Agile method: AI and cognitive sciences at the service of your training?

The agile method has established itself as an essential approach in software development. By focusing on collaboration, flexibility, and the continued delivery of value, it promises to improve product quality and customer satisfaction. However, many organizations are still struggling to take full advantage of this method. Often, the adoption of agility remains superficial: we set up a few rituals, we use new tools, but mentalities and real practices change little.

Training teams to the true essence of agility is therefore a key challenge, but it is a complex challenge. Indeed, it is not only a question of transmitting theoretical knowledge on a framework like Scrum or Kanban. Above all, it is necessary to develop new reflexes, new ways of thinking and working on a daily basis. How to design training courses that allow this in-depth appropriation? Recent advances in cognitive science and artificial intelligence provide powerful new answers to this question.

Deconstructing preconceived ideas about agility is not easy.

Many agility courses focus on the most visible and formal aspects of the method: the ceremonies to set up, the artifacts to be produced, the roles to be assigned... But in reality, becoming agile often involves challenging deep-rooted habits and assumptions about how to develop software:

• We are moving from a project mode with a fixed scope and schedule to a continuous flow driven by business value.
• We are moving from operating in specialized silos to integrated multidisciplinary teams.
• We are moving from top-down control and a culture of blame to accountability and the right to make mistakes.

To support such a transformation of mentalities, cognitive sciences show that top-down approaches where an expert delivers his knowledge have very limited effectiveness. Present slides explaining what a Burndown chart or the definition of”Done“will not be enough to change learners' representations. Worse, it could elicit rejection reactions if these new notions clash too head-on with their current beliefs.

It is therefore essential to get teams to experience the benefits of agility for themselves, by putting them in a position to solve concrete problems. For example, software development simulations with different constraints allow you to experience the limits of cascade operation and the benefits of iterative and incremental operation. Experienced situations thus bring out the key messages.

Rather than prescriptively formulating best practices, it is also important to let learners express their doubts and objections to agility. The trainer or the coaching system can then provide targeted feedback to gradually remove these obstacles. The process is gradual, by continuously readjusting the representations.
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Facilitate the appropriation of tools and methods: retain and apply

The adoption of the agile method in software development also requires the mastery of new tools and specific techniques:

• Project management frameworks like Scrum or Kanban, with their ceremonies, roles, and artifacts.
• Engineering practices such as test-driven development, continuous integration, pair programming.
• Tools for managing backlogs, CI/CD, velocity monitoring...

Again, a simple theoretical presentation will not be enough to make teams autonomous. To enable the real acquisition of these skills, it is essential to rely on the principles of educational design from cognitive sciences:

• Present the concepts in a gradual manner, always starting with the most essential information, and using meaningful examples from the learners' context.
• Exploiting multimodality, using a variety of media: texts, diagrams, screenshots, video demos, etc. This makes it possible to multiply memory hooks.
• Frequently alternate synthetic inputs and targeted practices, to avoid cognitive overload and the passivity of the learners.
• Suggest active memory activities like flashcards, to facilitate the storage of essential concepts in long-term memory.
• Challenging learners with application exercises of progressive difficulty. For example, have them set up Kanban boards adapted to different use cases.
• Allow the confrontation with unforeseen situations, to develop the ability to react to hazards. Simulate last-minute changes in the backlog for example.

A key point is to provide detailed and personalized feedback on learners' productions. Faced with an exercise, it is tempting to simply give the “official” correction. But to really make progress, nothing beats a specific feedback to each individual, pointing out their successes, areas for improvement, and giving targeted advice. It is this reflective practice that makes it possible to move from theoretical knowledge to grounded know-how.

Anchoring agility into daily practices

Too often, training is seen as a break from daily work. You train intensively over a short period of time, then you go back to your job hoping to apply what you've learned. But without long-term support, the achievements remain fragile and old habits quickly return.

This is particularly true for agility, which is not just a sum of techniques but a daily state of mind. Its real appropriation is therefore played out over the long term, over the course of sprints and projects. It is by living concrete situations that we develop agile interpersonal skills: focus on value, adaptation to change, transparency, etc.

To support this journey, it is essential that training does not end at the classroom doors but extends into the daily workflow. Several complementary levers exist:

• Provide task support resources, directly into the tools used by the teams: synthetic method sheets, checklists, pre-filled templates...
• Propose a proactive coaching system, who asks thoughtful questions at the right moments. For example: “Your backlog contains a lot of technical items. What user stories could you write to make business benefits more visible?”
• Organize regular fun challenges to anchor best practices. During a sprint, reward each good user story with points, for example.
• Encourage the sharing of experiences and mutual support between peers, by bringing out good ideas from the teams themselves. Management must create the spaces for this.

The objective is to bring agility to life on a daily basis, so that gestures become reflexes, and philosophy an evidence shared by all.

The lever of artificial intelligence

Deploying all these good training practices based on cognitive science may seem to require considerable resources. Produce content specific to the context, develop numerous exercises and personalized feedback, provide daily support... This seems to be reserved for large organizations with large training budgets.

But the recent development of teaching assistants based on artificial intelligence is radically changing the situation. Take the example of Didask: its educational AI makes it possible to industrialize the best training techniques, to make them accessible to all structures that want to adopt agility:

• The company's agile experts can focus on transmitting their “raw” knowledge: by writing notes on the specifics of their context, by commenting on photos of the team's Kanban boards, by recording a video on a key point...
• Didask's educational AI automatically transforms this content into interactive and graduated training courses. It generates multimedia animations, flashcards, and quizzes. It offers original simulation activities.
• During the exercises, she analyzes the responses of each learner and provides highly personalized feedback. It highlights specific areas of progress and proposes concrete ways of improvement.
• Finally, it offers a coaching system integrated into daily tools (Slack, Teams, Jira...). Teams receive targeted advice and exercise suggestions at the right time.

So, educational AI allows you to reconcile the best of both worlds. On the one hand, training content is rooted in reality and the field expertise specific to each organization. But on the other hand, these contents are highlighted and made really actionable thanks to the best teaching techniques from cognitive sciences. All without mobilizing excessive resources!

Training teams in the agile method on their software development projects is a strategic challenge for many organizations, but it is an arduous challenge. To truly transform mentalities and entrench new practices, it is not enough to conduct a traditional training program. It is necessary to design learning experiences that are based on the latest advances in cognitive sciences: deconstruction of presuppositions, frequent simulations, personalized feedback, long-term support...

Artificial intelligence, in particular educational assistants like the one offered by Didask, provides a pragmatic and powerful response to this challenge. It makes it possible to industrialize the creation of tailor-made and immersive training courses, without requiring considerable resources. With these new tools, the promise of a true agile transformation of development teams is more within reach than ever.
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