What Happens When We Ask Better Questions?

I ask a lot of questions.

And, increasingly, I find myself questioning the questions too.

What are we actually trying to understand?

What do we mean by the words we're using?

Who are we asking?

What assumptions have we already made?

What else might be influencing what we're seeing?

And perhaps most importantly: is the question we're asking giving us the kind of understanding we actually need?

For a long time, I thought asking better questions meant making them more structured and precise.

I still think that matters.

But I'm beginning to think there is another part to it.

Sometimes, we can't know the better question until we have started asking.

We tend to imagine questions as something relatively linear:

But many of the questions I find most interesting don't seem to work that way.

They look more like:

And sometimes that next question changes how I understand the first one.

I've noticed versions of this throughout very different parts of my career.

Years ago, I interviewed for a SOX compliance role at Zurich Insurance — work relating to financial reporting controls.

The work was technical: controls, governance, processes, procedures, documentation, compliance.

During the interview, I was asked what I thought was the most important part of my job.

I answered:

Connecting with people.

I don't remember thinking that this was an unusual answer at the time. It simply seemed obvious to me.

Because if I wanted to understand whether a process worked, I needed the people involved in that process.

They knew how things actually happened.

They knew where something became difficult.

They knew things that weren't necessarily written in the procedure.

But more than that, I couldn't do my job in isolation.

I needed people to talk to me, work with me, challenge me, explain things to me, and sometimes help me.

And I had noticed, time and time again, that when you treat people as human beings — with respect and fairness, regardless of their position, profession, background or culture — you create a very different kind of relationship.

Perhaps one day you need their help.

Perhaps they need yours.

Perhaps neither happens.

But either way, you're much more likely to understand each other and achieve something together.

The controls mattered.

The procedures mattered.

But so did the human beings operating them.

I didn't have the language for it then, but I can see the pattern much more clearly now:

Keep the human being in the picture.

Years later, working in women's health and nutrition, I started noticing something similar.

Women would come to me wanting help with nutrition.

So, naturally, we talked about nutrition.

But we rarely stayed there.

We would start talking about their lives. What they had learned growing up. Their experiences and beliefs. Their relationship with food. What they wanted to change. What they already knew. What made change difficult.

Nutrition was still important.

But sometimes it became almost a second layer rather than the first.

Knowing what someone could eat was one question.

Understanding what might help that particular person make a meaningful, realistic change was another.

And this is where another idea started becoming clearer to me:

The technically correct answer isn't necessarily the practically useful answer.

Again, the information mattered.

But information alone wasn't necessarily enough.

And that kept making me ask:

What else might be influencing what we're seeing?

If I want to know how to use my coffee machine, I can look at the instructions.

Press this button.

Turn this dial.

Put the cup here.

Excellent. Coffee. ☕

There are plenty of problems for which clear instructions are exactly what we need.

But human beings don't work quite like coffee machines.

Our decisions sit inside lives.

Our health sits inside lives.

Our behaviour, work, relationships, learning, motivation and capacity sit inside lives too.

So when the subject is a human being, I increasingly want to understand the architecture around the question.

Who is this person?

What are they trying to achieve?

What else is happening?

What assumptions are we making?

What does this word mean to them?

What might we be missing?

Not because every question needs to become endlessly complicated.

Actually, I think the opposite can happen.

Understanding the wider system can help us identify what actually deserves our attention now.

AI has made this particularly interesting for me.

There is a lot of discussion about asking AI better questions and writing better prompts.

And yes, wording matters.

Context matters.

Instructions matter.

But that isn't the most interesting thing AI has changed about questioning for me.

The interesting part is the rambling.

I write better than I speak.

I like time to think, make connections, question myself and come back to something.

So my conversations with AI often don't begin with a beautifully engineered prompt.

They begin more like:

"I've been thinking about something..."

And then I ramble.

A lot. 😂

And that's where things often become interesting.

The response gives me something to react to.

Sometimes I agree.

Sometimes I think, No, that's not quite what I mean.

Sometimes a question makes me realise that I know something I hadn't articulated before.

Sometimes I realise that I don't know something I assumed I did.

Sometimes something from one part of my life suddenly connects with something that seemed completely unrelated.

And then I ask something else.

Or I correct something.

Or I explain what I meant more clearly.

Or I realise that the question itself has changed.

And through that process, my understanding changes too.

For me, the value isn't simply that AI can give me an answer.

It is that the dialogue gives me another opportunity to question my own thinking.

That still leaves me responsible for what I take from the conversation: checking factual claims, considering what might be missing, and deciding what makes sense to use.

And importantly, the questioning isn't the end of the process.

The exploration helps me understand what I'm actually trying to do, what context matters, what assumptions I've made and what might be missing. From there, I can create something more structured — better instructions, a clearer process, a framework, an experiment, or sometimes simply a much better next question.

The structure becomes better because the thinking underneath it has become clearer.

This may be the part I value most.

Once I've explored an idea, questioned it, connected it to other things and consolidated what I've learned, that thinking can become the starting point for the next exploration.

For me, that means deliberately saving and organising what I want to keep, and revisiting it as my understanding changes.

I don't have to reconstruct everything from the beginning every time I return to it.

My thinking can become cumulative:

That allows me to work across several projects and ideas without feeling as though every return requires me to rediscover where my brain was last time.

And interestingly, I've realised that the messiness at the beginning isn't necessarily a problem.

I used to think that a good question needed clarity first.

Now I'm wondering whether sometimes clarity is what exploration produces.

The first question doesn't need to be perfect.

It needs to give us somewhere useful to begin.

Which brings me back to the title of this article.

What happens when we ask better questions?

There's an assumption hiding inside that word.

Better according to whom?

Better towards what outcome?

And how do we know, before we've tried something, whether it really is better?

Perhaps a more useful question is:

What could I do 1% differently?

Different doesn't assume that I already know the answer.

It creates an experiment.

I can change something.

Observe.

Notice what happens.

Learn something about myself, another person or the system I'm trying to understand.

And bring that information back into the next question.

Perhaps asking better questions isn't only about becoming better at finding answers.

Perhaps it is about becoming more willing to examine what we think we know, what we might be missing, and what else could be influencing what we see.

And when we don't yet know what “better” looks like, we can start somewhere smaller.

Adapted from my article originally published on LinkedIn.