Where We Are Now
A checkpoint - the architecture as it stands so far.
Half the series is behind us. Before we add the harder pieces, it's worth stopping to see the whole shape of what's standing, because everything next builds on it.
What's standing
You have a server on Azure that any AI can connect to. It signs clients in, lists its tools, and runs them. Its tools reach out to Azure and GitHub, and you can add more. It carries its own instructions so every client behaves the same. It lives in one resource group with a cost cap, and it can stamp another copy of itself when you need one.
What you can do with it today
Connect Claude or ChatGPT and ask it about your cloud: what's deployed, what it's costing. Ask it to make a change and it can. Ask it to add a tool and it will edit its own code and redeploy. That is already a real, useful system, and it is running for about the price of a coffee a month.
What it does not have yet
It can act, but it cannot remember much, and it cannot answer from your documents. There is no knowledge layer: no place to put information and have the system retrieve it by meaning (see RAG, in plain English for the idea). That is the gap the back half of the series fills.
What's next
The control plane is done; now we give it a brain. The next pieces add the service side: a place to store and retrieve knowledge, scoped access to the outside world, and an agent that uses all of it to actually manage your cloud. That is a second project, stacked on this one.