I have started noticing one thing that makes even the smartest AI feel surprisingly stupid.
You can spend hours working with it. Explain your business. Correct the same writing habit. Show it how you organize a project. Tell it which tool you use. Make an important decision together.
Then you come back later and somehow end up explaining half of it again.
That was annoying when AI was just a chatbot.
Now we are giving AI whole jobs.
Claude Cowork can work through folders. GPT-6 Astra can run long agent tasks. Kimi K3 can work across huge projects. Hermes can stay running as a personal agent. We are connecting agents to browsers, codebases, emails, documents, CRMs and automations.
A forgetful chatbot wastes a few minutes.
A forgetful agent can waste an entire workflow.
AI got a much bigger brain. That did not solve memory.
GPT-6 Astra can now take up to 1.05 million tokens of context. Kimi K3 has a 1-million-token context window. Claude Opus 5.5 can compact long conversations when they get too large.
That is an enormous amount of information.
But context and memory are different things.
A large context window means:
“I can read a lot right now.”
Memory means:
“I know what from yesterday still matters today.”
That second problem is much harder.
And after going through the current memory systems in Claude, OpenAI, Hermes, Mem0, Graphiti, Obsidian and newer agent setups, I think the best way to build memory is much simpler than people make it sound.
You do not need to give your agent everything.
You need to give it the right things in the right places.
Inside this guide, we are going to build exactly that: a small permanent memory, a working project memory, deeper recall when the agent needs it, automatic memory cleaning, and a simple knowledge vault you can actually open and read yourself.
First, stop putting everything into “memory”
Here is the easiest way I have found to think about this.
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