AI perspective and SaaS blueprints


Regardless of where AI is sitting in your stack today, when it becomes versatile it can help you with code not with manual clicks in consoles. The longer you wait, the more progress slips your IP. The longer it will take some time to catch up when everyone is there. The longer you would spend on AI. This might disrupt your business.

See also

Zero-time provisioning

 

Removing manual work was never that effective. There is no security person checking configuration, no operations copying secrets from one place to another, no manager coordinating and prioritizing work between teams, no figuring out dependencies over and over, reduces surface of a costly mistake at least in half. In a fact most secrets are provisioned as part of blueprint and there is no soul which sees those credentials.

This leans feature engineering to crafting itself with minimal wrapping. This means feature can go to end customer with 4-5 times less people involved, and hence 8-10 times faster in a responsible manner. Risk management on early stages gives advantage on later stages. Hence compounding cycle continues as you go to larger customers.

This is a good example which shows five nine analysis prism in action: if something goes south, how can team reconfigure this quickly in a new place? Once this question answered - it turns out this is the same question as how to optimally design a feature in a first place, or how to reuse parts of technology would an organization go to a different direction or vertical.

Focusing on blueprinting of dependency provisioning multiplies software teams as they can provision own configuration once and pass it to relevant application at every stage of SDLC.

This is a way to own your SaaS. 

Contact us here for more information.

See also