Takeaways, so far

Context engineering is so much more than prompt engineering. The biggest engineering challenge in giving agents context in an internal AI platform is managing data created by an organization pre-AI, never designed to be joined, where every team has a slightly different idea of how data should be stored. Quality of data in → quality of data out. It's not from inference layer.

I'd like to write about this properly once there's something I can share publicly. Until then, if you want to talk about context layers, graph indexing, or running local inference on-prem, please reach out.