The Model Is Not The Problem: The Engine Is The Problem

Thanks to Charles Sullivan for giving this talk!

**The Model Is Not The Problem: The Engine Is The Problem**

There is a massive disconnect in AI. We have five discrete but interconnected problems with inference in 2026:

* The streaming problem. Inference is a black box: wall of text in, pull the lever, wall of text out. No streaming, no back-and-forth, no iterative progress.

* The memory problem. The LLM can't remember anything. It pretends to remember by re-reading context on every request, but it doesn't actually remember.

* The learning problem. The LLM can't internalize anything. If the capital of France were to change tomorrow, we would have to add the new capital to the system prompt to be re-read on every pass. And learning new skills is completely out of the question.

* The text problem. Underpinning all of this is the fact that all "memories" (e.g. from RAG) and "skills" (e.g. tool calls) are plain text. That would be like remembering a concert by reading notes about it. Th