Rate Limit
What is a rate limit?
A rate limit is a constraint placed on how frequently users can make requests to an AI service or API, designed to control costs and manage system resources. In the context of AI products, rate limits determine how many times a user can interact with an LLM within a given timeframe—whether measured by number of messages, API calls, or specific use cases.
Why do AI products need rate limits?
AI products need rate limits primarily to manage costs. When teams deploy AI features, every interaction with an LLM costs money through API calls. Without rate limits, teams face uncertainty about how much their AI product will cost to operate.
Rate limits can be implemented at different levels based on user identifiers. For example, when embedding an AI tool in a learning management system, teams can rate limit based on student IDs to ensure fair access while controlling costs. This allows teams to provide AI features to users while maintaining predictable expenses.
How should teams set rate limits?
Setting effective rate limits requires understanding actual usage patterns, not just intended use cases. Teams often discover that their initial rate limit configurations need adjustment based on how users actually engage with the AI product.
For example, a team might set a rate limit of "two practice interviews per week" based on expected use cases. But if users start asking follow-up questions to get more detailed feedback—treating the AI like a real coach—they might hit rate limits "artificially" by consuming more messages than anticipated.
This kind of engagement is actually a positive signal that users find the AI valuable. When it happens, teams should revisit their rate limiting strategy to balance cost control with enabling valuable user interactions.
Learn more:
- Behind the Scenes: Building the Product Talk Interview Coach
- Building My First AI Product: 6 Lessons from My 90-Day Deep Dive
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