AI is transforming software development, but not necessarily improving code quality

Giulio Rusciano
3 min readJan 27, 2025

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Software quality has never been limited solely by how fast we can write code. The real challenges — understanding requirements, designing maintainable systems, handling edge cases, ensuring security, and optimizing performance — still require human judgment, experience, and most of all, critical thinking.

Software development is not just about writing code (as fast as possible); it’s about solving the right problems in the right way. High test coverage, robust code reviews, and rapid coding are essential practices, but they are merely tools to help us achieve the true goal — delivering value to users.

An AI agent can enhance these processes, but it cannot replace the strategic thinking and problem-solving skills that are fundamental to successful software projects. This is precisely why AI delivers the best results when guided by an expert developer who can harness its capabilities effectively.

Accelerating the iteration process

What AI does exceptionally well is accelerating the iteration process. It enables us to prototype ideas quickly, explore multiple approaches, and gather feedback at an unprecedented pace. This increased velocity can lead to better solutions by allowing teams to test hypotheses and refine their designs more efficiently. However, speed without direction can be dangerous. Without proper engineering discipline, AI can introduce more technical debt, create fragile systems, and foster a culture of shortcuts that ultimately undermine software quality.

AI tools can assist us in writing code faster and automating repetitive tasks, but they cannot replace the need for deep domain knowledge, thoughtful system architecture, and an understanding of users’ needs. If used without careful guidance, they can lead to suboptimal solutions that may look good on the surface but fail to deliver long-term value.

Balancing AI’s power with Engineering discipline

To harness AI’s full potential, we must stay grounded in our core software engineering principles. This means:

  • Prioritizing clear requirements: AI can generate code, but it can’t understand the nuances of business needs or user expectations.
  • Focusing on maintainability: Rapid code generation should not come at the cost of creating unreadable or unscalable systems.
  • Ensuring security and performance: AI can assist in optimization, but human oversight is crucial to prevent vulnerabilities and inefficiencies.
  • Iterating with purpose: Faster iteration cycles enabled by AI should align with strategic goals rather than becoming an exercise in speed for speed’s sake.

Used effectively, AI can free engineers from mundane tasks, allowing them to focus on innovation, creative problem-solving, and higher-level design. But it must be guided by a clear understanding of what quality software truly means.

The Human Factor remains essential

At the end of the day, software development is about people — both the developers building it and the users benefiting from it. AI can support us in getting there faster, but it’s still up to us to define what “better” means and how to achieve it.

To truly build great software, we need to embrace AI as a powerful ally, not as a replacement for the engineering discipline that underpins every successful project.

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Giulio Rusciano
Giulio Rusciano

Written by Giulio Rusciano

20+ yrs in technology leadership, design, development & entrepreneurship, I'm a creative technologist who blends design & tech to bring innovative ideas to life

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