Why is AI execution still so unreliable?

AI models have become incredibly good at reasoning, generating code, and understanding intent — but execution is still the weak point.

Most agents can think through tasks, yet fail when interacting with real systems: APIs, permissions, environments, workflows, memory, authentication, browser state, infrastructure, and unpredictable edge cases.

In many ways, current software ecosystems were designed for humans, not autonomous agents.

Curious how others see this:

• Where do AI agents fail most in your workflow today?
• What’s the hardest part of reliable execution?
• What infrastructure or tooling do you think is still missing?
• Would you trust an autonomous agent in production right now?

Would love to hear real experiences, failures, and opinions from builders here.