[3Qs with AI CoE]: Guest Zubair Farooq
The “Cyborg” Approach to Customer Support. When the manual doesn’t exist, the support agent becomes the engineer.
Most podcasts are 45 minutes of fluff wrapping 5 minutes of insight. We skip the weather, the “how are yous,” and the generic bios.
Welcome to 3 Questions with Trilogy AI Center of Excellence.
The rules are simple: I ask the guest three rigorous, tailored questions based on their actual work. They ask me zero to three questions back. We are done in 15 minutes.
For this episode, I sat down with Zubair Farooq. Zubair is an L2 Customer Support Engineer who works under the internal designation of “Cyborg.” He represents a new class of employee: the early adopter who was thrown into the deep end of AI and learned to swim by building his own life raft.
Here is what we uncovered.
1. Thrown into the Deep End (Capability > Speed)
I asked Zubair about the early days of the “AI First” transition. This wasn’t a carefully managed rollout with training modules; it was a mandate to figure it out.
Zubair explained that they didn’t use AI simply to work faster. Instead, they used it to widen the scope of their technical abilities. They adopted complex frameworks (like Co-STAR) and mastered prompt engineering immediately.
Spiky Point of View:
Most people use AI to do the same job in less time. Zubair used AI to do a different job entirely. By mastering the inputs, he transformed from a support agent who escalates problems into a technical operator who solves them. It wasn’t about speed; it was about becoming a superior engineer through better tooling.
2. The Technical Person (Who Isn’t an Engineer)
Zubair lists “optimization” as a core skill, so I pressed him for a concrete example. He described a scenario involving a legacy platform where customers frequently needed a specific installer file. It was a repetitive, four-click manual process.
Zubair is not a backend developer by trade. However, he realized that “optimization” meant removing the human element entirely. He used AI to write an AWS Lambda function that detects the ticket intent, fetches the file from the S3 bucket, and posts it automatically.
Spiky Point of View:
There is a distinction between being a “Software Engineer” and being a “Technical Person.” Zubair proves you don’t need a CS degree to build production-grade automation. If you understand the logic and the friction, AI allows you to write the syntax. The modern “techie” is defined by their ability to solve the problem, not their ability to pass a coding interview.
3. The Hunger for Context (Curiosity)
I asked Zubair what drives him to join new initiatives and participate in these discussions. His answer was simple: Continuous Curiosity.
He actively follows technical “Office Hours” chats even when he can’t attend the meetings. He reads about RAG (Retrieval-Augmented Generation) architectures not because it’s in his job description, but because he sees how it applies to his problems.
Spiky Point of View:
In an AI world, skills depreciate fast, but curiosity compounds. The most valuable employees aren’t the ones who know everything today; they are the ones obsessed with what they can build tomorrow. You can train for skills, but you cannot train for the “hunger” to learn.
The Reverse Card: The Metric of Success
Zubair turned the tables and asked me a fundamental question: “In this new world, what is the actual success metric for a Cyborg? Is it volume? Is it complexity?”
My Answer:
It is Documentation Structure.
The goal of a “Cyborg” is not just to solve the ticket. The goal is to solve the ticket and simultaneously create the data structure that ensures an AI can solve it next time without human intervention.
We are moving toward a model where humans handle Novelty - the edge cases the system hasn’t seen before. Once you solve a novel problem, your duty is to encode that solution into the knowledge base.
The Takeaway:
If you are solving the same problem twice, you have failed. Success is defined by how well you document your solution so that it becomes part of the automated system.
You are not just a support agent; you are a Knowledge Creator. As soon as your job consists only of solving new problems, you have won.
Watch the 8-minute edited video here: