Problem Framing
How a problem is framed determines what solutions become visible — and what gets built.
Every project begins with an implicit definition of the problem. That definition determines which solutions appear possible.
Problem framing is the process of making that definition explicit, challenging it, and improving it before significant resources are committed.
Problems can be framed too broadly, too narrowly, aimed at the wrong target, or accepted without being questioned.
Too Broad
“We don’t have good visibility into what’s happening.”
That sounds like a problem.
But what exactly is the problem?
Too broad means action becomes guesswork.
Too Narrow
“We need to build a dashboard.”
Maybe.
But it could also be:
Too narrow means useful alternatives are excluded too early.
Misplaced
“We need to improve our website.”
The problem may be real, but it may not be the most important problem.
It could also be:
Misplaced means the wrong thing may be built well.
Inherited
“Customers want more features.”
This assumption may be correct. But has it actually been examined?
Questions worth asking:
Inherited means old assumptions keep directing new effort.
AI helps expand the frame. Human intelligence decides what matters.
AI-assisted exploration
Human judgment
In practice, problem framing is usually an iterative process: AI helps surface possibilities, humans evaluate them, and the frame is refined before significant resources are committed to execution.
Before discussing solutions, spend a few minutes making sure the problem itself has been framed well.
If you cannot describe the problem clearly, it is difficult to solve it well.
Different ways of framing the same situation often reveal different solutions.
Every problem statement contains assumptions that deserve examination.
Changing an assumption can completely change what the problem appears to be.
Once the problem is well framed, the right solutions become much easier to identify.
Clarify what is actually being solved before anything is built.
Decide what belongs to software, AI, and human judgment.
Produce the type of solution the problem requires.
Every project begins with assumptions about what needs to be solved. Let's make those assumptions explicit, challenge them, and identify the problem that actually deserves attention.
