Agent benchmark development
Build a benchmark that measures the decision owner's intended use
Available public benchmarks do not resemble the agent's actual workflow. The decision is how to build a benchmark that measures the decision owner's intended use. The work begins with your actual workflow and looks for the evidence that separates intended behaviour from a consequential exception. It is particularly relevant to evaluation researchers and product owners. A useful outcome is an explicit account of what was examined, what remains uncertain, and which decision the evidence can support.
The release evidence relationship
- Task taxonomy
Establish the basis for task taxonomy.
- Scoring contract
Include tool action and terminal-state requirements.
- Benchmark specification
Retain the scoped finding and its unresolved dependencies.
Decision
Frame the decision around task taxonomy
Questions and the evidence they need
- Task taxonomy
- Inspect task taxonomy for the relevant constraint or observation.
- Scoring contract
- Inspect representative cases for the relevant constraint or observation.
- Held-out cases
- Inspect scoring rules for the relevant constraint or observation.
The decision is how to build a benchmark that measures the decision owner’s intended use. This is relevant to evaluation researchers and product owners when available public benchmarks do not resemble the agent’s actual workflow. Name the affected workflow, the consequence of a wrong decision, and the owner who can act on the result. The initial discussion should establish which evidence is already available and which uncertainty is material enough to investigate.
The specific failure hypothesis is that a benchmark rewards fluent output while ignoring required tool actions and final system state. It remains a hypothesis until examined in the deployment. Existing internal tests or operating records may already resolve it; identify the uncovered question before commissioning additional work.
Mechanism
Benchmark design should follow the intended decision
Relationships within release evidence
- Task taxonomy
- Represent the jobs the organisation actually needs.
- Scoring contract
- Include tool action and terminal-state requirements.
- Held-out cases
- Control exposure and revisions as teams optimise.
What this specialty examines
Benchmark development begins with construct definition: what ability or behaviour is the benchmark meant to measure? Specify task representation, expected outcomes, scoring and prohibited shortcuts. Cases should reflect the decision without pretending to represent all possible operating conditions.
The review should design case strata, scoring rubrics, held-out examples and comparison rules before evaluating candidates. Identify the normal route, relevant exceptions and the authoritative record of the outcome. Inspect the relevant business-system record, enforcement event or process evidence alongside any reported status. Keep incomplete cases visible, with an explanation of what their absence prevents the owner from concluding.
The tradeoff to make explicit
For this decision, stable benchmark cases support comparison while evolving business tasks require controlled revisions. Compare the available design or operating choices against the same intended outcome. If one option removes a required control or changes the task boundary, describe that difference before treating its apparent simplicity, speed or lower effort as an improvement. The decision should expose the tradeoff instead of burying it in an aggregate score.
Preparation
Connect the working inputs to the boundary being examined
Evidence packet for task taxonomy
Illustrative working format
- Task taxonomy
- Identify provenance and the specific decision this material can inform.
- Representative cases
- Keep expected behaviour and the limits of the constructed example explicit.
- Scoring rules
- Separate required outcomes, consequential exceptions, and reviewer interpretation.
- Contamination controls
- Identify provenance and the specific decision this material can inform.
Start with task taxonomy, representative cases, scoring rules and contamination controls. Identify the owner, revision and operating context of each source. Sanitised examples may support initial design, but differences from actual conditions should remain explicit. Where direct access is unsuitable, a customer-controlled evidence or execution route may be considered, with agreed handling and retention.
The scope also needs the release owner, agreed expectations for a representative task case, and the authority to inspect the relevant boundary. Specify what evidence would distinguish the failure in which a benchmark rewards fluent output while ignoring required tool actions and final system state from acceptable behaviour. If stakeholders disagree about intended behaviour, resolve the interpretation before classifying the observed difference as a defect.
How the work proceeds
Carry task taxonomy through to an accountable finding
From the scoped material to a decision record
- Task taxonomy
Separate hard constraints from graded preferences.
- Scoring contract
Apply the scoped check to held-out cases.
- Benchmark specification
Record the evidence, open dependencies, and the owner’s next decision.
Prepare the evaluation cases
Work with evaluation researchers and product owners to assemble task taxonomy, representative cases, scoring rules and contamination controls. Select a normal task, a consequential exception and a case with insufficient information. Identify the relevant requirement and expected result for each, then mark which outcomes need human adjudication. The preparation output is a case packet that separates blocking behaviour from graded quality preferences before any comparison is run.
Run and review the comparisons
Separate development examples from held-out comparison material where practical. Record exposure and revisions so repeated optimisation does not silently turn evaluation cases into training targets. Scoring disagreement and ambiguous cases deserve review rather than automatic deletion from the dataset.
Choose the release or evaluation change
Use the reviewed cases to produce a benchmark specification with dataset governance, scoring rationale and reporting conventions. Distinguish a product defect from a missing test, an ambiguous requirement or an unreliable measuring method. For each, name the proposed correction and the case that would check it. The release owner can then decide whether to change the implementation, improve coverage or restrict the intended use while a specific gap remains.
Indicative artefact
Make the benchmark specification usable by its owner
Benchmark specification
Illustrative working format
- Benchmark specification
- Identify the assessed workflow, revision, and decision boundary.
- Dataset governance
- Link supporting and contrary observations to inspectable evidence.
- Scoring rationale
- Define the required observation and who resolves disagreement about acceptance.
A useful decision artefact is a benchmark specification with dataset governance, scoring rationale and reporting conventions. Supporting material may include selected cases, configuration or process records, evidence references, a disagreement log and prioritised actions. Retain the case selection rationale and material disagreements alongside the result; otherwise the result may be mistaken for complete coverage.
Illustrative scenario
Examine held-out cases through a constructed exception
A constructed case and its decision paths
Illustrative scenario
- Task taxonomy
A procurement agent is ranked on answers despite needing approval reconciliation.
- Scoring contract
Add reconciliation, approval, and final-state criteria to the task contract.
- Held-out cases
Reject a broad capability conclusion from answer-only evidence.
Consider a fictional situation: a procurement assistant is compared using generic question answering despite needing to reconcile line items and approvals. The scenario is illustrative, with no client engagement, executed test or measured improvement implied.
For procurement, a benchmark should include line-item reconciliation, missing evidence and approval limits. A candidate that answers general questions well may still fail those tasks. The result should support a workflow-specific comparison, not a universal ranking of agent quality.
Scope and next action
Keep the conclusion within selected task cases
Confirm fit before the next commitment
- Task taxonomy
- This review is limited to selected task cases.
- Task taxonomy evidence
- The relevant owner must confirm access and the intended operating conditions.
- Benchmark specification
- The customer retains the release decision.
A result applies to the recorded configuration and selected cases. It does not establish universal agent competence or authorise release. Any engagement depends on an agreed scope, qualified team, authorised access and confirmed availability. Bring the affected workflow, its current configuration or process, the triggering change and the evidence already available. The immediate scope question is prompted by the situation in which available public benchmarks do not resemble the agent’s actual workflow; confirm which missing observation would change the owner’s next action.
Ways to engage
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Related insights and resources
Engineer the harness, not just the prompt
Define the contracts around an agent's decisions: what state it trusts, which actions can execute, how interrupted work resumes, and what evidence an operator needs to recover safely.
What would justify releasing this agent?
Replace a single pass rate with a reviewable chain of requirements, cases, observations and judgements. Distinguish task quality, control failures and uncertainty before increasing an agent's exposure.
The evidence behind the go-live decision
A working paper for leaders who need to explain why an agent workflow is ready for its next release. Includes a proposed evidence-pack structure, decision table and review agenda.