Software development is undergoing a profound transformation. Just a year ago, Gartner predicted that by 2028, nine out of ten enterprise software engineers would use AI-based code assistants, and more than half of teams would develop LLM-based applications and agents. With recent advances in generative and agentic AI, that prediction is not only coming true but has accelerated. Today, any self-respecting developer integrates AI as the core engine of their daily work.

However, this revolution does not imply the massive replacement of developers, as some alarming headlines suggest. On the contrary, the automation brought by AI allows professionals to focus on tasks of higher strategic value. As highlighted in ComputerWorld's Software Development Special, human oversight is more necessary than ever. It's not about producing more code, but producing better code, and that's where governance and quality become priorities.

The New Mantra: Quality and Security by Design

Speed is no longer the only goal. Development teams are shifting their focus toward software sustainability, scalability, and security. The concept of security by design is not new, but it gains critical relevance in the era of democratized AI. Automated tools for identifying vulnerabilities are within everyone's reach, including cybercriminals. Ignoring this risk could have disastrous consequences for organizations.

In this context, the triad formed by automation/AI, quality, and cybersecurity becomes the pillar of success. Major industry players must strive to balance these elements, with human oversight as the backbone. Only then can robust applications be developed that do not put companies, administrations, or critical infrastructure at risk.

Integration with Modern Tools

To achieve this balance, teams are adopting platforms that unify AI, quality, and security. For example, Nx Polygraph helps AI agents navigate monorepos without crashing, while Tokiota accelerates enterprise AI with a library of use cases. Security is also reinforced with guides like virtualization with Proxmox, and the democratization of AI advances with initiatives like Accenture Edge.

Automation in deployments, as seen in Kubernetes, builds trust, but AI raises the stakes by demanding finer control. Even at events like VivaTech 2026, European talent shines, but funding to scale remains a challenge. Ultimately, the future of software development depends on how organizations integrate AI, quality, and cybersecurity, with a focus on governance and human oversight.

Original source: ComputerWorld. Analysis and adaptation by ForgeNEX.