The fastest way to be displaced by AI is to stay at the level AI operates at most comfortably. Monday we established that AI cannot do architecture: the training data problem is structural, not temporary, and the gap between generating plausible-looking code and designing systems that survive contact with the real world is not closing. … Read more
Mondays post established why AI cannot do architecture – and why that gap is structural, not temporary. The training data problem means LLMs pattern-match against a corpus of mostly bad architecture. That will not change as models scale. What changes is the opportunity: if AI handles expression and design is the only bottleneck remaining, the … Read more
LLMs are extraordinary at writing code. They are genuinely bad at architecture. Most people treat this as a temporary limitation – a capability gap that will close as models improve. It won’t. And understanding why tells you everything about what software engineering actually is. Why LLMs Are Good at Code The answer is in the … Read more