LESSON 3.10 · Assessment · 240 min
Mastery Gate 3: draw and implement GPT closed-book
Mastery Gate 3: draw and implement GPT closed-book. Learn architecture, objective, training, and generation as one system and complete: Whiteboard, implement, and train on a new co
Learning objectives
- Explain what problem “Mastery Gate 3: draw and implement GPT closed-book” solves without hiding behind terminology.
- Trace the variables and causal links across architecture, objective, training.
- Complete “Whiteboard, implement, and train on a new corpus” and judge the result with evidence rather than intuition.
Core concepts
architecture
architecture is part of the lesson’s causal model. State its inputs, outputs, invariants, and failure mode; then verify it with a hand-check or a minimal experiment before moving to an optimized implementation.
objective
objective is part of the lesson’s causal model. State its inputs, outputs, invariants, and failure mode; then verify it with a hand-check or a minimal experiment.
training
training is part of the lesson’s causal model. State its inputs, outputs, invariants, and failure mode; then verify it with a hand-check or a minimal experiment.
and generation as one system
and generation as one system is part of the lesson’s causal model. State its inputs, outputs, invariants, and failure mode; then verify it with a hand-check or a minimal experiment.
Build and verify
Whiteboard, implement, and train on a new corpus
- Predict: write the expected output, trend, or failure before running code.
- Build: implement only the minimum components needed to answer the question.
- Verify: compare with a baseline or trusted implementation; save seeds, parameters, and raw outputs.
- Transfer: change one shape, dataset, scale, or workload condition and explain whether the conclusion still holds.