If you’ve ever wondered how much documentation is enough in an agile project, or you’ve heard you don’t even need documentation with agile, please check out my article on StickyMinds about how my teams have approached agile documentation.
My AI learning journey has been long, and littered with gaps. I first got really interested in AI and machine learning back in 2018 and
I’ve worked primarily in a tester and quality engineering role for a few decades now. “Metrics” have always been the magic beans of improving quality.
I’m fortunate to talk with lots of quality and testing professionals looking for advice and resources to grow their careers. I’m lucky to have a
Back in 2000, reading Kent Beck’s book Extreme Programming Explained was an epiphany for me. It’s all about the people! When we work together, have
Recently I had the honor to discuss AI, testing, and the DORA AI Capabilities Model with the leading practitioners who host the Beyond Quality podcast.
Continuous quality improvement is an important goal for modern software teams. Metrics to measure quality are a perennial hot topic that people often ask me
3 Responses
That was a really interesting article and on a topic I struggled with a lot when I first switched to Agile. And although my thoughts have evolved a lot since I started ( and wrote this piece on it: http://www.everydayqa.com/2010/agile-development/documentation-on-agile-developement-teams/ – I still feel like it is one of the biggest issues our team faces- the struggle to maintain the right amount of documentation with out getting bogged down by process.
As our automated regression suite has grown, it has been a great reference and in a way, has served that documentation role, as you mention. I am also hoping to get archived pivotal tracker stories to play a similar role in the future.
Great post!
Thanks, Devon! I’m going to read your post too.