This article from the How Do YOU CM2? series emphasizes the importance of capturing design rationale in decision-making for effective knowledge management. It highlights how failing to document the reasoning behind design choices leads to inefficiencies, particularly for new hires. AI can assist in documenting these rationales seamlessly during the engineering process, improving future decision-making.
This article discusses the integration of AI in configuration management, highlighting the challenges posed by probabilistic decision-making compared to deterministic systems. It emphasizes the need for governance frameworks to validate AI outputs against compliance requirements and establish confidence thresholds for manual review in decision-making processes.
This article discusses challenges of AI-assisted product changes, particularly context degradation in large language models as conversations progress. It introduces scaffolding, a structured approach to maintain contextual integrity in change management. By emphasizing task decomposition and context engineering, organizations can improve AI performance and enhance governance in engineering workflows.
Rob Ferrone’s and Oleg Shilovitsky’s LinkedIn bromance 😉 has resulted in an interesting post by Oleg: How to Build PLM Applications We Love Using AI. His premise (my interpretation) is to build Minimum Loveable PLM applications as small applications supported by AI that fulfill a specific purpose using data from a shared data platform. No MVPs, but MLPs! Around the same time, Michael Finocchario published The Agentic AI Revolution: Reimagining PLM as… Read More »How the CM Baseline and Agentic AI enables the future of Enterprise applications.