Agentcore

Last time I gave the agent real tools behind a real Gateway, then told you — in bold — that the front door was propped open with a brick. Anyone with the URL could list every note, write garbage, run your Bedrock bill for sport. “The fix has earned its own post,” I said. This is that post. But the lock isn’t even the interesting part. The interesting part is what comes after the lock: alice and bob become two different people instead of one undifferentiated “demo-user” sharing a single pile. The agent knows who’s talking to it, their notes are theirs, and the model had absolutely no say in making that happen. ...

Last time the agent learned to remember you: durable conversations, your preferences trailing you across sessions. It knows you like terse summaries. It knows the Q3 doc is in the shared drive. It does not have the Q3 doc. It has never had your notes. For three posts add_note has been dropping them into a Python list that lives in RAM and dies with the process, like a goldfish keeping a diary. The agent remembers the conversation about your notes. The notes themselves were a rumor it was too polite to correct. ...

Last time we put the agent in the cloud behind a real endpoint. It works, it scales, two users don’t trample each other — and it has the retention span of a mayfly. Notes live in a Python list that evaporates the instant the instance recycles. It remembers your note right up until it doesn’t, which is arguably worse than a goldfish: at least the goldfish never promised. This post gives it AgentCore Memory. Two kinds, in order of how much they’ll surprise you: ...

Previously I wrote a whole series about building an agent from scratch. The big reveal was almost insultingly simple: An agent is a while loop. The model asks for a tool, your code runs the tool, you hand the result back, repeat until it stops asking. Six hundred lines of Python, a babysitter wrapped around a language model, and you’ve got something useful, if not dangerous. I stand by every word of it. If you’ve never hand-rolled the loop, go read that series first — this one assumes you already know what a tool-call looks like coming back from the model. ...

Last time we built a notes agent with Strands and ran it in a terminal. It worked. It also ran exactly as long as I left the terminal open, which is to say: it was production-ready in the same sense that a campfire is central heating. This post fixes the “on my laptop” problem and nothing else. Same agent. Same tools. Same build_agent() from Part 1, not one line changed. The only new thing is where it runs — and the surprising part is how little code that takes. ...