This article highlights the unexpected complexities of scaling AI text generation, particularly regarding API rate limits. The author discovered that OpenAI's rate limits are multi-dimensional (RPM, TPM, TPD) and independent, causing failures even when basic limits seemed to be met.
The article reflects on the Treasure Hunt Engine's launch, a year after its rollout, which aimed to revolutionize gaming with AI-driven mechanics. The primary challenge, however, wasn't the AI but efficiently scaling servers and infrastructure to handle rapid growth and increasing traffic without succumbing to latency issues.
A treasure hunt engine experienced severe failures and a high error rate (30%) upon hitting a growth inflection point. The initial Veltrix configuration with caching and horizontal scaling proved insufficient for 10,000 concurrent users, leading to 5-second latency and user drop-offs.