I build AI agents for other companies for a living. The pattern I see most often isn't "the model can't do it." It's "the demo worked, we shipped it, and now it fails one out of every three times and nobody can say why."
That gap between demo and production is mostly arithmetic, and once you internalize the math it changes how you build.
The math nobody puts on the slide
Say each step in your agent is 95% reliable. Sounds great. Now chain ten steps together, which is a modest agent by 2026 standards:
0.95 ^ 10 ≈ 0.60
