PostTrainLLM's curriculum begins with a model as a parameterized function and ends with evaluation and self-improving factory loops.
It has ten modules. Each module includes a small exercise, a repository anchor, and a mastery gate. The coverage map connects shipped subsystems back to the lesson that explains them.
That structure avoids a familiar learning trap. It is possible to read about gradient descent, tokenization, attention, and rewards while remaining unable to diagnose a failed run. A repository anchor forces the concept to meet an implementation. A mastery gate asks the learner to do something that can be checked.
The curriculum also keeps the product honest. When a component has no learning anchor, it is easier for it to become a copied black box. When the explanation and implementation disagree, the mismatch becomes visible work.
The aim is not course completion. It is being able to explain why a post-training result is real, invalid, or incomplete.
The curriculum and devlog are linked from https://posttrainllm.com/devlog.
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