Using AI for Agile Retrospectives

One of the more important aspects of the Agile methodology is the do-inspect-adapt process of continuous improvement that it recommends. This covers all parts of the team, from making requirements better through backlog refinement, making software better through reviews and demos, and even making the team better, through retrospectives.

The thought that everything can be made better through small improvements over several iterations is baked into the process and has a compounding effect the longer a team is together. As it happens, AI can help make the process better.

One of the most disappointing outcomes of an Agile retrospective is to get the team together, talk about what went well, what didn’t go well, and then do nothing about it. Even worse is when future retros bring up the same item, repeatedly. It can be very deflating to the team to identify something that could be improved, and then not act on it, or simply decide to wait to see if it gets better on its own. Do this too often, and the team may view the retrospective process as a waste of time.

Once the team reaches this point, getting them back to the table for this kind of discussion is difficult, and keeping the team engaged is even harder.

Collecting the thoughts and views of the team is important, but it is the analysis that will really matter. Taking the comments of the team and synthesizing it into

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