AI systems can be highly capable within a single interaction while still losing important project understanding across longer periods of work.
The difficulty is not simply storing more conversation history.
Useful project context includes decisions, current state, constraints, open tasks, source material and what another person or system needs to continue the work correctly.
Passing everything creates noise.
Passing too little creates repetition and incorrect assumptions.
A stronger context system therefore needs to decide what information is relevant to the current task, preserve important project continuity and keep the user able to understand what is being carried forward.
The long-term value of AI in real work depends not only on model intelligence, but also on reliable context.