The first wave of Gen AI in software engineering has been dominated by coding assistants. But coding is only one part of the product development lifecycle. A team can produce more code and still move slowly because of unclear requirements,…
By Dmitry LopatikIn the first article, I argued that Software-Defined Vehicles (SDVs) are fundamentally a business transformation challenge, not simply an AI challenge. In the second, I explored why Software-Defined Vehicles require Software-Defined Organisations. Delivering software throughout a vehicle’s lifecycle demands…
By Dmitry LopatikIn the first article, I argued that Software-Defined Vehicles (SDVs) are not simply an AI or software engineering challenge. They represent a much bigger business transformation. Building the software is only one part of the equation. The harder…
By Dmitry LopatikFor years, the automotive industry has been fixated on one question: how do we build Software-Defined Vehicles? The industry has made significant progress in answering that question. The harder problem is what comes next i.e. delivering software at…
Almost every CTO is being asked the same question.“How quickly can we add AI to our product?”It sounds like the right question, but the better question is far less exciting.“Is the product actually ready for AI?”This distinction is important because…
Walk into almost any boardroom discussing AI, and the conversation eventually reaches the same conclusion.“Our products weren’t built for this.”The statement is usually followed by another.“We probably need to rebuild.”It sounds logical. It is also where many modernization programs begin…
Every major technology shift eventually changes how engineering teams work. Cloud computing changed infrastructure ownership. DevOps changed the relationship between development and operations. Microservices changed how software was designed, deployed, and maintained.AI is often described in similar terms. Most conversations…
For decades, product development followed a familiar rhythm.Business teams identified an opportunity. Product managers translated ideas into requirements. Designers created user experiences. Engineers built the software. Test teams validated quality. Operations deployed the release. Customer feedback informed the next iteration.Development…
Software has always evolved in waves. The first generation of enterprise applications digitized paper-based processes. The next generation moved those applications to the cloud and introduced the Software-as-a-Service (SaaS) model. Instead of purchasing perpetual licenses, organizations subscribed to software that…
If the first wave of enterprise AI was about proving value, the next wave is about making that value scale. And this is where many organizations are encountering a structural limitation they hadn’t anticipated.Despite strong individual use cases, AI initiatives…