Eliminate table ambiguity to kill hallucinations

To a human analyst, an ambiguous column named “latency” or “revenue” can be deciphered with a bit of institutional context. But to an AI agent, it’s a hallucination trap. Without rigid guardrails, the agent is forced to guess. Sometimes it gets it right; sometimes it mistakes milliseconds for seconds, or gross revenue for net revenue.

To solve this, enforce strict, self-describing naming conventions across your entire schema. Use standardized prefixes (id_ for joins, is_ for booleans, amt_ for currency) and explicit unit suffixes (_ms, _usd, _gb). When a vague column is transformed into dur_latency_ms or amt_gross_revenue_usd, the data becomes entirely self-documenting.

The agent reads the name, instantly knows the data type and unit, and no longer has to guess.