Pricing
How to Price AI Summaries Without Getting Weird
The clean version is simple: let people get to the first good result for free, then charge in a way that stays legible after every run.
Start with trust, not a paywall
Most AI products ask for money before the user has learned whether the output is any good. That is backwards. For a summary product, the first job is to get someone from curiosity to one genuinely useful reading edition.
That is why the product starts with free summaries. The user should be able to try real URLs, compare the output to the source, and decide whether they would ever return.
Metered usage is fine if the math stays visible
The cost of a summary is tied to the actual model work involved. Pretending otherwise usually leads to fake unlimited plans, vague fair-use language, or pricing that makes sense only for the company.
Prepaid credits are less glamorous, but they are honest. They let the product pass through upstream model cost with a visible markup, and they spare the user from surprise end-of-month invoices.
Every charge should explain itself
After a run, the user should understand what happened. How much source text was processed. What it cost upstream. What margin was added. If the explanation needs a support article, the pricing model is already too clever.