The businesses getting real value from AI aren't getting it by accident. They're working from a system.
We wrote ours down. Four free guides, personal practice to team capability:
Collaborating with AI
AI Skills
AI Tooling
AI Workspace
https://t.co/qcjKUy8XRm
I run all of my AI work out of one local project. A workspace. Claude and Codex both operate in it. Same files, different tool, nothing rebuilt.
Providers will keep changing. That should cost you a subscription, not the thing you have been building all year.
Past a point, more instruction makes AI output worse.
Refine is the step people get wrong, because it does not just mean add more. Something comes out badly and the instinct is to write another rule.
RoleModel's full AI Skills guide: https://t.co/05Ouu1QLpE
"What problem are you trying to solve?" is a better question in a world of AI prototypes. It is also the easiest one to skip.
The risk isn't that the prototype is wrong. It's that it works well enough to stop the conversation.
A fresh chat asks generic questions.
A model that holds your prior work asks better ones, then weighs your answers against decisions you already made.
The prompt is one line anyone can copy. The context isn't.
If you need the same answer every time, stop prompting for it.
Have the model write the script. Then run the script.
The LLM is the prototype. What proves itself gets hardened.
After experimenting with fasting for the last 6 months, decide to write up my experience. An easy implement, high reward New Year's resolution. https://t.co/8TicsNMQFI