Engineering Has A Context Problem, Generative AI Is The Fix

TechEngineering Has A Context Problem, Generative AI Is The FixByYu Fang,Forbes Councils Member.for Forbes Technology CouncilCOUNCIL POSTExpertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. | Membership (fee-based)May 26, 2026, 07:15am EDTYu Fang is Co-Founder & CTO at Sonatus, specializing in distributed systems and AI-enabled vehicle architectures. gettyModern products behave less like applications and more like ecosystems. A single customer experience spans embedded controllers, cloud services, mobile apps, supplier components and real-time data pipelines. As challenging as it can be to build these systems, the bigger challenge for engineering teams today is understanding them. ​Every organization is facing the same problem: engineering teams don’t lack data. They lack context for that data. ​Critical information lives everywhere and nowhere at once. Design documents, test logs, manufacturing notes, field reports, supplier data, customer tickets—each holds a fragment of the truth. But no engineer, no matter how experienced, can stitch these fragments together fast enough to diagnose issues confidently. Systems generate more context in a week than a team can reasonably review. ​This is the context trap: the information exists, but it’s too fragmented, too unstructured or too distributed for any human to gather manually. ​Why Traditional Diagnostics Fall Short For decades, engineering teams relied on structured signals like logs, metrics or sensor data to understand failures. These signals are essential, but they represent only the visible tip of the iceberg. The real root causes often live in the submerged mass below the waterline: ​• A configuration change buried in a release document • A pattern across historical incidents• A dealership report describing behavior outside formal tests ​Traditional tools couldn’t unify these signals because they spanned formats, systems and organizations. The result was th...