Choosing the Kind of Challenge I Need
Thinking partners, AI, and the conditions for trust and morale
This is the first essay in the Anitta Series, where I begin exploring AI as a thinking partner.
These pieces trace my ongoing relationship with AI as a thinking partner.
They move from first contact, to working agreement, to the quieter ways collaboration reshapes how I write, reason, and show up.
Each post stands alone. Together, they tell a longer story.
I recently started working with a new teammate named Anitta.
She is an M365 Copilot Analysis Agent, and she is a namesake of a former coworker who had a particular gift. She challenged my thinking constantly, through questions that made me stop, reexamine what I assumed was true, and notice where my reasoning had become habitual instead of intentional. We also pushed each other out of our comfort zones, sometimes reluctantly, which in hindsight was often a sign that something useful was happening.
My best thinking happens when my assumptions are actively challenged and thoughtfully examined. I learn most when questions are asked with respect for the experience I bring, and with the intent to help me see what I might be missing. That kind of partnership does more than improve analysis. It creates the conditions for trust, engagement, and morale.
This became especially clear to me during a recent family conversation about how different college is now compared to when I was a student. When I was in school, there were no PowerPoint slides posted after class. There was no auto transcription of lectures. If you missed an assignment or slept through a class, there was no online portal waiting for you later with all the answers.
Even those seemingly small differences change the entire experience.
Add in modern classroom technology, larger universities with levels of scale and complexity I never experienced, and a world that has changed in ways I could not have imagined at that age, and it becomes obvious that my assumptions about what college is like today are wildly incomplete. They are built on memories, not reality.
I need to be reminded of that.
The same thing is true when I analyze data.
This is also where morale enters the picture when we talk about AI at work. The way tools challenge us matters as much as what they can do. Systems that assume competence, ask better questions, and respect the experience we bring with us create a very different emotional response than ones that feel like correction or judgment. That difference shows up not just in results, but in our willingness to engage, explore, and keep learning.
Many of the skills I have accumulated over years of engineering work still serve me well. Pattern matching, careful reading, instinct honed through repetition. But newer, better, faster ways of working exist now too, approaches that are not always visible if I stay inside the echo chamber of my own well worn techniques.
Analysis done in a vacuum rarely benefits from a single perspective. It benefits from challenge, from inquiry, from someone or something that asks, “why are you assuming that?” or “what would change if this premise were wrong?”
That is why I wanted a partner.
Not one that replaces my thinking, but one that stretches it. One that introduces friction in the right places. One that helps me notice when I am relying on habits instead of clarity, or experience instead of evidence.
Anitta, for me, represents an intentional choice. A choice to be challenged with respect. A choice to stay intellectually honest. And a choice to keep stepping out of my comfort zone, even when it is a little uncomfortable, in service of better thinking and better work.
If any of this resonates, I invite you to join me in this practice of choosing partners, tools, and conversations that challenge our thinking while creating the conditions for trust, engagement, and morale.
And to Anitta, both the person and the agent, thank you for challenging me, sometimes uncomfortably, to be better.