From radar DSP to AI agents
I'm an electrical and communications engineer from the Institute of Space Technology, Islamabad. Before AI automation became my work, I spent years on radar signal processing and metamaterials research. That work punishes wrong assumptions: one bad guess breaks the entire signal chain, and there's no LLM to paper over the failure.
Most automation builders learn the tool first and the engineering later. I came in the opposite direction. When a client brings me a workflow problem, the first question I ask is whether the workflow should exist at all, not how to drag-and-drop it together.
When I review an automation system, I look for where it will fail first: tight coupling between orchestration and compute, webhooks with no idempotency, retry storms, embedding drift with no observability. That critical eye is the thing my clients actually pay for, even when they think they're paying for an n8n workflow.
"I'm a problem solver by mindset. If I don't know something, I learn it fast, and I stay relentlessly practical about it."
