Flush with the proceeds of a $70 million Series B raised earlier this year, you might expect Qodo to spend freely on internal AI. After all, the startup uses artificial intelligence to ensure AI-generated code meets customer quality and governance requirements. An upstart technology company using AI to improve AI outputs is AI-pilled by definition.

Instead, the company has limits on AI consumption. Qodo CEO Itamar Friedman tells The New Stack that his engineers can access $10,000 worth of tokens per month, a cap that he described as “generous.” Most Qodo developers never reach it. The ceiling wasn’t enacted to “restrict usage,” Friedman says, but instead to drive “visibility and efficiency” at the startup so that it can “scale without runaway costs.” Put another way, the cap exists to make somebody answer this question: “Which path of automation or usage will be the best [use] of our money?”

Qodo’s AI footprint is larger than its developer token budget. The startup’s AI infrastructure spend — the cost of running the product for customers rather than the cost of its own engineers using AI — is growing at “roughly 5x year over year,” the company tells TNS in an email, reflecting both “increased user adoption” and its agents taking on more, and longer tasks as they mature. Qodo says it is pushing the other direction at the same time, driving down the cost of reviewed pull requests through routing and inference efficiency.

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