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I recently talked to a Series B founder who told me their Anthropic bill would soon jump from $400,000 to $1.4 million per year.
This is at a software company with 150 employees and only covers internal use of AI.
The company is Pylon, a support platform built for B2B. Co-founder and CEO Marty Kausas went viral after posting about how they face a 3.5x overnight cost jump from Anthropic.
This cost jump didn’t have to do with Pylon’s AI usage exploding. It was because they were about to pass 150 seats, which is when Anthropic forces customers into their Enterprise tier according to Marty. Enterprise seats no longer include subsidized usage meaning that every token is billed at Anthropic’s standard API rates. Given Pylon’s AI consumption, this was a wakeup call.
The Information reported on Anthropic’s new enterprise pricing in April 2026
Pylon is far from the only company seeing truly eye-watering AI bills and wondering what to do about it. As much as there’s talk about AI costs coming down – OpenAI is reportedly considering “drastic price cuts” – frontier models continue to get more expensive.
Anthropic’s splashy new model, Fable 5, is finally available (again) to the public. Fable 5 will soon move off subscription plans; however, and require usage credits. The sticker price of this usage – $10 per 1M input tokens, $50 per 1M output tokens – is about twice as expensive as Opus 4.8. Fable 5 also produces longer responses on the same prompts. On a cost per task basis, Fable 5 is estimated to cost about 3-5x Opus 4.8 and 10x Sonnet 4.6. Ouch.
The TL;DR: AI bills are likely to keep going up, not down. Today’s post unpacks the looming AI cost crisis and what GTM teams can do about it — without killing AI adoption.
A huge thank you to Marty Kausas (co-founder and CEO at Pylon), John McCauley (CFO at Vanta), Dan Zhang (CFO at ClickUp), and Sonalee Parekh (CFO at SentinelOne) for sharing their insights.
We panicked our way into this crisis
This is a pretty strange piece to write because the AI cost debacle is a completely invented problem.
We as an industry created this problem.
We panicked and pushed AI adoption over all other things. And “we” means panicked investors, which trickled down to founders, then management teams, and finally scared employees who didn’t want to get fired because they didn’t use AI.
If you’re anything like me, you spent nights and weekends learning Claude Code or Cowork possibly because everyone else was doing it. You set up all the context that Claude needs to deliver reliable outputs. You turned your GTM expertise into custom Claude skills.
Now that AI finally (for the first time!) feels like it’s working for GTM, there’s a new crisis. It’s gotten insanely expensive to keep running the AI workflows you worked so hard to build.
The whiplash is exhausting. But the rent (LLM tokens) is still due.