Join me to develop innovative software that uses NLP and ML to analyze user stories in agile development and suggest how to break them down into smaller, more manageable chunks. With your help, we can improve the effectiveness of agile teams by automating the process of reviewing and refining user stories.

1. Collect and preprocess a large dataset of user stories that have been labeled as "well-written" or "poorly-written".
2. Extract relevant features from the preprocessed data and train NLP and ML models to classify user stories.
3. Evaluate the performance of the models using a validation dataset and refine the feature extraction and model training processes as necessary.
4. Implement a feature that suggests how to break down larger user stories into smaller, more manageable chunks based on the content of the story.
5. Test the software extensively to ensure its accuracy and usability.
6. Collaborate with the project team to continuously improve the software and add new features based on user feedback.

Students will have the opportunity to gain hands-on experience with NLP and ML techniques, learn about agile development practices, and contribute to the development of a cutting-edge software tool that has the potential to improve software development teams.

My software developer and I have been working on this tool for five years. We will be available as needed by phone or email, but we also hold a weekly meeting to discuss progress, demo updates, and make decisions. Students would be invited to these meetings as well. I would also expect to spend a couple hours acquainting the students with the tool, what we are trying to achieve, and more specific on the background of this project. We have a development environment available on the web for the students and will also provide access to our Github repository as needed.