Something I’ve been noticing that I don’t see written about much. AI coding tools that build persistent organizational understanding are starting to change the onboarding experience for new engineers in a specific and interesting way. The traditional onboarding problem: a new engineer joins a team with years of accumulated conventions, internal libraries, architectural decisions. They spend the first three to six months building that mental model. During that period their output is limited and they lean heavily on senior engineers who have to context-switch to answer questions. It’s expensive in time for everyone. An AI coding tool with genuine organizational contextual intelligence changes that dynamic. The new engineer gets suggestions that reflect the actual codebase conventions from day one. They see correct pattern usage demonstrated in every suggestion rather than learning by mistake and correction. The senior engineer still needs to be involved but the volume of “why are we doing it this way” questions drops because the AI is demonstrating the how even if it can’t explain the why. This isn’t a solved problem and the tools aren’t perfect at it. But the direction is interesting. Has anyone been tracking onboarding metrics alongside AI coding tool adoption? Curious whether the time-to-productivity curve has actually shifted. submitted by /u/AssasinRingo
Originally posted by u/AssasinRingo on r/ArtificialInteligence