A proposito di Sheldon K Salmon
Reliable AI Architecture
Most teams using AI in real decisions don't know which outputs to trust. They don't know where the hallucinations are hiding. They don't know what their actual exposure looks like until something fails.
I make that visible before it fails.
I evaluate AI outputs used in real business decisions and produce a structured written report — plain language, no machinery, just exactly where you can rely on the output and exactly where a human needs to be in the loop before action proceeds.
This is not a philosophical conversation about AI safety. It is an engineering report about your specific outputs and your specific risk.
I've spent several years developing the evaluation method. It works because it was built to find the edges — not to confirm that everything is fine.
Currently offering 3 free AI Reliability Snapshots to founding participants.
If your team is making decisions from AI outputs and you want clarity on what you are actually holding:
aionsystems.carrd.co
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