AI is making software development faster, more automated and more factory like. Code can be generated in seconds, tests created automatically and ideas moved toward production with less effort.
But speed does not replace clear intent, sound architecture, independent verification, security, ownership or operational feedback. When these foundations are weak, AI can produce convincing results while moving cost and risk into review, release and production.
This session examines why software delivery fundamentals matter more as AI adoption grows. It considers how technical and business leaders can recognize false confidence, set appropriate boundaries and maintain accountability across an AI enabled SDLC. The discussion is organized around three questions: What is true? How is it proved? How do we recover?
The aim is not to slow the factory down. It is to help ensure that faster output becomes software that can be understood, operated and sustained.
Sini TistelgrénCo-Founder, COO & Tech Lead at Aimbition
Sini Tistelgrén is Co-Founder, COO & Tech Lead at Aimbition. She has nearly 15 years of experience in IT, leading teams, shaping strategy, driving AI initiatives, and managing complex multi-vendor projects. Her work focuses on making AI adoption in software engineering practical and human-centred by aligning people, technology, and processes.