The Value of Just-in-Time Learning
When we first bought our remote property back in 2017, we aspired to off grid living. Initially we ruled it out due to cost and complexity. It moved to the "someday" list. As we've been watching the demand for energy increase this year, and the costs rise too, we decided to look at solar again.
We used AI at multiple steps during our research and evaluation process. Looking back through conversation histories with ChatGPT and Grok we see questions like:
Help me create a document that details all the elements of my property and the building where I want to install solar panels so that I can share it with solar companies to get a detailed quote.
How can I future-proof my design so that the solar system will serve my needs as I add an electric vehicle?
What do I need to do to be able to view the status of the system via a mobile app, remotely (via WiFi/Cat6) as needed?
Just this week the knowledge gained from iterative learning with AI helped prevent a delay in our solar installation. On a support call with our power company, the person gave incorrect information about the next step. Because we'd done our research, we could clarify, question, and ultimately get the right answer.
The research process hasn't fundamentally changed but using AI to help at each step allowed us to draw on knowledge from a broader set of sources. We always try to get quotes from 3 suppliers when making a big purchase, but with AI it was as easy to find and engage 10 companies.
For us, this solar project became a practical example of something larger we've been observing: the need for a fundamentally different approach to learning.
Things are changing so quickly that the old "just-in-case" learning method, where you would cover a topic in depth and at length in case you needed to know about it, doesn't offer the agility we need in our work.
Adaptability is going to be a differentiator between people who can transition to new ways of working, like leading hybrid people-agent teams, and those who are feeling stuck in roles that are becoming redundant.
We regularly highlight the value of deep learning; there's absolutely still a case for making time to read books and undertake long-term study. But for many of the projects you're asked to work on, a pertinent question is:
What will I need to know in the next 90 days?
That's where just-in-time learning comes in. This approach focuses on learning "on the fly" so you can apply what you learn immediately, which has a bonus benefit of making it stick in your brain.
Think of this approach as raising your hand and asking for the information you need, rather than sitting and listening to a lecture. It's a "pull" approach to knowledge where you need to identify the gap, rather than a "push" approach which has been more typical in work settings in the form of mandatory training.
Working this muscle allows you to upskill quickly, meaning you can take on new projects, add extra value to the people you're working with, or choose the kind of roles you want to take on. Just-in-time learners will have a competitive advantage.
Try this Prompt
Think of a project, responsibility, or skill gap you're facing in the next 90 days. Then try this prompt with Deep Research (ChatGPT or Gemini) or the Researcher agent if you have a Microsoft 365 Copilot license:
Help me understand the rise in just-in-time learning and how I can use these techniques with AI to quickly get up to speed on changing trends or topics outside my area of expertise.
You can also ask AI to teach you while it is helping you with a task, which prompts you to engage critical thinking as you interact with the outputs.
We hope you've found this series on Learning valuable, next week we start a new series on how to be Future-Ready. If you have any questions or topics you'd like us to cover hit reply to this email.
