A client rarely arrives with a perfectly written technical specification.
Sometimes they arrive with a sentence.
"Our current system is too slow."
Or:
"We need a new website."
Or:
"Can you automate this process?"
These statements are useful.
But they are not enough to start building.
What does "too slow" mean?
- Too slow for whom?
- At what point?
- How often?
- Compared with what?
- Is the system technically slow, or does the process feel slow because someone has to perform several manual steps?
The first job is not necessarily to write code.
It is to understand.
Listen for the problem behind the request
People naturally describe solutions.
A client might ask for a mobile application. But perhaps what they actually need is a simpler way for field staff to submit information.
A client might ask for an automated email system. But perhaps the underlying problem is that nobody knows which customers need follow-up.
The requested solution can be useful information.
It should not automatically be treated as the final specification.
Good questions create clarity
Useful questions might include:
- Who is experiencing the problem?
- What are they doing today?
- What is difficult about the current process?
- How often does this happen?
- What happens when it goes wrong?
- What would success look like?
- Are there constraints we need to understand?
- What absolutely needs to happen?
- What would be useful but can wait?
These questions turn a vague request into something you can work with.
Requirements are a shared responsibility
Understanding requirements is not about making the client do all the work.
You bring technical knowledge.
The client brings knowledge of their business, users and processes.
The useful solution comes from combining those perspectives.
Sometimes you will need to explain why a requested approach has a technical limitation.
Sometimes the client will explain something about the business that changes your technical assumptions.
Both sides need to listen.
The danger of building too early
One of the most expensive mistakes in software is building something that nobody actually needed.
- You can write excellent code.
- You can build a beautiful interface.
- You can deploy it successfully.
- And still fail to solve the problem.
That is why requirements work matters.
It reduces the chance that technical effort is spent moving in the wrong direction.
AI cannot have the client conversation for you
- AI can help turn notes into requirements.
- It can help identify missing questions.
- It can suggest edge cases.
- It can help structure documentation.
But it cannot replace your responsibility to understand the people involved and the context in which the software will be used.
A technically correct solution can still be the wrong solution.
The lighthouse starts before the coding
The lighthouse is not only useful when you are already at sea.
It helps you understand where you are going.
In professional work, clarity about the destination comes before choosing the route.
Before building, make sure you understand what "success" actually means.
Good software starts with good understanding.