive intersection of passion, ambiguity tolerance and paradigm shifts - where the mind of the learner genuinely expands, and the contextual frame of the AI mirrors that expansion.
This is it. This is the moment traditional learning can’t capture. When human confusion meets AI limitation, something magical happens: we both grow.
This is the learning pattern no LMS measures:
- Traditional Platform: “Complete this Babylon.js course” Reality: “Why does onPointerObservable behave differently after camera rotation?”
- Traditional Metric: “Course completed ✓” Reality: “Spent 3 days teaching AI to help me debug something that ‘should’ work”
- Traditional Outcome: “Knows Babylon.js” Reality: “Understands the messy edges where documentation fails and creativity begins”
This is why I’m genuinely excited about the upcoming keynote between Majd Sakr and Amit Dayal at Adobe Learning Summit.
Majd brings the perfect lens - a Carnegie Mellon professor who built cloud computing labs before joining Accenture LearnVantage. He’s seen learning from both sides: the academic ideal and the enterprise reality. When he talks about gen AI revolutionizing skill-building, he’s not selling consulting speak - he’s lived the gap between what we teach and what we need.
And Amit? Here’s someone who’s led product innovation at Oracle, Yahoo, Samsung, and now runs a global learning business at Adobe. He understands that learning platforms must evolve from content pipelines to intelligence partners. Leading teams across continents, he knows the messy reality of scaling learning across cultures, time zones, and wildly different contexts.
The conversation I’m hoping they’ll have:
- What happens when we stop pretending learning is linear?
- How do platforms support the beautiful mess of human-AI collaboration?
- Can we measure growth that happens in confusion, not completion?
Your LMS measures completion. But real learning happens in the patient investigation of subtle patterns. In teaching AI what it doesn’t know while discovering what you don’t know either.
The future learning platform isn’t one that eliminates these struggles. It’s one that recognizes them as the highest form of learning. Where “I don’t know, let’s figure this out together” becomes the most valuable educational moment.
🎯 Don’t miss this keynote conversation about learning’s real evolution 📅 September 23-25, 2025 | Las Vegas 🔗 https://adobe-learning-summit.elearning.adobeevents.com/
Maybe the measure of a great learning platform isn’t how smoothly it delivers answers. Maybe it’s how gracefully it helps us navigate the questions neither human nor AI can answer alone.
That’s the conversation I believe Majd and Amit will bring to life.
#RealLearning #AICollaboration #LearningAtTheEdges #AdobeLearningSummit