Topical Index of the Gitential Blog

You can find the full Agile Manifesto and other Agile essentials over at the Agile Alliance. 

AI serves to make it easier and faster for real people to carry out their work more accurately. This is especially true when it comes to working with large amounts of complex data, as is definitely the case when managing software development teams. Software development is expensive. The larger the company and/or project, the more complex it is and the more inclined it is to be challenged or fail outright. 

AI heavily reinforces Agile’s first value, that, people come first. Everything about software development boils down to individual developers and team dynamics. Using AI for Agile project management involves a focus on continuously improving each developer’s skill and aptitude for teamwork. Everything else is a natural and logical extension of helping all software development stakeholders achieve their full potential and work better as a team.

Remember – successful software, at a minimum, is delivered on time, on budget, and according to specifications – all of which depend on team skill and teamwork. AI helps managers, and actually all stakeholders, better channel the resources, training, and mentoring, as well as improve work processes and team interaction to help everyone do their best.

This format depends upon self-reporting where answers may reflect more on the individual than the task. It’s also likely that team members are thinking more about what they should say than listening to what others are sharing. Not everyone is brave enough to volunteer that they need assistance with a task. This standup routine can be painfully monotonous. If you’re using this format, and you can see engagement could be better, you might just need to mix up the format.