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Most AI agents feel smart in the moment.
Then you start a new chat.
And it forgets everything you just taught it.
That “amnesia” is why most agent demos never become real workflows.
You keep paying in time, context, and rework.
I noticed something important this week.
The next wave of agents won’t win on prompts.
They’ll win on memory and execution.
Nous Research just shipped Hermes Agent, and the idea is simple.
It turns your wins into searchable markdown Skill Documents.
So the next time you need that workflow, it repeats it quickly.
The second shift is even bigger.
Persistent terminal access.
Local.
Docker.
SSH.
Even HPC containers.
That means the agent can actually run.
Not just talk.
It can work for hours while you sleep.
Then ping you when it’s done.
Imagine a weekly ops task that takes 90 minutes.
If an agent learns it once and reruns it every week, that’s 78 hours saved per year.
Per person.
Here’s the playbook ↓
↳ Pick one repeatable workflow you hate.
↳ Define “done” in plain English.
↳ Store the steps as a reusable skill.
↳ Give it a real terminal and a safe sandbox.
↳ Review outputs like you would a junior teammate.
The hidden advantage is compounding.
Your best process becomes a repeatable asset.
What’s the one workflow you’d most want an agent to learn once and run forever?
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