What you need

Choose hardware, storage, operating system and a cloud-first, hybrid or local setup.

What this step is for.

You can begin with an ordinary computer and hosted AI. Local AI adds privacy, offline capability and cost control, but it also adds hardware requirements. RAM stores active programs and model data; GPU VRAM can accelerate compatible local models; storage matters because model files can be large.

Keep the scope small enough that you can inspect the result yourself. AI can accelerate the work, but it should not erase the distinction between a suggestion, a changed file, a successful build and a verified product.

Take one concrete action.

Inventory your current computer: operating system, RAM, free storage and GPU/VRAM if present. Then choose Cloud-first, Hybrid or Local-first. Do not buy hardware until you know which tasks require it.

Turn the idea into evidence.

Do the action in a disposable or backed-up workspace first. Write down what you expected to happen, what actually happened and what you changed when the result differed. This small habit becomes increasingly important as your AI tools gain access to more files and commands.

Do not move on until this is true.

You have a written setup choice and can explain why it fits your first project.

Why we use this principle.

Nyfir Studios treats generated output and verified output as different states. Development work on local AI, Android software and bookkeeping workflows has repeatedly shown that recoverable state, explicit tests and clear product status are more useful than simply producing more output.