As AI costs rise, employees are competing for compute resources. The answer? Measurement and optimization.
Pylon CEO Marty Kausas faced an increasingly common challenge, described in a recent Business Insider story. As the employee count on his Anthropic plan passed 150, he was about to move into a new usage tier that would triple his costs, to $1.4M a year—and rising. So he started putting limits on AI access by his employees. "This is just the start," he said.
As AI cost pressures, and the need to show ROI, increase, Larridin is stepping into the spotlight. Larridin founder and CEO Russ Fradin sees the moment clearly. “Of course they will limit who gets to use these tools. It’s not even a question," said Fradin.
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“Of course they will limit who gets to use these tools. It’s not even a question.” — Russ Fradin, Founder and CEO, Larridin |
Just a few months ago, AI token budgets were a perk that companies had to push employees to use. Now they are a limited, and increasingly expensive, resource that employees are competing to claim. OpenAI CEO Sam Altman says that the cost has become “a huge issue,” according to the story.
The cost of AI, and how to allocate it within company budgets, is increasingly a board-level concern. According to analysis by business intelligence platform AlphaSense, the word “tokens” appeared in 57 earnings calls in Q1 2026, then more than doubled to 129 calls by Q2 2026, as shown in the chart. (Source: Alphasense.)
Engineers are advocating for token budgets, and prospective employees are asking about AI access and token policies in job interviews. Former Bain & Company AI advisor Brock Simon, now the founder of startup Native, has seen restrictive AI policies leave employees behind. “It really hurt some people’s careers,” he said.
Kausas, for his part, is determined to avoid going too far in restricting token usage. “If we told engineers that they were not allowed to use AI products, they would not work here,” he said. “It would feel like you were in the Stone Age.”
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If AI usage were restricted too much, “It would feel like — Marty Kausas, Founder, Pylon |
What's the answer? Measurement and optimization. AI usage from every source must be measured and allocated to workflows. The cost of AI usage can then be balanced against results, supporting ROI calculations and well-informed budgeting choices.
The Larridin platform supports measurement and optimization of token use across the AI lifecycle. It measures all sources of AI usage, tracks token burn against workflows completed, and helps companies calculate ROI contribution for every token used and every dollar spent.
With Larridin in place, companies don't have to make tough, and potentially harmful, choices in the dark. Customers can take full advantage of now opportunities opened up by AI, better serving their customers as they create competitive advantage.
For complete details, see the original story. If you'd like to learn more about the Larridin platform, see the description of our recently launched AI Token Spend & Insight features, or contact Larridin.