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In this article, Cara Elizabeth introduces a new paradigm for learning based on the latest Neuroscience and Organisational Design research.

The model is called a Development LOOP, which is a cyclical and flexible approach that breaks learning into four stages:

Lay → Operate → Organise → Propel

Instead of treating growth like a straight line, Development LOOPs treat learning like a living process, one that adapts to pace and goals in real-time.

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Learning isn't what we thought it was

A few weeks ago, I wrote about how learning faces massive disruption right now. This disruption rings especially true when you look at the ways AI is reshaping work.

But I realised something interesting.

It's not just our learning tools that need an upgrade, but how we think about learning altogether.

Our paradigm of learning needs a reboot.

Many of us grew up with the idea that learning is something you do in school, during training, or in the context of significant career changes. But that mindset doesn't match how the world works today.

The truth is that most people don't love change. Psychologists like Samuelson and Zeckhauser refer to it as the Status Quo Bias. We stick to what we know, even if it's not working. It's how our brains protect us.

But work is moving faster than ever, and companies are racing to develop tech at lightspeed.

People are expected to keep up. But we're only human.

Something's got to give.

We need a way to learn that aligns with how people work today and can adapt to tomorrow's needs as well.

The idea of a Development LOOP is inspired by how scientists test ideas and how designers build prototypes. We wanted to apply that same logic and turn it into a simple mental model that leaders could keep in their everyday toolbox. One that remains solid in a fluid world.

Breaking progress into small, repeatable cycles makes change feel less overwhelming and more doable. It gives people room to try, adjust, and move forward in a way that's practical, flexible, and human.

TL;DR

→ A LOOP is a simple, repeatable learning cycle in 4 stages:
Lay → Operate → Organise → Propel
→ Based on research from prototyping, design, and behavioural science
→ It matches how people really learn in fast-changing environments
→ Helps teams build skills, improve collaboration, and grow careers
→ Supports a learning culture that adapts over time

Goodbye Career Path

We have a problem.

People are still using the terms "career ladder" or "path." Even Gen Z. Just take a look on TikTok.

These were first popular over a hundred years ago, and somehow, they're still hanging around.

The Career Ladder is a simple concept: start at the bottom and climb to the top.

Growth is in one direction: up.

That worked when industries were stable, roles rarely changed, and success was about following a clear, fixed path. But why are we still clinging to this metaphor today?

Work doesn't look like that anymore. Now, skills can become obsolete within a matter of months. It's time to wake up.

Newer models, like career lattices and webs, have been proposed. These models accommodate lateral moves, short-term role swaps, skill-based projects, and nonlinear paths. So people can move sideways or even take a step back.

Unlike a ladder, these models are:

→ Multidirectional: Career movement happens in all directions.
→ Co-created: People shape their path rather than just following a pre-set career.
→ Feedback-rich: Teams build learning into everyday workflows.
→ Interconnected: Roles and skills evolve together, with no siloes in sight.

Although this approach originated decades ago (Gore & Associates introduced it in the 1960s), it aligns more closely with modern work than the ladder.

Companies like Buffer, Spotify, and Deloitte use their versions of these concepts. For example:

→ Dual career tracks for leadership and technical growth
→ Internal mobility programs
→ Project-based development instead of static job titles

And the results speak volumes:

✓ Stronger skills
✓ More engaged people
✓ Teams that grow together and stick around

A New Way To Think About Career Growth

One model for work that stood out came from MIT Sloan's research.

Their team studied how companies are rethinking their approach to career development. Instead of the usual top-down approach, they describe what's called a "Workforce Ecosystem."

It's a flexible network of people, roles, and skills that stretches the limits of earlier models. The ecosystem aligns more closely with how people work today, across teams, tools, and time zones.

What they found:

Led by Elizabeth Altman, David Kiron, and Robin Jones, the team found that nearly 90% of global executives now manage talent using this kind of approach.

They use AI and data to:

→ Track skills in real-time
→ Spot skill gaps early
→ Connect people to the right projects or learning opportunities based on what they need right now

So, what's different about this? Here's what sets the top companies apart:

✓ Learning happens during work, not just in scheduled training
✓ Support is personalised based on current goals and skill gaps
✓ AI surfaces relevant lessons as and when needed
✓ Learning becomes cultural and just part of how a team works

These macro findings got us thinking.

At Superhumxn, we encounter many growing companies that aim to achieve similar results. Still, they struggle to access a practical mental model that helps them create this kind of learning experience.

It sparked the idea of the Development LOOP.

So, What Is A Development LOOP?

Skill Development LOOPs are a micro tool for accelerated learning.

They utilise a simple, repeatable framework that leaders can apply to support learning in the workplace. We designed them for fast-paced environments where traditional training can't keep up. Use the model when you face uncertainty, lead through change, or try to improve what matters.

Instead of following a rigid learning plan, Development LOOPs enable growth through short, focused cycles.

It's like an Agile Sprint but for personal development.

Why They Work:

Unlike traditional career models, Development Loops are:

→ Flexible: They adapt to needs.
→ Actionable: You learn by doing, not just by reading or watching something.
→ Sustainable: Growth happens incrementally, which helps reduce burnout.
→ Human: Built around how people think, work, and grow.

What They're Not For:

✗ Low-autonomy, high-stakes environments: This is an iterative process that requires a degree of risk tolerance and psychological safety.
✗ A one-time solution to solving complex challenges. They require repetition and practice to benefit the learner.
✗ Passive reflection or journaling: This is a structured tool linked to action and real-life feedback.

How It Works:

LAY

Lay the foundation for learning.

Start by getting clear on what matters. Think of this stage as choosing the right approach before taking action. Do you understand the challenge correctly?

Sometimes, you might need to "clear your cache" and strip away outdated logic before rebuilding. Or unlearn before you can learn.

Lay is about:

→ Fully understanding the challenge.
→ Getting intentional about how you want to learn and develop.
→ Prepping your mindset based on your capabilities and learning preferences.

2. OPERATE

Operate on the plan.

Try it out, experiment. Observe what happens, then adjust. Now that you've clarified the challenge in the LAY stage, it's time to get your hands dirty.

Pick one thing to test. Like:

→ Giving feedback in a different way.
→ Testing a new decision-making style in a team meeting.
→ Running a quick scenario to build a skill like discernment or critical thinking.

You're not aiming for perfect. Gather feedback and iterate.

3. ORGANISE

Organise your insights.

Make sense of what just happened. Reflect and break it down.

Translate your experience into insight. Reflection provides the return on investment (ROI) of your learning.

After every test or attempt, pause and ask:

→ “What did I try?”
→ “How did it land?”
→ “Why did that happen?”
→ “What would I change?”

Note any patterns in a learning log, and pull out what's useful. Organise these around the context, e.g. leadership.

4. PROPEL

Propel to the next level of learning. Turn insight into momentum.

You've reflected and seen what worked and what didn't. Now it's time to do something with it.

This stage is about evaluating your insights:

→ You may need to frame the challenge differently.
→ Could this task be automated (through AI?) So, the next LOOP of learning should focus on this instead.

Question and critique your thinking before deciding whether to repeat another LOOP.

Then, decide whether to repeat the cycle based on an automation calculation:

Will repeating this cycle challenge me in a new way or develop additional skills? If yes, then repeat. If not, this is a process that should be automated, using AI if appropriate or available.

Our Learning Model

Want to try it out IRL?
Download our Development LOOP guide **here**.

Stay Flexible

We designed Development LOOPs to be flexible and straightforward because people learn in different ways:

→ Some people like to dive in and learn as they go.
→ Others prefer to observe, think, or research before acting.
→ Lots of us bounce between the steps, depending on the complexity.

There's no one right way to learn, so adapt and use the model in a way that suits you best. What matters is that you keep up the momentum in a way that feels natural to you.

Each LOOP builds on the last, so development feels connected and not like a bunch of random learning moments.

Learning By Doing - Why It Works

The idea behind the Development LOOPs builds on something researchers have known for decades:

We learn best by doing.

One of the most influential models in this space is David Kolb's Experiential Learning Theory. He found that real learning happens through experience, not just instruction.

Kolb's Four-Part Learning Cycle:

Concrete Experience: Try something in the real world.
Reflective Observation: Think about what happened.
Abstract Conceptualisation: Make sense of what you learned.
Active Experimentation: Test out new ideas and repeat.

Why It Works:

✓ You retain more by applying knowledge right away.
✓ You build practical, transferable skills.
✓ You become more adaptable because you've trained your thinking, not just your memory.
✓ Reflection helps you turn today's actions into tomorrow's insights.

Development Loops vs. Kolb's Model

Development LOOPs build on Kolb's foundation, but we specifically designed them for today's fast, AI-driven, project-based environment.

Kolb's
Experiential Learning Cycle
vs.
Development LOOP

IRL Example

Rethinking onboarding using Development LOOPs

Major transitions at work create ideal opportunities for growth. For example, starting work at a new company. Instead of overwhelming new joiners with information and expecting them to "hit the ground running," you break the experience into manageable, repeatable steps.

The Typical Onboarding Experience

→ New hires sit through hours (or days) of intensive training.
→ Companies flood them with information, most of which they forget before ever using it.
→ The learning feels disconnected from the actual work.

Here's what onboarding looks like using a LOOP:

1. LAY

Remove any existing assumptions. Set the foundation by getting clear about what to learn and why it matters.

LAY isn't about "orientation." It's about narrowing the field so people know what's worth paying attention to. In complex roles, this means mapping unknowns, setting expectations, and offering a mental "scaffolding."

💡 Ideas:

→ A "Learning Zones" map that separates fixed knowledge from areas of flexibility.
→ A pre-brief asking: "What do you already know about our product/data/problem space? What are you unsure about?"
→ A systems diagram of core dependencies (e.g. for engineers: how internal tools, deployment pipelines, and API calls interact)

2. OPERATE

Break down complexity through micro-exposure.

Now, it's time to get hands-on.

💡 Ideas:

→ Join a meeting or take ownership of a minor, isolated issue
→ Conduct a low-risk test with guidance from a peer
→ Run a mini-experiment: e.g. "Try to replicate this dataset and log the blocks you encounter."

3. ORGANISE

Make sense of what you’ve learned and spot any patterns.

This stage is about sense-making, not just reflection. You help the learner begin to notice patterns, gaps in their current model, or contradictions between what they expected and what they're observing.

💡 Ideas:

→ Ask: "What's one thing you thought was true about how we do things that turned out differently?"
→ Create a pattern map: "What terms, tools, or concepts do you keep encountering?"
→ Highlight touch-points for gathering feedback: Where do decisions get made? What patterns do you see across sprints or customer issues?
→ Build a running glossary or mock-up of their mental model (or thinking) so far (this is esp. useful for machine learning, security, or dev-ops roles)

4. PROPEL

Apply your insights and evaluate progress.

PROPEL is the decision-making stage. Based on the patterns uncovered in ORGANISE, what changes do we need to make in the learning process? What can be automated, deprioritised, or reframed? What should feed into a new learning LOOP?

💡Ideas:

→ Build a custom onboarding module for frequently misunderstood systems.
→ Reframe a challenge: "I thought onboarding was about mastering tools, but it's really about understanding the 'why' behind our work."
→ Identify something to streamline: "I created a script to speed up local setup based on my notes."
→ Move on to a second LOOP, for example: "Next, I'm going to dive deeper into system observability and logging."

Why This Works

A 2023 study by Deloitte found that companies using iterative, embedded learning during onboarding were much more effective than those using traditional training methods.

Why is this model different?

There's no shortage of learning models available, but some can feel abstract or disconnected from the way people work today.

We created Development LOOPs to fill five key gaps in the way we believe you can approach learning at work:

1. They provide a transparent, repeatable process
When people know what to expect, it reduces uncertainty and calms the brain's threat response.
Small wins release dopamine, reinforce motivation, and create momentum. These small wins build lasting habits.
2. They put people in the driver's seat
Development LOOPs are co-created. People choose their focus based on tangible goals and feedback.
A recent article by Entrepreneur explains the Neuroscience behind when people feel in control. Essentially, they're less resistant to change.
3. They're practical
The model integrates learning into real everyday work.
4. They help navigate growth
They act like a map. They show what's next and help track progress. Instead of aiming at one big leap, people move through small, reflective cycles that build confidence.
Each LOOP reinforces learning with feedback, which helps keep pace.
5. They're based on science
This model works with how the brain learns:
→ Feedback builds awareness.
→ Choice reduces resistance.
→ Repetition reinforces long-term growth.
LOOPs guide change in a way that feels natural and sustainable. In short, they make complex things feel doable.

Your Environment Matters

Even the best learning system won't work if the culture doesn't support it.

Any learning model needs the right environment or foundation to achieve the best results.

A study in The Learning Organisation Journal found that continuous learning only sticks when adaptability is part of the culture.

What That Looks Like in Practice:

→ Learning daily is part of the work.
→ Knowledge is shared across teams and roles, not siloed.
→ It's safe to ask questions, try things, and even fail.
→ Curiosity is encouraged.
→ Leaders don't just talk about learning, but they model it.
→ Reflection and experimentation are how things get done regularly.

For people to grow, they need a culture where leaders expect, support, and reward development.

How Tech Helps

The LOOP cycle is a strong foundation, but tech is what makes it scalable and sustainable.

Here are two key tools for making that happen:

1. Adaptive Learning Platforms (ALPs)
These are innovative learning systems powered by AI. A study published on ArXiv highlights their power in improving both training and education.
Think of ALPs as personalised coaching engines.
During the LAY phase of a LOOP, an ALP might:
→ Recommend lessons to close a specific skill gap
→ Suggest what to do next based on progress so far
→ Help people create a learning plan at their own pace
It removes the guesswork and helps people focus on what matters.
2. Nudge Technology (Nudgetech)
Nudgetech uses small, well-timed behavioural prompts to keep people moving without added pressure.
Some examples could be:
→ A Slack message reminding someone to reflect
→ A pop-up after a task suggesting how to apply what they learned
→ A gentle push to try a skill in their next meeting

What nudges do:

→ Trigger timely action ("Try this today")
→ Prompt reflection ("What stood out from that experience?")
→ Reinforce progress by celebrating small wins

Research from the Josh Bersin Academy found that companies using nudges build skills 3x faster than those relying on traditional training alone.

Tech done right can completely overhaul your learning processes.

Make Learning Last

According to the NeuroLeadership Institute, building a new habit takes time—around 63 days of consistent effort, to be exact.

So, if you want the lesson to stick, the key is consistency.

Here's how to make it work:

Start small
→ Pilot with one team or department. Keep the focus tight and manageable.
Show success
→ Share quick wins, quotes, or stories from the team to build momentum and spark curiosity.
Keep it simple
→ Rather than creating a whole new system of learning, build loops into things you already do (like 1:1s, project retros, or weekly planning).
Lead by example
→ When leaders commit to the process of learning, others are far more likely to follow. Learning sticks when it's built into real work, led by real people, and repeated enough to become second nature.

Make It Stick:
Learning Routine

→ Start small
→ Track quick wins
→ Build habits
→ Celebrate every success
→ Reflect often
→ Make it personal
→ Repeat as needed

These days, careers don't follow a straight path. Hard skills expire quickly. Priorities change overnight.

So, why are we still relying on one-way models to guide our learning?

Development LOOPs offer an alternative approach that reflects how learning happens in the brain: through repetition, reflection, and real-world application.

What learning tools have you tried? Share your stories in the comments below.

How To Learn Fast In A Fast World