Traditional software is built on predictability, where the same input produces the same output.
This predictability permits testing, debugging, and clear guarantees. AI systems, particularly those powered by LLMs, break this model. Their outputs are inherently variable, shaped by probabilities rather than fixed logic. The result is an “oil and water” moment, where two fundamentally different behaviors must operate within a single architecture.