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Knowledge Engineering
Paradigm 1
Performance curve
Logarithmic
Scaling behaviour
Ceiling
Early compute
Efficient ✓
High compute
Saturates ✗
Discovery
Limited to encoded knowledge
⚡
Scale + Learning
Paradigm 2
Performance curve
Power law
Scaling behaviour
Unbounded
Early compute
Inefficient ✗
High compute
Keeps improving ✓
Discovery
Discovers unknown patterns
What this means for engineers building today
1
Know where you are on the compute curve. If your compute budget is low and your domain knowledge is high, Paradigm 1 may still win. But know the ceiling exists.
2
Infrastructure investment compounds; clever features don't. The team that can run 50 experiments per week beats the team with the most elegant hand-crafted pipeline.
3
The crossover has already happened in most domains. If you're still investing heavily in feature engineering for text, images, or structured prediction, check whether you are past the crossover point.
4
The Bitter Lesson doesn't mean humans are irrelevant. It means the value moves: from encoding knowledge to specifying objectives, building evaluation, and interpreting emergent behaviour.