Why AI Software Development alone is not enough

The most important points at a glance

AI can significantly accelerate software development, but only sustainably if architecture, data flows and dependencies are still understood, checked and documented. Functioning code is not yet a maintainable solution. For business-critical software, it counts not only speed but also understandability, testability and operational reliability.

From our experience at symas GmbH it becomes evident again and again: the faster a system is created, the more important the clear classification of technical decisions becomes. Those who use AI in software development must look not less, but differently, closely at things.

Why AI software development must be not only faster, but better

Thomas Kehl describes in a LinkedIn post a web application that became slower over time. In the analysis, several database queries were found where one would have sufficed, missing caching, fragile dependencies as well as abstractions and functions without clear benefit. The application ran, but changes became expensive because first the thing that AI had built had to be understood.

The code was created faster than the understanding of it.
— Thomas Kehl

What principles apply in professional use?

Make deliberate architectural decisions before large amounts of code are created.
Review, test and monitor AI-generated code as productive code.
The team must be able to explain why a solution is built this way and what the consequences of a change are.

AI is well suited for designs, recurring tasks, tests, documentation, analyses and variants. It can make connections visible more quickly and accelerate implementation. The responsibility for requirements, safety boundaries, data management, interfaces and operation remains with the development team and the company.

What does a sensible workflow look like?

Start with a clear specification.
Define architecture and quality criteria.
Have AI generate suggestions or assist with steps.
Use code reviews, automated tests, performance measurements and traceable approvals.

Especially for business-critical software, speed must not be pitted against maintainability. Short-term saved development time can later be lost again due to errors, extensions or a developer change. Good AI-assisted software development therefore combines speed with understanding.

What role does symas GmbH play?

symas GmbH develops customized software, data-based models, simulations and AI solutions for Swiss companies. This includes software consulting, AI consulting and potential analysis, AI integration into existing software, AI-assisted modeling and simulation as well as tailor-made software development. The focus is on building solutions that remain comprehensible, auditable and maintainable in operation.

Frequently asked questions

How do I notice that AI makes my software faster but not better?

A warning sign is when changes suddenly become hard to understand or errors only become apparent in operation. If the code works but no one can explain the interaction of data flows, dependencies and architecture, maintainability is missing. In that case AI only saves time at the beginning.

For which tasks is AI particularly well suited in development?

According to the post, AI is especially strong in designs, recurring tasks, tests, documentation, analyses and variants. It speeds up implementation and makes connections visible faster. The professional responsibility remains with the team.

Why are code reviews and tests still needed despite AI?

Because AI-generated code is productive code and therefore must meet the same quality requirements. Reviews, automated tests and performance measurements check whether the solution truly supports the domain and technical needs. Without this control the risk of expensive rework grows.

How does symas support companies in AI in software development?

symas GmbH combines AI with conscious architecture, reviews and traceable decisions. This includes AI consulting, potential analysis, integration into existing applications, modeling, simulation and tailor-made software development. The aim is better decisions and solutions that remain understandable in operation.

Whoever wants to use AI software development sensibly should never view speed in isolation. What matters is that architecture, quality and operation grow together so that fast code becomes a reliable solution. This is where symas GmbH starts with AI, simulation and traceable software architecture.

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symas GmbH, Oberegg

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