I am reposting here in Feature requests as it aligns better with product behavior improvements for enterprise users. Thank you.
I am reposting here in Feature requests as it aligns better with product behavior improvements for enterprise users. Thank you
This is feedback from a business (B2B) usage perspective.
In enterprise use, the most critical risk is not that an AI gives a wrong answer.
Errors are expected in any tool.
The real problem is what happens *after* the error.
When an AI:
- confidently states it can do something it actually cannot,
- allows the workflow to proceed based on that assumption,
- and only later reveals the limitation,
the result is not a simple mistake, but a broken process.
By that point, time, labor, and trust have already been lost.
Worse, when the error is pointed out, the current behavior often attempts to recover trust through:
- lengthy explanations,
- retroactive rationalization,
- or repeating the user’s own actions in verbose form.
In real B2B environments, this behavior is not interpreted as helpful.
It is interpreted as:
- lack of accountability,
- post-hoc justification,
- and loss of professional reliability.
In practice, the correct response would be very simple:
- acknowledge the mistake immediately,
- clearly apologize,
- confirm that the user’s work is correct,
- and stop.
No extra explanation.
No attempt to regain authority through verbosity.
The business impact of failing here is severe but largely invisible:
- companies quietly terminate trials after a single failed project,
- teams stop proposing the tool as an option internally,
- and the product simply stops appearing in future vendor selections.
This kind of loss does not show up in usage metrics, churn dashboards, or error logs.
But over time, it compounds and reduces future adoption opportunities.
From a B2B standpoint, the ability to:
- say “I was wrong” quickly,
- distinguish clearly between “possible” and “not possible,”
- and remain silent when no further contribution is needed,
is more important than being conversational, verbose, or explanatory.
This is not a request for higher model accuracy.
It is a request for more professional post-error behavior, aligned with real business communication norms..