September 19, 2023

From Retro to Learning

Transform your Agile retrospectives into actionable learning modules with our AI Trainer. From extracting data in CSV format to crafting engaging messages, this guide walks you through the entire process of converting retros into personalized team training courses. Elevate your retros and empower your team today!

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Agile retrospectives are a cornerstone for team improvement but often fail to deliver actionable learning. While teams discuss what went right or wrong, the insights may not translate to effective training. Enter a game-changing solution: using AI to turn your retrospectives into targeted learning experiences. This guide shows you how to revamp your retros so they're not just a forum for venting, but a goldmine for AI-generated, team-specific training.

Imagine your retrospective insights serving as the foundation for customized training modules. With today's AI technology, it's entirely feasible. However, the challenge lies in formatting and running your retros in a way that the AI can comprehend and convert into useful training. This guide will walk you through the steps to make your retros more AI-friendly, without sacrificing the essence of what makes retrospectives a vital part of agile methodologies.

The problem with retros

In traditional settings, retrospectives often end up as a collection of random thoughts, disjointed insights, and a 'things to do' list that nobody looks at after the meeting. While this might offer some short-term relief, it doesn't contribute to long-term learning or improvement. In contrast, structuring your retrospectives with an eye toward learning can transform them into a goldmine of data that can be translated into specific, actionable training modules.

The secret is to turn those retrospective insights into learning objectives. Instead of just identifying what went wrong or what could be improved, dig deeper. Ask 'why' and 'how' questions until you arrive at the root cause. This information is invaluable; it's the raw material that can be fed into our AI trainer, which will then generate targeted training content tailored to your team's unique needs

Imagine your team has identified 'poor communication' as a recurring issue during your retrospectives. Instead of stopping there, delve into the 'why's. Is it because of unclear roles, inadequate tools, or perhaps a lack of trust? By asking these questions, you not only identify the root problem but also create specific learning objectives like 'Improve Trust Among Team Members' or 'Clarify Roles and Responsibilities'


To maximize the effectiveness of your AI Trainer in generating a tailored learning course, you'll want to consider how you format the retrospective output. The key here is specificity and structure.

  1. Clearly Define Problems and Issues: Instead of vague descriptions like 'Communication could be better,' aim for more precise definitions such as 'Lack of clarity in project requirements from stakeholders.'
  2. Use Bulleted Lists for Observations: This makes it easier for the AI to parse through the data. For example:
  3. Observation 1: Team often misses deadlines.
  4. Observation 2: Overlapping responsibilities cause confusion.
  5. Highlight Action Items and Learning Objectives: Clearly outline what needs to be done and what the team should learn. Use actionable language.
  6. Wrong Way: 'We should communicate better.'
  7. Right Way: 'Implement a daily stand-up meeting to improve team communication.'
  8. Categorize and Label: If possible, tag or label the issues, action items, or learning objectives. Categories like 'Communication,' 'Teamwork,' and 'Project Management' can guide the AI Trainer to create more targeted learning modules.

By following these formatting guidelines, you're making it much easier for the AI to analyze the retrospective output and generate a learning course that’s both relevant and impactful for your team.

Extracting retros from Miro or Mural

When you're using platforms like Miro or Mural for your retrospectives, the extraction process becomes crucial for ensuring the AI Trainer can efficiently turn your retros into actionable learning courses. Here’s how you can do it:

  1. Export to CSV: Both Miro and Mural offer options to export your board content to a CSV file. Look for 'Export' in the menu and choose the CSV format.
  2. Check for Format Consistency: Once exported, open the CSV file and ensure that the columns are well-structured. You should ideally have columns for 'Issues,' 'Observations,' 'Action Items,' and 'Categories.'
  3. Conduct a Quick Audit: Run through the exported data to see if it aligns with the formatting guidelines mentioned in the previous section. Ensure each item is specific, structured, and actionable.
  4. Label and Categorize: If you didn't do this while conducting the retrospective, now's the time. Add tags or labels in a separate column in the CSV to guide the AI Trainer for topic targeting.
  5. Save and Upload: Once you’ve made the necessary adjustments, save your CSV file. You're now ready to upload it to your AI Trainer for generating a targeted learning course.

And just like that, you’ve transformed your Miro or Mural-based retrospective into a resource that can be leveraged for AI-generated learning. This ensures you’re not just identifying problems but actively taking steps to solve them through tailored training.

Working with the Ai trainer

The next stage involves the real magic: transforming your retrospective insights into a targeted team training module. Here's how to make it happen:

  1. Upload the CSV: Navigate to the 'Ai creator' in your dashboard and click 'Upload CSV.' Choose the CSV file you prepared.
  2. AI Clarifications: Once uploaded, our AI Trainer will review the data and may ask you some clarifying questions to fine-tune the training topics. This ensures that your learning modules are as relevant as possible.
  3. Review Proposed Modules: After the clarifications, the AI will propose 1-3 learning modules tailored to your team’s needs. You can review these proposals to see which one(s) align most closely with your goals.
  4. Click 'Build': Happy with the proposed learning module? Simply click the 'Build' button. The AI Trainer will then create a custom team training module derived from your retrospective data.
  5. Quality Check: Before launching the training, you'll have a chance to preview the content. If everything looks good, you’re ready to roll it out to your team.

This way, your retrospectives don’t just end at identifying issues; they convert into a structured learning experience designed to elevate team performance.

Deploying the team training with the Course Scheduler

Once your custom module is ready, it's time to get it in front of your team. The Course Scheduler makes deployment easy and efficient. Here's how to proceed:

  1. Schedule the Course: Navigate to the 'Learning Path' section and set the date and time that works best for your team. You can schedule multiple sessions if needed.
  2. Announce the Team: Communication is key. Let your team know about the upcoming training. Not sure how to frame it? Our AI Trainer can help craft an engaging announcement message to get your team excited.
  3. Use the AI Trainer for Messaging: Simply input your course details into the AI Trainer, and it will generate a compelling message that you can send directly to your team. This ensures that your team is well-informed and motivated to participate.

Post-Course Analytics

After the training session, it's crucial to evaluate its impact. Navigate to our 'Analytics' section to see how your team is doing:

  • Engagement: Check how many team members actively participated and completed the course.
  • Confidence Levels: Our analytics can show you how confident your team members are in applying what they've learned.
  • Skill Gap: Identify areas where your team still has room for improvement. This can guide your future retrospectives and training modules.
The data you gather here not only validates the training's effectiveness but also feeds into future retrospectives, making each loop more focused and productive.

This wraps up our guide on turning retrospectives into actionable, AI-generated learning modules. What you've essentially done is convert a post-game analysis into a training playbook. That's something to be proud of!

Closing Thoughts

You've just journeyed through a transformative process that elevates retrospectives from mere reflections to actionable learning adventures. Leveraging AI-driven tools like our Course Scheduler and Analytics suite, you're not just solving problems; you're empowering your team to evolve. Turn your retros into roadmaps and continue to navigate the ever-changing landscape of team dynamics and skills.

Happy Learning!

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