LLM Lifecycle
Complete lifecycle of large language models from pre-training through fine-tuning, RLHF, and deployment — with architecture diagrams and production considerations.
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LLM Lifecycle — From Data to Deployment
The end-to-end journey of a modern large language model — from raw web text to a low-latency production endpoint. Every Staff FDE should be able to trace all five phases, because each one quietly sets the ceiling on quality, safety, cost, and latency that you inherit downstream.
A shipped model is the frozen output of a pipeline you never see. Pretraining decides what it knows; post-training decides how it behaves; inference is where you pay for it — over and over, on every single token, forever. Training is a one-time capital cost. Inference is the bill that never stops.