The Co-Worker Who Always Has Time

If you've read anything I've written before, you know the theme by now: I'm a question asker. It's not something I do to look engaged in meetings. It's how I'm wired. My brain generates questions the way other people's brains generate small talk — constantly, involuntarily, and in the moment as things are happening and especially as I see a "gap" in my understanding.

The Unanswered Questions

Before AI, when a question came up or a curious thought entered my mind, I had a handful of places to take it. I could ask a department head, if they had time. I could ask a co-worker, if they knew and had time. I could ask the developer who built the thing I was curious about, if someone was willing to engage.

The reality is that worked only some of the time. Maybe someone had five minutes, and I got my answer, and my understanding of the software world forward one notch.

But more often — far more often — the questions went unanswered. Not because anyone was unkind. Not because anyone was hoarding knowledge. But because everyone is busy. Genuinely, deeply, legitimately busy. A question from me about how the service layer connects to the UI is, for the person I'm asking, an interruption in the middle of twelve other things that are actually their job. So the question gets a "let me get back to you on that" — and I completely understand why it never comes.

Although to be clear, I get it. As interesting as marketing strategies are, and as fascinating as UI-to-service-layer technology is, everyone at a company has a job to do. Their job is not to answer questions and train curious co-workers just because those co-workers are genuinely curious and want to learn. That was never in anyone's job description. It was never fair of me to expect it, and I never resented anyone for it.

But my desire to know know and understand how things work didn't just go away just because I had no one, or little to no one, to help me.

Principles Vs Real Examples

When the people around me couldn't answer my questions, I did what question askers have always done: I turned to formal learning. Bootdev courses. Online videos and webinars. Research.

And those have their place. But here's the thing about courses and webinars: they teach in general principles. Abstractions. Basically the textbook version of how things work, in a clean room, with no history, no constraints, no legacy code, no business logic that grew tangled over three years of feature requests.

Real examples are much better to learn from. How does this company's bug fix work, in this codebase, with this architecture, between this front end and this back end? That's the knowledge I actually want. That's the knowledge that makes me better at my job, because it's the actual system I work in.

But the people living those examples — the developers at the company, the engineers, the ones who touch that code every day — are, rightly so, busy doing exactly that. Living the examples doesn't leave a lot of room for narrating them.

So there was a gap. A permanent, structural gap. The general principles were available to anyone willing to sit through a course. The real examples were locked inside the heads of people who were too busy being good at their jobs to host tours.

And then, everything changed.

A Question Asker's Best Friend

Thanks to AI, us "question askers" and "knowledge seekers" finally have someone to ask our questions to — and someone who always readily available to answer us.

For those reading this, I need you to understand what a sentence like that means to someone like me. For my entire career, my questions have actually been rationed. Not by anyone's policy — by reality. By the finite patience and finite time of the people around me. I learned to hold questions. To triage them. To ask only the ones that seemed worth the interruption. To let the rest pile up in a notebook somewhere, unanswered, until I half forgot what made me curious about them in the first place.

Now the rationing is over. The pile is being worked through. And the person answering is never annoyed, never interrupted, never too busy, and never makes me feel like I'm imposing just by wondering out loud.

What It Actually Looks Like

This isn't theoretical for me. It's my daily work.

In Monday.com, when I want to better understand the output from another agent — a QA test result, a software "bug" evaluation, a PR (pull request) — I can ask Monday's in-house AI to explain it. To summarize it. To bottom-line it: what does this actually mean, in plain language, and what do I need to know? And when the explanation still isn't landing — when the concept is slippery — I can ask for an analogy. "Explain this like I'm new to it. Give me a comparison that makes it stick." And it does. And it sticks.

That's not a small thing. An analogy that makes a technical concept click is one of the most valuable teaching tools that exists, and it's exactly the kind of thing a busy co-worker almost never has the bandwidth to craft for you on demand.

Then there's my work agent — the one I direct to connect to Monday itself. I can ask it to connect to Monday, analyze all the pulses, and give me a detailed yet straight-to-the-point report on any topic or trend. Not a vague summary. A real analysis of the actual data, focused on whatever I need it focused on, at whatever depth I ask for.

I can ask it how this bug fix or this new feature works behind the scenes — in the codebase, between the UI/front end and the back end — so that I can understand the fix or the feature better. Not the textbook version. The actual version. The one that lives in our real code, in our real system. The exact kind of knowledge that used to be locked away, now unlocked by asking.

And one of my favorite uses: I can ask my agent to compare all the upcoming pulses — everything that's about to be deployed — against all the knowledge base articles I manage, and give me a list of which articles may need updates, along with what those updates might be. Then I review them, decide what's right, and implement the changes. A task that used to depend on me happening to hear about changes soon enough to catch stale documentation is now a systematic, reliable process.

Not Just a Fancy Search Engine

But here's the part that elevates this beyond "AI is a nice search engine."

Not only can I ask all the questions I want — learn as much as I can, follow every thread, finally feed the hunger that's been rationed my whole career — I can also direct my agent to help implement the changes I'm in charge of. The knowledge base updates. The documentation. The customer-facing materials. The work that's actually mine.

That's the distinction that matters. AI isn't just a wealth of information. It's a super smart assistant that can work alongside you. It doesn't just tell me things — it does things. It connects, it analyzes, it drafts, it updates, it builds the artifacts of my actual job while keeping me in the loop to review and decide.

The question asker and the knowledge seeker in me finally have a partner. And the professional in me — the one responsible for deliverables, not just curiosity — has one too.

The Co-Worker Who's Always There

I've written before about how the right environment — the right people around you — makes all the difference in whether a question asker thrives or wilts. That's still true. Nothing replaces brilliant colleagues who have the time and generosity to teach.

But in a world where everyone is even more busy than they've ever been — more meetings, more tools, more platforms, more pressure to use agentic AI and increase their output— asking people questions is making less lense. The spare minutes are rarer. And sadly with that, goes the interconnectedness and relationship at work, but this is the world that we live in...

Which is why I am truly grateful to have a "co-worker" that is always available for me to ask questions and get answers. One who knows the codebase context I need, connects to the platforms I work in, explains at whatever level I ask for, answers the fifth follow-up with the same patience as the first, and then rolls up its sleeves and helps me do the work. Finally with AI not only can I get any questions answered that I want, I can also learn to do things by watching my agent perform the work based on my prompt.

The gap between my questions and the world's answers was, for most of my life, just a fact of nature. But now my questions finally have somewhere to go. Every single one of them, as fast as I can think of them and whenever I think of them.

For someone built like me, that's not a convenience. That's a kind of freedom I've always been waiting for!