What is vibe coding?
In simple terms, vibe coding is using AI to help create code from natural language instructions.
Instead of manually writing every line of code, someone describes what they want the interaction or tool to do, and an AI coding assistant helps generate the code. In an elearning context, this might be a small HTML interaction, a quiz, a branching scenario, a calculator, a simulation, a custom Storyline JavaScript trigger, or even a standalone micro module.
In an elearning context, vibe coding could look like:
- A short scenario where learners make decisions and see consequences
- A product knowledge activity with custom feedback
- A calculator or diagnostic tool embedded inside a course
- A custom interaction that sits inside Storyline, Rise, Moodle or another LMS environment
- A lightweight standalone module built from scratch using HTML, CSS and JavaScript
Where vibe coding works well in elearning
Vibe coding is particularly useful when the learning need is clear, focused and contained.
For example, it can work well for a short compliance refresher where learners need to practise identifying the right action. It can also be useful for a product knowledge interaction, a simple workplace decision tree, or a small tool that helps learners apply a process.
It is also useful when the output does not need to carry too much complexity. If the module is short, the logic is simple, the data requirements are minimal, and the learning outcome is clear, vibe coding can be a practical accelerator.
This is why micro modules are such a natural fit.
A micro module can be designed around one specific learning outcome. It can be short, targeted and interactive. It does not always need a full course structure. In some cases, a vibe coded module can be created quickly and then embedded into an LMS, a web page, a Rise course or a Storyline shell.
That does not mean every micro module should be vibe coded. But it does mean this is one of the most practical areas to explore.
What a vibe coded elearning activity might include
A vibe coded elearning asset could be simple or more sophisticated, depending on the use case.
For example, it might include:
- A branching workplace scenario
- A drag and drop sorting activity
- A short quiz with custom feedback
- A risk rating calculator
- A policy decision tool
- A product selector
- A coaching conversation simulator
- A compliance refresher interaction
- A web based job aid
- A custom widget embedded inside a broader course
These examples sit somewhere between standard authoring and full custom development. They give learning teams more flexibility than a standard template, without always needing a large development project.
Where it becomes harder
The challenge comes when the learning asset needs to live for a long time.
A vibe coded module might work beautifully on day one. But what happens six months later when someone needs to update the content, change the logic, add a new accessibility feature, update the branding, fix an LMS tracking issue, or hand it over to another team?
This is where developer experience matters.
AI can generate code, but someone still needs to understand what the code is doing. Someone needs to know whether it is clean, accessible, secure, maintainable and compatible with the target platform.
Without that expertise, organisations can end up with learning assets that are fast to create but hard to support.
That is the real risk. Not that vibe coding is bad. It is that it can create a false sense of simplicity.
The skills question
The learning profession has always relied on a mix of skills.
There are consultants and learning partners who can manage projects end to end. They understand stakeholders, learning needs, content, delivery, review cycles and implementation.
There are specialist instructional designers who focus deeply on learning structure, behaviour change, assessment and learner experience.
There are graphic designers and multimedia specialists who bring visual polish, brand consistency and creative direction.
There are developers and programmers who understand how digital products actually work behind the scenes.
And there are QA, accessibility and testing specialists who make sure the final product is fit for delivery.
Vibe coding does not remove the need for those roles. In many ways, it makes the differences between them more important.
A generalist may be able to prompt an AI tool and create a working prototype. That is valuable. But when the work moves from prototype to production, the need for specialist review increases.
The best results usually come when vibe coding is used as part of a broader digital learning design and development process, not as a shortcut around it.
How vibe coding can work with common elearning tools
Most organisations are not starting from scratch. They already use tools such as Articulate Storyline, Rise, Adobe Captivate, iSpring, Lectora, Moodle, H5P or other LMS and authoring platforms.
Vibe coding can fit into these environments in different ways.
In Storyline, AI generated JavaScript can be used to extend interactions beyond standard triggers and variables. This can support more customised learner experiences, dynamic feedback, custom scoring, or more advanced interface behaviour. Articulate also provides guidance on using JavaScript in Storyline 360, which is an important reference point for teams experimenting in this space.
In Rise, custom content can sometimes be embedded through blocks, Storyline embeds or iframe based content. This means a vibe coded interaction can sit inside a more standard Rise course structure.
In Captivate or Lectora, JavaScript can be used to extend what the tool does natively. This gives more flexibility, but also requires more technical confidence.
In Moodle or other LMS environments, custom HTML or H5P activities can be embedded or linked as part of a broader course. H5P is designed to support interactive content such as videos, quizzes and presentations within platforms such as Moodle.
In some cases, a standalone module can be built outside the authoring tool and then packaged, embedded or linked from the LMS.
The key question is not simply “Can we build it?” It is “Can we support it after it is built?”
For more on matching the right tool to the learning need, see Lucid’s guide to selecting the right elearning authoring tool
Accessibility cannot be an afterthought
This is THE biggest consideration!
A vibe coded interaction might look great on screen but still fail accessibility requirements. It might not work properly with keyboard navigation. It might not be readable by a screen reader. It might have poor focus order, missing labels, low colour contrast, inaccessible drag and drop behaviour, or feedback that is only shown visually.
These issues are not always obvious in a quick preview.
For organisations that need accessible elearning, especially those working to WCAG 2.2, vibe coded content needs proper accessibility testing. WCAG 2.2 covers recommendations for making web content more accessible and is structured around testable success criteria. The W3C also notes that WCAG 2.2 builds on earlier versions and encourages use of the most current version when developing or updating accessibility policies.
Good QA should include:
- Keyboard only testing
- Screen reader testing
- Colour contrast checks
- Focus order review
- Alt text and labelling checks
- Responsive testing across devices
- Testing inside the LMS or delivery platform
- Review of completion, scoring and reporting behaviour
This is where QA becomes more than a final check. It needs to be part of the development process.
For more on this topic, see Lucid’s article on accessibility considerations in elearning design.
AI governance also matters
Vibe coding is part of a broader conversation about how organisations use AI safely and responsibly.
That does not mean every small prototype needs a heavy governance process. But it does mean organisations should think about data, privacy, security, copyright, human review and accountability.
The Australian Government’s AI Ethics Principles include principles such as fairness, privacy protection, security, reliability, transparency and accountability. The Australian Government’s Voluntary AI Safety Standard also sets out guardrails to help organisations benefit from AI while managing risks.
For learning teams, this means being clear about:
- What tools are approved for use
- What content can and cannot be entered into AI tools
- Whether client, learner or organisational data is being used
- Who reviews AI generated code before it is published
- How testing and version control are managed
- How the final asset will be maintained
For organisations building broader AI capability, Lucid’s AI Risk Management and Ethics elearning is designed to help teams understand responsible AI use in a practical workplace context.
When vibe coding is a good fit
Vibe coding is a good fit when the learning experience is small, focused and low risk.
It can be a strong option for:
- Rapid prototypes
- Concept testing
- Micro modules
- Interactive scenarios
- Simple decision trees
- Knowledge checks
- Calculators and job aids
- Custom widgets
- Internal pilots
- Low risk learning activities
It is also useful when a developer or technically skilled elearning specialist is involved and can review, refine and document the output.
Used well, vibe coding can help L&D teams move faster and be more creative.
When to be cautious
Organisations should be more cautious when the module is high stakes, complex or likely to need long term maintenance.
This includes:
- Compliance training
- Assessment heavy modules
- Modules that handle learner data
- Modules that need detailed LMS reporting
- Highly accessible learning experiences
- Large scale enterprise rollout
- Content that will be updated frequently
- Modules that need to be maintained by non technical teams
In these cases, vibe coding may still have a role, but it should sit inside a proper design, development, QA and governance process.
The maintenance issue
One of the biggest hidden costs of vibe coding is maintenance.
A module can be quick to create but slow to fix if no one understands how it was built.
This is why source files, documentation and handover notes matter. Prompts should not disappear into a chat window. Code should not live only in an exported package. Decisions should be documented.
A maintainable vibe coded asset should include:
- Source files
- Clear file structure
- Comments in the code
- A short technical handover note
- Known limitations
- Testing notes
- Accessibility notes
- LMS publishing settings
- Version history
Without those basics, the organisation may be buying speed upfront and complexity later.
What this means for learning teams
The most practical way to think about vibe coding is not as a replacement for elearning development. It is an accelerator.
It can help teams move faster from idea to prototype. It can help create richer interactions. It can make custom development more accessible. It can support experimentation.
But it still needs human judgement.
Learning designers still need to define the learning outcome.
Developers still need to understand the code.
Designers still need to shape the experience.
QA specialists still need to test the output.
Accessibility still needs to be validated.
The LMS still needs to work.
The best use of vibe coding is not “let the AI build the course”. It is “use AI to help us build better ideas faster, then apply the right expertise to make sure the final product is fit for purpose”.
A sensible way to start
For organisations interested in vibe coding, the best place to start is with a small, low risk use case.
Choose one interaction or micro module. Keep the learning objective narrow. Build a prototype. Test it. Review the accessibility. Check how it works in your authoring tool or LMS. Then decide whether it is worth taking further.
A good first project might be:
- A short scenario based activity
- A custom knowledge check
- A simple process decision tool
- A product selection guide
- A compliance refresher interaction
- A small web based job aid
From there, you can build a clearer view of where vibe coding fits your learning ecosystem.
Lucid’s elearning project start up checklist is a useful starting point for defining learning outcomes, audience needs, source materials, technical constraints and success measures before development begins.
Vibe coding is not a silver bullet, and it is not something organisations need to fear.
Vibe coding is not a silver bullet, and it is not something organisations need to fear.
For elearning, it creates a useful new layer between standard authoring and full custom development. It gives learning teams more room to experiment, prototype and create engaging digital experiences.
The opportunity is real. So are the considerations.
The organisations that get the most value from vibe coding will be the ones that use it thoughtfully. They will combine the speed of AI with the discipline of good learning design, accessibility, QA, technical review and long term maintainability.
That is where vibe coding becomes more than a trend. It becomes another useful tool in the digital learning toolkit.
If you are interested in exploring how vibe coding could be used in your existing or new elearning, contact the team at Lucid. We can help you identify practical use cases, test what is possible, and make sure the final learning experience is engaging, accessible and built to last.
