What happens when you not only add AI to your software but also use it to develop that software? And what does that ultimately mean for the people who work with the learning platform?
In Episode 5 of the “ Procademy ” podcast, Bas Mourits from Studio voor Betekenis sits down with Wouter van Emmerik on the beach. They discuss the changes taking place at Procademy, the possibilities of AI, and how a small team can develop software faster and more efficiently.
They also call Peter Esser, who is attending the AFAS Partner Festival, and Herman Versteegt, who explains from his car how AI helps support and onboard new customers.
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For those who prefer to read the podcast, or for those who have difficulty listening, a written transcript is also available .
The project began during the Christmas season. While the office was largely empty, Wouter and Peter set to work exploring new possibilities for AI-powered software development.
Procademy had already been using AI for some time for day-to-day tasks, such as improving texts or checking code. But the capabilities of new AI models turned out to go much further.
Whereas modifying existing software used to require a great deal of preparation and development time, it became possible to analyze, improve, and test large parts of the platform much more quickly.
That led to a significant change—not only in the speed at which software could be developed, but also in the way the team works together.
Traditionally, software development and customer implementation have often been separate tasks. One colleague discusses the customer's needs, and then a developer translates those needs into technical solutions.
At Procademy , those roles have grown increasingly closer together.
With the help of AI agents, colleagues who work directly with customers can also actively contribute to the platform's development. As a result, insights from customer interactions reach the people and systems responsible for improving the software more quickly.
This reduces the amount of information that needs to be conveyed and makes it easier to make decisions together.
After all, faster development does not automatically mean that everything that is technically possible must be built right away. It is precisely the joint setting of priorities that remains important.
An important question in AI-assisted software development is how to maintain control over the final result.
How do you ensure that new features integrate seamlessly with existing parts of the platform? That the software remains secure? And that accessibility isn't overlooked?
Wouter explains how Procademy operates in this regard, using detailed instructions and guidelines for AI agents. These describe, among other things, how features should be developed, what controls are necessary, and what quality standards the platform must meet.
For example, there are agreements regarding the technical architecture, automated testing, and the design of the user interface.
Accessibility also plays an important role here. For example, by using reusable components and established guidelines, we ensure that contrast, consistency, and the WCAG guidelines are taken into account.
This does not give AI unlimited freedom to modify software. It operates within parameters that are established, monitored, and continuously improved by the team.
Ultimately, the development of the platform isn't about AI itself, but about the people who work with it.
These include participants who take courses, as well as administrators, planners, instructors, and developers of learning materials.
Organizing learning can be quite complex. Consider employees who change roles, mandatory training courses that must be automatically assigned, certificates that expire, or results that need to be fed back into an HR system.
In the past, users sometimes had to have a good understanding of how the software worked in order to set up certain processes.
The goal is to continue shifting this dynamic: it is not the user who should have to adapt to the software, but rather the software that should help the user achieve their goal.
Thanks to AI, Procademy can focus more on such improvements, even down to the smallest details.
A concrete example is the new editor for developing learning materials, which Wouter discusses in the podcast.
This makes it easier to add and edit content in various ways. For example, by writing your own text, importing existing materials, or dragging elements to the right place.
AI also plays a role here. Think of generating voice-overs or editing images with a simple instruction.
The idea behind this is that an author should be able to focus primarily on the content of a training course, rather than on all the technical steps required to create it.
That doesn't mean, however, that good e-learning just happens on its own.
During the episode, Herman also receives a phone call; he is on his way back from a meeting with a new client.
He explains how AI helps speed up the preparation of implementations. This includes gathering technical documentation for integrations with AFAS and Microsoft, preparing for client meetings, and incorporating specific client requests into a quote.
Tasks that previously required a lot of manual work can now be prepared more quickly. This leaves more time for personal interaction and substantive guidance.
But Herman also has an important tip for those just starting out with a learning environment.
A good LMS is no guarantee of a good learning experience.
Developing effective e-learning requires expertise in educational design. How do you ensure that participants understand the material? That a training program is tailored to the target audience? And, most importantly, that people are actually able to do something differently or better afterward?
Organizations that do not have that expertise in-house would be wise to bring in an educational specialist or a specialized development partner.
Technology makes it easier to develop and offer training courses. The quality of the learning content remains just as important.
Speaking at the AFAS Partner Festival, Peter shares his perspective on developments in the field of AI.
Software development isn't just about speed; it's also about reliability, quality, and security.
That is precisely where AI can help. For example, by conducting inspections and tests in a more systematic way and automating repetitive tasks.
This development is part of a broader trend: automating, as much as possible, the tasks that a computer can perform well, so that people can focus their attention on tasks where their knowledge, creativity, and judgment make a difference.
For Procademy , this also means that the collaboration between engineering, implementation, and customer support is changing.
This episode shows how the use of AI goes beyond simply adding smart features to a learning platform.
It also changes the way software is developed, with shorter lines of communication between the customer and the development team, more room to improve existing features, and new opportunities to streamline processes.
At the same time, human expertise, clear agreements, and quality control remain essential.
And perhaps that is the most important conclusion of the discussion: AI can speed up a lot of work, but ultimately, what matters is what it enables for the user.
For Procademy , this is a learning platform that is becoming increasingly intuitive, accessible, and enjoyable to use.
Curious to see what that looks like behind the scenes?
Listen to Episode 5 of the " Procademy " podcast: Vacation Vibes on the Beach.
Spotify:
https://open.spotify.com/show/6Ku9hrwYq6i7PFJbzmujxV
Apple Podcasts:
procademy
Podcast Addict:
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