Founder Lessons

Building AI Products While Running an MSP

What building AI products alongside a managed IT and cybersecurity business has taught me about focus, customer problems, integrations and production reality.

By Damir Grubisa, CEO of Group 4 Networks · Executive perspective

Operating experience changes what you build

Running an MSP exposes you to real workflow friction every day. That makes it easier to see where automation can remove repetitive work and where a new product would only create another dashboard.

A product needs a narrow job

The strongest AI ideas are usually specific. Define the user, the workflow and the outcome before adding features. Focus creates a system that can be tested and explained.

Infrastructure and security are part of AI product design

Identity, data access, logging, integrations, reliability and support are not secondary concerns. They determine whether a promising AI application can be trusted in a business environment.

Building changes how I advise

Hands-on product work makes me more skeptical of AI strategies that stop at presentations. I want to know how an idea will connect to systems, who will operate it, what it will cost and how the organization will know whether it worked.

About the author

CEO of Group 4 Networks. I write about what I am learning while building and operating technology businesses across managed IT, cybersecurity, automation and practical AI.