The last post in my series on software development team standards focuses on meetings. The cause of, and solution to, all life’s problems, its very easy for meetings to get too far one way or the other on the spectrum of managability. On one side, too many meetings are often a waste of resources, while on the other not having key stakeholders present in meetings can leave large gaps in knowledge and functionality that will impact the quality of your software product. Here’s a few things to look out for.

Post #3 on my series on software development team standards focuses on testing and code quality, two hot-button topics for most implementation teams. Although both can cause some disagreements and take a bit of effort to get right, I think they are very critical aspects of high performance teams and should be addressed as early as possible so that developers can focus on what they do best - implementing features.

It’s post two of my series on software development team standards! Today’s post focuses on development practices - the particulars of writing and managing code. Here’s a few best practices I’ve observed, implemented, and/or witnessed over the years from high functioning teams.

Having worked on a number of different teams over the last 20 years, I’ve started to notice a number of trends among the higher functioning software development groups. I think at this point in our industry there’s a number of “best practices” that most software teams have adopted, and those who haven’t are often struggling with common issues that could be addressed by those same practices. Today’s article will focus on task management and sprints, two areas where there can be potentially a lot of divergence from established standards.

It’s no secret - calls to generative AI APIs are expensive and slow. It seemed like a crazy concept when it was first introduced - having to pay per API call? For an API that takes seconds to return? Who does that? Now that it’s established as normal, strategies are being developed to attempt to reduce cost and improve response times when it comes to generative AI APIs, and one of the most promising is Semantic Caching.