Prove the forecast before you bet on it

The cardinal sin is shipping a forecast agent and trusting it because the dashboard is green and the number looks plausible. A plausible number is the most dangerous output a forecast can produce. You have to prove the forecast is honest the same way you prove any system, by checking it against reality, on the values, not the vibes.

Backtest against closed quarters. Before the agent's forecast drives a single decision, run it backwards over the last four closed quarters. Feed it the pipeline as it stood at the start of each quarter and compare its prediction to what actually closed. Measure the real error, deal by deal, not the headline accuracy. If it would have missed last Q3 by 30%, it will miss next quarter by 30%, and you are not allowed to ship one that does that with a fresh coat of AI on it.

Audit the inputs, not just the output. Forecast accuracy is a lagging indicator, by the time you know it was wrong, the quarter is over. So watch the leading indicators of hygiene that drive it: percentage of open deals with a fresh next step, percentage with activity in the last 14 days, duplicate rate, percentage of forecast value resting on verified-fresh data. When those degrade, the forecast is about to lie, and you fix it upstream. The gap is real, many revenue leaders say they trust their CRM while independent audits put accuracy far lower, and the only cure is measuring the inputs continuously rather than assuming them. Treat those hygiene metrics with the same seriousness as the funnel metrics that move revenue.

Make the agent show its work. Every forecast number the agent produces should be clickable down to the deals and the signals behind it. "Why is this deal at 70%?" must have an answer in observed activity, not a black-box score. A forecast you cannot interrogate is a forecast you cannot defend in a board meeting, and one you should not be running your hiring plan against.