Learning path · Foundations · 02
LLM as Reasoning Engine
A general inference layer: it turns inputs into language and decisions. It is not a database of your company's facts.
Why it matters
- Stops the habit of expecting weights to store fresh facts.
- Shows where retrieval, tools, and memory belong.
- Keeps product design honest about what the model can hold.
Key ideas
- Inference, not storage
- Stack around it
- Facts live outside
An LLM is good at reading intent, following instructions, and drafting a plan. It will not reliably remember yesterday's ticket queue or a private policy unless you put that text in the request. Split the job: the model reasons over evidence you supply; indexes, APIs, and workflow state hold the facts. Draw those lines so the next engineer does not "just ask the model" under deadline pressure.
Updated 2026-08-09 · Full learning path