Free issue No. 1
The first constraint on local AI is not the GPU
Before selecting a model and server, you need to determine whether the system produces repeatable results without turning the owner into an operator.
Five questions before buying
- What measurable outcome should appear on a regular basis?
- What input data and evidence are required for that outcome?
- Which actions can be automated and which must remain under human control?
- How much time is genuinely spent on maintenance, verification and corrections?
- Is there a backup, action log and a clear rollback path?
Signs of false automation
- The system generates drafts that a person manually sends and tracks.
- A model is selected once without quality checks on the actual task.
- A new server is purchased before measuring utilisation and API costs.
- An agent is given external actions without sources, logs or rollback.
- Reports are generated on a schedule even when they change nothing.
Practical takeaway
Local AI is justified when it regularly produces a useful asset — a verified report, code, a dataset or a finished digital product — and does so at lower cost or greater reliability than the cloud route, once maintenance is factored in.