At IFIP PLM 2026 in Lecce, Italy, Oleg Shilovitsky presented a keynote that challenged one of the long-standing assumptions of product lifecycle management, tells Beyond PLM blog. For decades, engineering software has focused on managing CAD files, bills of materials, revisions, and workflows. While these systems have become increasingly effective at tracking what changed and when, they rarely capture the reasoning behind those decisions. The keynote argues that preserving this engineering knowledge is the next major step in the evolution of PLM.
Shilovitsky describes this concept as Product Memory. Rather than defining a product by its digital files, Product Memory views it as the complete collection of knowledge an organization accumulates throughout the product lifecycle. This includes design trade-offs, supplier evaluations, engineering discussions, review decisions, and the context that explains why specific choices were made. Much of this information currently resides in emails, spreadsheets, meeting notes, and, most importantly, in the memories of experienced engineers. When those individuals leave an organization, much of that knowledge disappears with them.
The keynote traces the evolution of engineering software from CAD to product data management (PDM), PLM, and enterprise resource planning (ERP). Each generation solved an important problem by improving control over product information. At the same time, each introduced another repository of disconnected data. As a result, organizations now possess extensive product records but often struggle to reconstruct the reasoning behind engineering decisions.
Artificial intelligence provides both the motivation and the opportunity for this shift. AI systems can analyze engineering information only when the necessary context is available. Simply storing files is no longer sufficient. Product Memory proposes creating connected knowledge structures that combine engineering data with design intent, enabling AI to answer not only what happened but also why it happened.
The keynote also marked the announcement of Shilovitsky’s upcoming book, From CAD Files to Product Memory, which expands on these ideas. Its central message is that the future of PLM will depend less on managing documents and more on preserving engineering knowledge as a lasting organizational asset that supports collaboration, informed decision-making, and AI-driven product development.
