Add Usage Limits

Define honest usage limits that tie price to value received and stop a minority of heavy users consuming the entire margin.

Pro involved Offer Improvement Recipes

What it adds

Fixes the unlimited or undefined offer where cost scales with consumption but revenue does not, and light users effectively subsidise heavy ones. The AI builder examines usage distribution and cost data in the source files to set limits that leave the great majority unaffected, then presents them as fair rather than restrictive. The outcome is protected margin and pricing that grows with the value each customer receives.

What your builder is told to do

The actual instructions, in order.

1
Inspect the source files and plot the usage distribution: what the typical customer consumes, what the upper range consumes, and where cost per account rises steeply.
2
Set limits above the level the overwhelming majority of current customers reach, so the change protects margin without penalising normal use.
3
Define what happens at the limit — soft warning, pause, or overage charge — and state it plainly. Silent throttling produces support tickets and cancellations.
4
Give every limit an upward route: a higher tier, an overage rate, or an add-on pack, each priced against documented cost rather than an arbitrary multiplier.
5
Separate structural changes from copy changes: structural work is metering, threshold enforcement, notification triggers, and the upgrade or overage mechanism; copy work is the limits table, the at-limit messaging, and the fairness rationale.
6
Grandfather or transition existing customers who exceed the new limits on written terms, with advance notice, rather than enforcing retroactively.
7
Specify responsive behavior: on mobile, current usage against the limit shows as a single progress row on the account screen with the upgrade action beneath; on tablet, usage and limits render as a two-column table; on desktop, the full limits table appears on the pricing page with current usage visible in the account area without navigation.
8
Define tracking: measure the share of customers reaching each limit, cost per account before and after, upgrade rate at the limit, and cancellations citing limits. Rollback rule — raise the threshold if cancellations attributed to limits exceed the margin recovered.

Edge cases it handles

The things an agent skips when you only say "build a add usage limits".

Never apply new limits retroactively to existing customers without notice and a stated transition period.
Preserve any unlimited commitment already made in the source files; if one exists, honor it for those customers and apply limits to new accounts only.
Set thresholds from observed distribution, not from round numbers that happen to look tidy.
Notify customers before they hit a limit, not after service has already changed.
Do not use limits as a hidden price increase; if cost recovery requires a higher price, price it openly instead.

Definition of done

Your builder is required to check every one of these before reporting the work finished.

Usage distribution and per-unit cost are documented from the source files and used to set every threshold.
Each limit has a defined at-limit behavior and a priced route to exceed it.
Existing customers above the new limits have a written transition policy with advance notice.
Before and after cost-per-account figures are recorded alongside the share of customers affected.
Mobile, tablet, and desktop presentations of usage and limits are each specified.
Limit-attributed cancellation tracking is defined with a written threshold-raising trigger.
The builder reports which source files it used and flags any cost or usage figure it could not verify.

Related offer files

Offer Improvement Recipes

Create An Order Bump

Insert a single low-friction add-on at checkout that completes the purchase without pulling attention off the main decision.

Offer Improvement Recipes

Split Into Tiers

Break a single take-it-or-leave-it offer into tiers that capture buyers at different budgets without gutting the core promise.

Offer Improvement Recipes

Repackage As A Bundle

Merge scattered standalone products into one coherent bundle solving a complete problem, priced below the sum of its parts.

How it works

1

Copy the link

Grab the Markdown blueprint URL for this offer type.
2

Give it to your builder

Paste it into Claude Code, Cursor, Codex, or whatever AI builder is already working in your app.
3

It maps, then builds

Your agent reads the blueprint first, then builds the offer into your app around the product, audience, and stack.

Works with your stack

These blueprints are written to adapt. They tell the agent to detect your framework, match your existing design system, and use your source files instead of guessing the offer.

Need it tighter than that? Customize the offer file and tell it exactly which source docs and stack to use.