AI coding tools have made writing code fast, but the real bottleneck in AI-assisted development is now operational: deploying AI-generated code safely and reliably in the cloud. Common failure points include missing retries, non-idempotent functions, broken rollbacks, and environment drift. LLMs lack context about live cloud state, permissions, and service dependencies, making deployment harder than with human-written code. The solution isn't smarter models but better-structured cloud environments with explicit state, guardrails, and safe primitives that AI agents can reliably interact with.
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