Everything is changing
And the way we learn will never be the same.
Hello! The Learning Stack is back. And no – this isn’t an April Fool.
It’s been a year since the last issue, and I’m bringing it back with something bold (literally and figuratively) to kick things off:
FORGET EVERYTHING YOU KNOW ABOUT LEARNING
(Sorry for shouting – but this is important.)
Learning isn’t evolving – it’s being rewritten.
I’ve been in the corporate learning space for 30 years, and I’ve never seen a shift like this – it’s both exciting and a little scary.
For the last few decades we have thought of “learning as an event” and rarely “learning as a system” – but that’s where we are heading and we all need to jump on board.
As we move into this new world of Agentic AI, we need to think about how these agents can unlock human capability further.
I am not being a doom monger here – we should see this as a huge opportunity for our area of business. We get to drive the future of learning in our respective companies.
Here are examples of how I believe things are changing:
Persistent Learning Companions, Not Courses
In a traditional world, learners “attend” learning – courses, webinars, certifications. In an agentic world:
- Each learner has a personalised AI learning agent **like a long-term coach, mentor, and performance analyst rolled into one.
- This agent knows your goals, learning style, current projects, and nudges you with the right microlearning, feedback, or reflection prompts at the right time.
Imagine: A dynamic feed of learning moments embedded across your day—surfaced by an agent that evolves with your role and performance.
Learning Loops, Not Learning Events
- AI agents can detect context and performance gaps, then close the loop with tailored learning nudges.
- Example: After a sales call, an agent offers a quick simulation based on a weak objection handling moment, pulling from both the call and your recent learning.
This creates a loop of sense–diagnose–learn–apply–reflect, repeated continuously in the flow of work.
Systemic, Data-Driven Orchestration
- AI agents act as a coordination layer across tools: LMS, LXP, CRM, HRIS, and performance management.
- They track skill progression, alert managers to developmental needs, and propose interventions—whether that’s content, coaching, or a stretch project.
Learning becomes a responsive, living system, where agents surface friction and opportunity continuously – not quarterly.
Agent-Led Personalisation at Scale
- AI agents build skill profiles that evolve as you complete tasks, receive feedback, and engage with learning content.
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These profiles drive recommendations for:
- What to learn next.
- Who to collaborate with (e.g. skill-based matchmaking).
- Where to apply knowledge in your current role.
This is self-directed learning with structure – the system adapts to you, while ensuring alignment to business-critical outcomes.
5. Learning as a Layer of Work Itself
In an agentic system, learning is no longer a layer on top of work—it’s a layer within it.
- AI agents embed microlearning, simulations, coaching nudges, and feedback in your actual workflows Slack, VS Code, Salesforce, etc.
- Reflection, assessment, and reinforcement are designed into your tools and tasks.
You’re always learning—but often without “doing a course” at all.
This isn’t evolution. It’s a new operating system.
As learning professionals, we are not tweaking around the edges – we are rewriting the rules. Agentic AI is not a new tool in the toolbox; it’s the architect of a fundamentally different system, where learning becomes invisible, embedded, and continuous.
The challenge now is not whether we adopt this shift – but how fast we can experiment, adapt, and reimagine what learning means in this new paradigm.
So ask yourself – and your team – not “What course should we build next?” but:
“What system are we designing that learns as fast as our people need to?”
Because in this new era, those who learn fast, win.
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P.S.
If this edition gave you something to think about, consider forwarding it to a colleague or friend who’s also navigating this shift in learning. Every share helps bring more sharp minds into the conversation – and that’s how we move the whole field forward.
One quick ask before you go:
I’m rebuilding The Learning Stack to be as useful and challenging as possible. If you’ve got a minute, I’d love to hear from you.
Just hit reply and share:
- What topics you’d like to see me explore next
- What stood out most to you in this edition
I will read and respond to every one.
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