Ongoing debates about where large language models fall short — in rigorous reasoning, precise maths or verifiable facts — are not a reason to avoid AI. They're a reason to be precise about where it belongs. A model that drafts, summarises or suggests is powerful; one trusted to be the final word on something exact is a risk.
We map each AI feature to what models are genuinely good at, and add verification, retrieval or human review where correctness is non-negotiable. The goal isn't to hide the limits but to design with them in mind — so the product is confident where it can be and careful where it should be.