CoreStory: Garbage Context In, Garbage Code Out - Fixing AI’s Real Problem

Many experienced developers do not trust AI-generated code, and in the case of a large codebase that the agent has never comprehended, they are right to feel this way. The issue is not with the model; it lies in the absence of context. Without a structured, up-to-date understanding of the codebase, agents make erroneous assumptions, replicate existing logic, and introduce changes that were not requested. This session directly addresses the skepticism and demonstrates the improvements that occur when developers and their AI agents operate from a persistent intelligence layer rooted in the code: fewer errors, fewer regressions, and output that developers can genuinely review and rely on. Designed for engineers who wish for AI to prove its worth in the workflow, rather than simply being enforced into it. Series Info - https://aka.ms/StartupSpotlight/S-1443 [EventID:27460]