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The software development landscape is undergoing a fundamental shift. As artificial intelligence becomes increasingly integrated into our workflows, many developers worry about job security. However, Sander Hoogendoorn’s experience at iBOOD suggests a different narrative — one where AI enables new possibilities rather than simply replacing human effort.
Hoogendoorn, a software architect and developer with over 35 years of coding experience, advocates for a fundamentally different approach to software development. Rather than viewing AI as a threat, his team has embraced it as a catalyst for transformation in how they work, organize, and deliver value.
The Foundation Matters
The key insight from Hoogendoorn’s approach is that AI amplifies what’s already working well. His team’s success with AI-driven development stems from a solid foundation built over years: trunk-based development, comprehensive automation, extensive testing at every pipeline stage, and continuous deployment practices. These weren’t implemented for AI — they were there before AI but made AI integration seamless.
This raises an important point: companies operating with legacy systems and poor architectural practices won’t benefit equally from AI. Without a firm foundation, AI becomes another tool struggling within a chaotic system.
The Product Engineer Model
Rather than maintaining traditional role separations (developer, architect, product owner), iBOOD operates with “product engineers” — developers who work directly with business stakeholders. This eliminates intermediaries and creates a direct feedback loop between technical implementation and business needs.
Remarkably, this model hasn’t required team scaling despite increased output. By maintaining high standards for automation and architecture, the team remains lean while delivering more features than ever before.
What AI Actually Changes
Contrary to speculation that AI simply makes developers faster at coding, Hoogendoorn emphasizes that AI enables teams to tackle previously unfeasible projects. Building custom UI components, creating personalized IDEs, and developing domain-specific tools—work that once required months—now takes days.
Business stakeholders also benefit from these capabilities, often building functional prototypes using AI before approaching the technical team. This shifts the conversation from requirements documents to working examples.
The Real Risk for Vendors
Perhaps most provocative is Hoogendoorn’s assessment of SaaS providers. Companies like Atlassian and specialized tool vendors face existential challenges not because they need to reorganize internally, but because their products are becoming obsolete. When organizations can build custom solutions cheaper and faster than maintaining subscriptions, the market dynamics shift fundamentally.
Conclusion
The AI-native era doesn’t eliminate the need for skilled engineers—it transforms their role. The future belongs not to those who simply code faster, but to those who understand domains deeply, architect systems thoughtfully, and enable others to build safely. The developers and architects who survive will be those who evolve from “coders” to strategic partners who help organizations navigate technological transformation while maintaining quality, security, and coherence across increasingly distributed systems.