Blog Details
Accuracy gets an agent approved for a pilot. It's not what keeps a team relying on it six months later.
Date
08.15.2026
Category
AI Agents
Automation
Workflow
6 min read
Author
Eassa Eisenberg
Content Writer
Every AI agent we’ve shipped has cleared a technical accuracy bar before going live — that part is table stakes. What actually determines whether an agent survives past its first quarter in production has almost nothing to do with its accuracy score, and almost everything to do with whether the people working alongside it trust it.
We’ve seen agents with excellent benchmark accuracy get quietly switched off within weeks, and agents with more modest accuracy become indispensable within days. The difference wasn’t the model. It was whether the team could predict what the agent would do — and whether it told them clearly when it wasn’t sure.
A support agent that resolves 95% of tickets correctly but occasionally closes a ticket it shouldn’t have, with no warning, will get uninstalled by a nervous team faster than one that resolves 85% correctly but flags its own uncertain cases every time.
Every agent we build surfaces a confidence score alongside its decision, and routes anything below a threshold — set jointly with the client, not by us alone — to a human. Teams stop watching over an agent’s shoulder once they’ve seen it correctly identify its own weak spots a few times in a row.
Agents that act invisibly get blamed for everything that goes wrong nearby, whether they caused it or not. We log every decision an agent makes, with the reasoning attached, so a manager can check any single action in seconds rather than taking it on faith.
We never hand an agent full authority on day one. It starts narrow, in shadow mode, then earns a wider mandate as its track record builds — the same way a new hire would.
Trust isn’t a feature you ship. It’s a track record the agent has to build in front of the people who have to live with its decisions.
On the factory floor specifically, this shows up as agents that flag ambiguous sensor readings instead of guessing, that explain their maintenance recommendations in plain language a technician can sanity-check, and that start with a single, narrow responsibility before earning a broader one.
None of this is exotic. It’s mostly just being honest about uncertainty, and resisting the temptation to hand an agent more authority than it’s earned yet — even when it’s technically capable of more.
08.15.2026 - 6 min read
Accuracy gets an agent built. Trust is what keeps it running six month later.
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