The cascaded inference piece is brillaint tbh. We ran into this exact problem where every query was hitting GPT-4 for tasks that could've been handled by way cheaper models. The breakdown of the six-layer cost stack really clarifies where the money actually goes, especialy the retrieval inefficiency part. In my experience, RAG systems are the most underestimated cost multiplier, like retrieving 10 chunks when 2 would do the job creates this silent burn that nobody notices until the bill comes. The idea that cheaper systems are fragile but efficient systems scale is kinda the whole point here.
This playbook highlights a truth many teams miss: AI cost isn’t just about model pricing — it’s about how the entire system is structured and how inefficiencies can compound unnoticed. Optimization isn’t a hardware problem or a “just use a smaller model” trick — it’s an architecture discipline that spans context, retrieval, agent loops, error retries, and token management, and only by understanding those interactions can you build systems that are both performant and economic at scale.
The cascaded inference piece is brillaint tbh. We ran into this exact problem where every query was hitting GPT-4 for tasks that could've been handled by way cheaper models. The breakdown of the six-layer cost stack really clarifies where the money actually goes, especialy the retrieval inefficiency part. In my experience, RAG systems are the most underestimated cost multiplier, like retrieving 10 chunks when 2 would do the job creates this silent burn that nobody notices until the bill comes. The idea that cheaper systems are fragile but efficient systems scale is kinda the whole point here.
Thank you so much for reading! Glad you liked it.
This playbook highlights a truth many teams miss: AI cost isn’t just about model pricing — it’s about how the entire system is structured and how inefficiencies can compound unnoticed. Optimization isn’t a hardware problem or a “just use a smaller model” trick — it’s an architecture discipline that spans context, retrieval, agent loops, error retries, and token management, and only by understanding those interactions can you build systems that are both performant and economic at scale.