Use AI to facilitate an efficient DevOps cycle

Software engineers spend less than 30% of their time writing code at corporate jobs. I don't think it's the corporates fault nor the engineers fault. Especially senior+ engineers don't get much coding done. They work with a lot of people and have to make sure everyone is on the same page. They are responsible for the effects of other peoples code. And there are just so many systems and tools to manage. To get software into production, an engineer might touch 20+ tools. From Notion to Jira, then to AWS, onto Gitlab, over to Snowflake and Datadog... you name it. It can be tedious.

Continuous AI has the mission to fill these cracks and let engineers focus more on what they love: Coding.
All the non-coding aspects of the DevOps process are super important (reference). LLMs are often used to help with coding. Continuous AI helps with everything except coding.
Concretely, our AI reviews project stories, does code reviews, tracks deployments and metrics and creates project status updates. And thats just the start.

We're really excited about this project. It can be a huge needle mover for developer productivity and helps tear down silos. Let us know what you think! Does this story transpire clearly out of the landing page? Do you feel engaged to drive an action?