Learning is non-linear, so why are so many L&D professionals thinking in straight lines?

The promise of a new year brings with it time for reflection and review of years past.

And yet the problem with all that's new is held within the bright and shiny promises of the future - always just out of reach. As we look to the 'future of learning' what stand out to me is this; we know learning is non-linear now, and yet a plethora of solutions continue to present linear models stuck in the classrooms of the past. Tools and technology will never matter more than the thinking we apply to those tools. It's not enough to buy the latest platform unless we change how we think.
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A quick story about Twitter.
​In 2002, while working for Citigroup, I asked my manager if I could use a new thing called Twitter to help my new hires continue their learning after their three weeks of training had come to an end. My idea was rejected based on a lack of understanding about the technology, and an attachment to the idea that the learning was already 'completed'.

• So, what was my idea? I wanted to use Twitter to create 'Classrooms' for each graduating group of new hires that they could 'join' at their discretion. Using the free Twitter app, which many learners already had on their mobile device, I wanted to seed each classroom with reminders about banking and finance laws and regulations, FAQs, terms and technical information. All the shared content would be publicly available, consolidated to reinforce key concepts for new hires.
• For example, a simple message to the Classroom like, "Remember, The Gramm-Leach-Bliley Act (GLBA) is a law that requires financial institutions to protect the privacy and security of their customers' personal information. The GLBA was enacted in 1999 and is enforced by the Federal Trade Commission (FTC)." 

The vision I had was to recognize on-the-job performance would be improved with relevant coaching, quick-tips, and easy reminders from concepts shared in new hire training. I knew if I could get approval my new hires would gain value, improve their call handling, and feel supported even though 'training was over', learning could continue. The rejection of this idea brings us to today, the start of 2025.

Break the Linear Thinking Habit.
As AI floods every headline, timeline, and news feed for many good and exciting reasons, I'm reminded that how we think about learning is what has to change more urgently than any new platform we might be called to adopt. From AICC, to SCORM 1.2, 2004, BigTinCan API, to xAPI, VR, AR, MR, XR to AI and beyond... the same thinking has faced new solutions time and again.

What do I mean when I say 'the same thinking'?

• How should we track the learning?
• What's our completion target look like?
• How many attempts should a learner get?
• What kind of feedback will selections provide?
• Where should we store and access the transcripts?

These questions are linear in nature and seek to complete a track and declare 'mission accomplished', often with little evidence of applied skill or content relevance. Are there cases where this thinking is useful? Yes, primarily related to certifications and regulated environments where success is determined by content consumption, not application. Most learning lacks relevance because it's not applied in the flow of work or at a specific time of need for a learner. No matter the task, when you reach for knowledge, relevance is what matters most, and this is why we have to change how we think about the learning at its core.

In circular learning, value comes from relevance, not volume.
Imagine you are standing in a circular library, free of corners you find you're able to swiftly access the knowledge and information you need, in the moment, to help you succeed. Now, further imagine the relevant content is surfaced first, and most often, with a rapid deprecation of content that is not 'on trend' related to your current landscape. Take this a step further and envision a clear use case for AI that amplifies a learner's query to curate content with value through relevance, instead of promising value through volume. Learning that is circular is driven by relevance; not volume. It's about application with meaning. The promise of technologies like LLMs, AI, and other agentic solutions can only be realized by those willing to think differently about the function of learning, the definition of performance success, and the operational value that will govern effective learning strategies over coming decades.
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What changes and what remains?
What must change is how learning interventions are defined from the very start, in order to link any planned actions to one key metric: relevance. Through deeper analysis of audience needs and greater understanding of use cases driven by various personas, learning professionals will define valid strategies that are lean and effective. What remains unchanged is a range of core, linear topics, that meet a specific need, related to black and white topics... which should become a minority of the content any learning organization produces. These topics may be related to SOPs, fixed legal doctrine, or regulated environmental content that has defined expiration dates and renewals.

How to move beyond linear thinking.

• As a learning professional ask yourself: "What evidence do I have that the learning intervention can or will be relevant for my audience?"

This question will reveal time and again whether an intervention is value or merely volume. This question can quickly impact any idea that may be untethered from a clear value proposition so it can be adjusted before it is deployed, or cancelled if that is the best decision. This question is also about relationships and service; to strengthen the relationship each stakeholder has with your learning organization, relevance must drive strategy. Through relevance, value becomes more and more obvious to everyone engaged.

The challenges ahead.
Changing how we think about learning and employee performance is both a tactical and strategic shift that will be met with a range of challenges. Past investments, sunk costs, lack of creativity among peers, fear of change, slow or delayed responses, stakeholder engagement delays, and time used to maintain existing infrastructure. These and other challenges can be addressed gradually by starting small.

How to champion the circular learning org.

1. Seek relevance related to a learning request or intervention.
2. Define success based on well-defined personas and user definitions.
3. Work to decrease content volume and increase value with refined resources.

I believe the future is bright, I also believe it's already here and needs are attention, not as a long-term play, but as an urgent call to all professionals in the world of corporate learning and employee development. We must upgrade our thinking, before we upgrade another set of tools, if we truly want to drive meaningful impact for learners across our organizations.

All the best, 
Phoenix R. Cavalier, Founder of Verus Learning

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