AI writes code in seconds. Whether it solves the right problem is for a person to judge.
AI writes clean, working code in seconds today. So software quality is no longer measured only by how the code is written. It's measured by whether it solves the right problem and whether you can still rely on it in two years.
Nobody is afraid AI will write the code. They're afraid of what comes next
In the last two years, software development has changed more than in the previous twenty. A feature that once took days to build has a prototype in an afternoon. Documentation and tests can be generated with a single instruction.
But developers aren't worried about whether AI can write code. They're worried about what happens next. Writing code was never the hardest part of development. The hardest part was always building the right solution for a real business problem.
Quality has moved from code to decisions
Readable, clear and easy-to-maintain code still matters. But today AI handles much of that on its own. A different question has become the hard one: is this even the right solution?
IBM names it with two terms: implementation quality and decision quality. Good code is getting easier to achieve. Good decisions are getting harder, and they are what makes the difference. AI isn't good at comparing different approaches, doesn't see the long-term business context and doesn't know when the simplest solution isn't the best.
With a person
A skilled builder will lay your driveway quickly and neatly. Whether it should lead to the main entrance or to the warehouse where the trucks go has to be decided by someone who knows how the site runs.
With AI
AI builds a feature quickly and nicely. Whether it should be built this way, how it behaves during an outage and what it does with ten times the customers has to be judged by a person who knows the whole system and the company.
“An online shop wants to send customers order status notifications. AI produces everything needed in minutes. But an experienced developer asks: what happens when the email service is down for an hour? Is the notification resent, or lost? And what about Christmas, when there are ten times more orders? The code doesn't answer these questions on its own.”
One change touches the whole system
Code used to be reviewed file by file. Someone looked at the changed lines, wrote a few comments and approved. Today, every change affects several things at once: connections to other systems, data, security, monitoring.
So the question changes. “Is this feature correct?” is no longer enough. You need to ask: “What will this change do to the whole system?” AI can write the code. Understanding the system is still a person's job.
Tests are the proof of quality, not the author
If AI wrote a feature, how do you know it's correct? Code can look elegant and have nice comments. But it's only correct once you verify its behavior.
That's why tests are turning from good practice into the main proof of quality. Automated tests, security checks, performance measurement and monitoring in production. We used to trust code because a person wrote it. Today we trust software because we've verified what it does.
Rules belong in the process, not in a document
Many companies have a document with development rules that nobody reads and that is outdated in six months. With AI development, that doesn't work at all. Rules have to be built right into the process:
- security requirements are checked automatically,
- tests are part of every change,
- code review runs continuously, not once before launch.
The goal isn't to remind people of the rules, but to make sure the right way is the easiest way. AI then works within clear boundaries and doesn't rely on what “everyone knows”.
Quality is not a check at the end
Quality control used to be the last stop before launch: a final check, a tester's sign-off, a checklist. That made sense when software was released twice a year. Today it changes continuously, and with AI even faster. So quality has to be checked with every change, from planning to production.
“Code and access are always in the client's name, and we give a 60-day warranty. Both only work when the code isn't a black box but a system with tests that someone else can take over after us. And the client talks to the person who builds, so decisions aren't made by a middleman.”
What becomes most valuable
AI doesn't replace developers. It changes what makes them valuable. The most valuable thing is judgment: asking good questions, understanding the system as a whole and knowing when to trust AI and when to question it.
For management, the advice is simple. When choosing a supplier, don't ask how fast they write code. Ask how they verify it's correct, and who will understand the system when the project ends.
Ask yourself
If you changed suppliers tomorrow, could the new team understand what your system does from its tests and documentation?
