Read the full article here: https://strategystack.io/blog/question-everything
If you don’t understand the outcome, the tech questions are noise. Most delivery problems start in meetings, not in code.
One of the hardest parts of a new story isn’t the implementation.
It’s the meeting where someone asks, “Any questions?” and you’re still trying to understand what the ticket even is.
You’re mapping the domain.
You’re decoding stakeholder language.
You’re trying to understand intent, scope, and constraints at the same time.
And now you’re supposed to ask “good questions.”
Most engineers default to technical questions:
What framework are we using?
Is this a new table or an update?
Is this synchronous or async?
Those aren’t bad questions. They’re just early. If you don’t understand the outcome, the rest is guesswork.
When you’re working with non-technical stakeholders, requirements are written in outcome language, policy language, or compliance language. Not engineering language. If you start at the tech layer, you’re building on fog.
The first question should always be:
“What should be true when this is done?”
Not how.
Not with what.
Not in which service.
Outcome first. Everything else follows.
Most delivery drag doesn’t come from bad code. It comes from misunderstood intent.
And here’s the uncomfortable truth…
Most engineers aren’t bad at coding. They’re bad at clarifying.
They try to listen, think, and write at the same time.
They miss context.
They miss nuance.
Their notes are useless later.
That’s not a skill problem. It’s a tooling problem.
This is where AI is real leverage.
Record the meeting.
Get the transcript.
Let AI structure the chaos.
Now you can extract intent, identify ambiguity, and come back with precise questions. Not guesses.
Domain understanding beats syntax every time.
The engineers who move fastest aren’t the ones who type the quickest.
They’re the ones who clarify the best.
That’s what quality software engineering looks like.
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