The AI honeymoon is ending

It feels like the AI pricing honeymoon phase is starting to end.

For the last year or two, we've gotten used to incredibly cheap access to powerful models but that was never going to last forever. We've already seen reports of companies like Meta, Tesla, and Uber putting limits on internal AI usage as compute costs keep climbing.

Now it's showing up in public APIs too. DeepSeek, practically the poster child which built a reputation for low-cost models is introducing peak-hour pricing for its upcoming V4 release. In simple terms, when demand is high, API prices go up.

It sounds a lot like surge pricing for GPUs and I think this changes how people build AI products.

On the positive side, I think this pushes the ecosystem in a healthier direction.

Instead of every team rebuilding the same pieces over and over, we'll probably see more specialized products that solve one part of the workflow really well. It saves teams from spending weeks building infra that already exists.

Firecrawl is a good example of helping teams handle web scraping and data ingestion instead of maintaining that infra themselves.

Chatbase is another example which helps teams turn their own docs and internal knowledge into AI assistants without having to build an entire chatbot from scratch.

That means engineers can spend more time working on the product itself instead of rebuilding another piece of infra.

As token costs become less predictable, that kind of specialization becomes a lot more valuable. The winning teams probably will be the ones putting better systems around those models.