AI agents betray trust with silent math errors and data blind spots
Monte Carlo’s post reveals that production AI agents rarely crash—instead they slip quietly, delivering confidently wrong numbers. Common patterns include doing arithmetic in prose, mistaking missing detail for zero activity, and silently substituting wrong metrics. These failures erode user trust, prompting a shift toward structured calculations and explicit data‑visibility checks.