An AI agent can produce a convincing answer and still fail the job you gave it. For a business owner, the useful question is whether it completed the intended task, stayed within its authority and left enough evidence for someone to check.
That evaluation problem is the subject of an October 22–23, 2026 workshop announced by Carnegie Mellon’s AIMSEC and Microsoft Research. The organizers’ published agenda covers measurement frameworks, tools and challenges in specific applications. Their pages describe planned public synthesis reports; they do not establish that a new standard has been adopted. This article uses that agenda as a starting point for practical analysis, not as evidence of completed workshop findings.
Measure the job you actually need done
Imagine an assistant preparing a weekly supplier update. A readable summary is only one part of success. Did it use the right reporting period? Did it distinguish an overdue shipment from a revised delivery estimate? Did it attach the correct source? Did it send anything before a manager approved it?
These are different checks. Combining them into a single “looks good” decision makes it difficult to spot the failure that matters. Before testing an agent, write down the expected result, the allowed actions and the conditions that require it to stop.
For this example, a sensible first trial might permit the agent to read approved delivery records and prepare a draft. Sending the message could remain a separate action. That boundary lets the team assess the work while keeping responsibility clear.
A source link is the beginning of a check
NIST’s early research into evaluation probes offers a useful distinction. Its research testbed checks claims against a curated document collection and records structured verdicts. The demonstration examines whether a claim is supported, whether it reflects the source’s fuller message and whether the evidence is strong enough for the conclusion. This is research described on a page updated in May 2026, not a guarantee that any commercial agent can verify itself.
Apply those distinctions to a supplier report. A document might say a shipment is delayed, while the agent says the supplier routinely misses deadlines. The link can be real and relevant while the broader claim remains unsupported. A second check should ask what the source actually establishes.
Then ask what it leaves out. Perhaps the same record says the customer requested a later dispatch. A summary that omits that detail could send a manager toward the wrong decision.
Build a small, revealing trial
The following is an editorial recommendation for teams planning an initial trial. Assemble a small set of representative jobs whose correct outcomes a knowledgeable person can inspect. Include straightforward work, incomplete inputs and a case where the safest result is a request for clarification.
For each job, record the input, expected result, actual result and reviewer’s decision. Keep the original documents available. If two reviewers disagree, examine the rule before adjusting the agent. An unclear acceptance rule can make a system appear inconsistent even when people have never agreed on what success means.
Do not measure speed alone. Record correction time and the importance of errors. A draft delivered quickly may offer little benefit if a specialist must reconstruct every source. Conversely, a slower draft may be useful if it saves a meaningful amount of careful checking.
Make the handoff part of the result
A completed draft should say what it used, what remains uncertain and what requires a decision. In the supplier example, the agent might flag a missing arrival date and identify the record it could not reconcile. That is a more useful handoff than silently filling the gap.
Assign a named person to exceptions. “Human review” is too vague if nobody knows who receives a disputed result or when it must be resolved. The trial should test that route as well as the agent’s output.
Keep permissions proportionate to the tested job. Expanding from preparing a report to changing supplier records creates a different workflow, with different consequences and checks. Reassess it before widening access.
What to watch next
The Microsoft Research event page identifies intended public outputs on unresolved evaluation problems and emerging practices. Those materials, when available and reviewed, may help teams sharpen their tests. An announced discussion is not a certification.
For now, a business can begin with a concrete job, a written definition of success, a visible review trail and an owner for exceptions. That gives a team something more useful than confidence in a polished demonstration: a way to decide whether delegation is working.
Cover: original conceptual illustration, not documentary evidence.