Claude has improved dramatically over the past year, and I use it daily, BUT ....

there is a business problem almost no one talks about enough:

Businesses are paying not only for useful output, but also for the AI’s mistakes, retries, ignored instructions, and admitted failures.

I recently got this response from Claude:

“That’s worse than a rookie mistake; that’s me violating CLAUDE.md rules #4, #5, and #7 … be honest / follow documented rules strictly / no assumptions.”

Think about that for a second.

The AI knew the rules.

The AI admitted it broke the rules.

And the user still paid for the bad output, the wasted tokens, and the lost time.

From a business perspective, that is not a small issue.

That is a real operational cost.

We spend too much time talking about benchmarks, speed, and model improvements, and not enough time talking about the hidden cost of failure:

retries,

corrections,

extra usage,

team delays,

and trust erosion.

If AI is becoming part of business infrastructure, then reliability and instruction-following should matter just as much as raw capability.

Why are customers expected to absorb the cost of the model’s mistakes?

That seems backwards to me.

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