Runway for AI/ML at Series B

Ehsan's Analysis

AI/ML runway planning is uniquely dangerous because costs are variable and unpredictable. An AI startup might project 12 months of runway based on current usage, then see a customer 10x their API usage in a single month (which happens — enterprise AI adoption is spiky, not gradual). If revenue does not scale proportionally (and it usually does not, because enterprise pricing is often flat-rate), a single customer success can threaten your runway. The AI runway rule: maintain a cash reserve equal to 3 months of peak (not average) inference costs. Model your runway at 2x your current API costs, not 1x, because usage will grow faster than revenue in early stages. The AI companies that managed runway well (Anthropic raising massive rounds, OpenAI's Microsoft partnership) understood that AI economics require different capitalization than SaaS. If you are building on top of foundation models, your burn is not in your control — it is in your customers' usage patterns. Plan for the worst-case usage scenario.