How to choose the AI coding assistant that works best for your engineering team
You have either already chosen an AI coding assistant for your team or are in the process of evaluating one. If you don't belong to either of the above two groups, you will soon find yourself in the minority. Irrespective of which camp you are in, the rapid advancements in this space mean that you need to carefully evaluate how you choose an AI coding assistant - one that is not just right for your needs today but also sets you up for the future. Here, we list the key questions you should ask while evaluating an AI coding assistant.
When you introduce a new developer tool in your organization, you want it to work alongside all your other tools. You want to ensure that any learning curve or changes associated with adopting a new tool are amply made up for by the benefits you will receive. Your AI coding assistant should integrate with your favorite editors - VSCode, JetBrains, etc. The relevant functionality should also be available in a simple web-based interface where applicable. Additionally, it should work with your code regardless of where it lives—GitHub, GitLab, Bitbucket, etc.
Each organization is different in terms of its choice of programming language(s) or frameworks, and its reasons for choosing also vary—history, skill, performance, preference, etc. You need a coding AI assistant that helps with your specific environment and produces the most relevant results for your language and framework choices.
