Due to COVID-19, organizations of all types have had to implement continuity plans within an unreasonably short amount of time. These live experiments in agility have shaken up our industry, but it's also taught us a lot of invaluable lessons about digital transformation, cybersecurity, performance engineering, and more.

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.