Practical AI / Granata Labs
Understand the cost
of a useful result.
A model’s price is one part of the decision. Start with the work it needs to complete.
Compare the same unit.
A monthly subscription, a token rate, and a price per second buy different things. Check what is included, how usage is measured, and what happens when you reach a limit.
Count the work around the output.
Include retries, editing, human review, and the software around the model. A low price per attempt can mean little if most attempts need to be repeated.
Run one representative task.
Use the same brief with a small shortlist. Record useful results, total spend, waiting time, and review time. That gives you a practical basis for choosing.
Keep a record you can act on.
Note the task, the exact product and plan, the settings, and what you accepted or rejected. Include any editing or engineering needed to make the result usable.
The Atlas task guides provide a first experiment and a prompt to take into your preferred AI. Use what you learn to decide whether to continue, change the approach, or ask for help.