AI credit usage
Overview
Like many other tools, Webflow’s AI features run on a credit system. Credits are a Workspace-level resource; that is, every user in a Workspace draws from a shared pool rather than a personal one. This behavior can create a mismatch between what users do and what they might see in the product. Users could hit a limit through no action of their own because any teammate’s usage counts against the same bucket of credits.
User experience also differs by role. Admins can purchase additional credits for their Workspace, while non-admins can’t. My task was to communicate all of this clearly and concisely without leaving users with more questions than I answered.
Goal
Define the primary terminology and language for AI credit usage and depletion across admin and non-admin experiences. The language needed to be accurate without being technically overwhelming, actionable without implying permissions users don’t have, and consistent enough to scale as the credit system evolved.
Process
Before writing any copy, I mapped out my constraints:
- Fixed terminology — “AI credits” was established and finalized terminology for these units.
- Shared resource pool — Since AI credits are a Workspace-level resource, the language couldn’t imply personal fault or suggest the user did something to trigger the state.
- Role-based permissions — Admins can add credits, while non-admins can only ask their admin to act. The copy needed to fork for these experiences but remain consistent overall.
Then, I developed three directions and wrote out the UI implications for each, along with pros and cons:
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“Your Workspace is out of AI credits” — Plain language that describes the state directly and works cleanly regardless of who hit the Workspace limit. The warning-to-exhaustion progression (“almost out” to “out of”) leads users naturally to the next step: add credits or wait for them to reset.
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“Your Workspace needs more AI credits” – More positive, but less accurate. “Needs more” doesn’t clearly communicate that a limit has been reached; it reads more as a suggestion than a boundary. As a user, I might ask: Needs more credits for what? Needs more credits when?
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“Your Workspace reached its monthly AI credit limit” – Accurate, and contextualizes the limit as cyclical, but “credit limit” is a financial term that already carries meaning for users. Borrowing that connotation adds complexity without clarity, and it’s less clear and concise than the alternatives.
I also pushed for a change to the interaction model. The original usage indicator counted upward to the limit, following the pattern established for Webflow bandwidth usage. Since users can’t exceed their AI credit allowance the way they can exceed site bandwidth usage, I argued for a depletion model instead, counting down from the limit to zero to match how the system actually works.
Results
I brought the full analysis to stakeholders, recommending option #1 and the change to the usage indicator. The recommendations were approved and covered four states (admin and non-admin, at warning and at limit), each with distinct available actions but consistent framing.
Challenges
The hardest part of this project was deciding what not to explain. When money is involved, there’s pressure to surface every nuance and complexity so the product feels trustworthy. In this case, prioritizing transparency would have come at the cost of clarity and confidence.
The indicator direction was a related but separate judgment call where I opted “against” best practices. I typically prioritize consistency with established patterns, but the established pattern in this case misrepresented how the system works, so divergence was necessary to clarify the interaction model.