The gap between an impressive agent demo and a dependable production system is wide — but it's now reasonably well understood. Reading across the first wave of real deployments, the same few factors separate the agents that stick from the ones quietly switched off.
Narrow beats general
The agents delivering real ROI do one job: triage this queue, reconcile these invoices, draft this report. Ambitious 'do-everything' agents fail in ways nobody can debug. Scope is a feature.
Design the failure path first
Every production agent needs an explicit answer to: what happens when it's unsure? The good ones escalate to a human with full context. Confidence thresholds, human-in-the-loop review, and audit logs aren't overhead — they're what makes deployment possible.
Evaluation is the real engineering
Teams that succeed build evaluation sets before they build the agent: real inputs, expected outputs, measured continuously. Without it you're guessing whether v2 is better than v1.
The economics are straightforward
An agent that reliably handles even a meaningful slice of a repetitive queue — correctly, with a clean escalation path — pays for itself quickly. The technology is ready; the differentiator is engineering discipline.
We help teams go from agent idea to production deployment, including the evaluation and guardrail infrastructure that makes it safe. Happy to talk through what that would look like for your use case.