Context Engineering Blog

Have you ever asked an AI coding assistant to implement a new feature, only for it to generate code that’s completely incompatible with your existing architecture? The root cause is almost always a failure in context engineering. A 2023 study found that AI developers spend up to 70% of their time on data-related tasks, including sourcing and preparing context. This isn’t just an annoyance; it’s a critical bottleneck that determines whether an AI is a powerful partner or a frustratingly inefficient tool.