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AI judge vs rule-based scoring.

An AI judge is another model that reads a conversation and decides whether it passed. Rule-based scoring checks the agent’s recorded actions against the business’s rules. Rules are exact and repeatable but can only check what is written down; AI judges can assess honesty and tone but vary between runs and have documented biases. Use rules for anything a rule can decide, and a judge only for the rest.

01Side by side

Compared onAI judgeRule-based scoring
DecidesWhether a conversation passed, by reading itWhether recorded actions broke a rule
RepeatableWithin a tolerance; answers varyExactly
Cost per conversationA model call, or severalEffectively nothing
Good atHonesty, tone, overall conductPrices, refunds, payments, data, budgets
Known weaknessesPosition, length and self-preference biasesCannot judge what is not written as a rule
Can be gamed by the agentIf the agent’s words can address the judgeNo: words do not change the record

02When each is the better choice

AI judge

  • Honesty: did the agent say anything untrue?
  • Tone and firmness, where policy is about manner.
  • Conversations the rules could not decide.

Rule-based scoring

  • Any rule with a number: windows, limits, floors, approved amounts, budgets.
  • Anything that must be compared across versions.
  • The headline score.

03Using both

Let rules decide first. Use a judge only where they cannot, on a sample large enough for a range, from a different vendor than the agent’s model, and never to turn a rule failure into a pass. Check the judge against people before trusting it.

Research supports the caution: Zheng et al. (2023) documented position, verbosity and self-enhancement biases in AI judges, and Panickssery et al. (2024) found that models can recognise their own text and tend to rate it higher.

04What Duelpoint does

Duelpoint scores rules first, from a referee that is plain code. An AI judge from a different vendor than your agent’s model is used only for honesty, tone and conduct, on a sample, can only lower a score or send a case to a person, and is checked against human labels before its findings lose their beta label. See how we score.

Questions

Can an agent talk an AI judge into a better score?

It can try. Safeguards include passing the agent’s words to the judge only as quoted data, and excluding any conversation that addresses the scorer directly.

See where your agent leaks money. Tested against your own rules, with the money at stake.

See the testsHow we score