Agile projects focus on very lightweight, simple requirements embodied in user stories. However, there are some problems with relying solely on user stories. They often don't contain enough accuracy for development, testing, or industry regulations. There's a better way to write detailed requirements that are still agile.

Developing a tool that runs on artificial intelligence is mostly about training a machine with data. But you can’t just feed it information and expect AI to wave a magic wand and produce results. The type of data sets you use and how you use them to train the tool are important. Here are five pitfalls to be wary of.

Threat modeling‍ has transitioned from a theoretical concept into an IT security best practice. Choosing the right methodology is a combination of finding what works for your SDLC maturity and ensuring it results in the desired outputs. Let’s look at four different methodologies and assess their strengths and weaknesses.