A convincing demo shows that an AI tool can succeed on one task. Before relying on it, you need to know how it behaves on ordinary work, awkward inputs and cases where it should ask for help.
You can learn a lot without building a formal benchmark. Start with a small set of representative tasks, define what counts as success and keep the original inputs so you can repeat the comparison later.
Choose tasks you can judge
Use examples from the work the tool would actually receive. For a document assistant, include a short clean document, a messy scan and a question that needs information from more than one section. For a coding assistant, use a contained change with a clear expected behavior.
Avoid making every task easy to inspect only because you already know the answer. Include a realistic case where checking the output takes effort. That review burden is part of the product’s usefulness.
Create a separate set of examples for tuning prompts and for judging the result. If you keep adjusting instructions until one particular task works, you have learned less about the next unseen task.
Write the success condition first
“Looks good” is difficult to reproduce. A better condition describes the required result and the unacceptable errors.
A summary might need to preserve three key figures, identify the source document and avoid adding unsupported claims. A spreadsheet task might need to change only the requested rows and preserve formulas elsewhere. An action-taking assistant might need to request approval before sending anything.
Anthropic’s engineering discussion of agent evaluations distinguishes the task, the observed run and the outcome being graded. That separation is useful even in a simple spreadsheet: record what you asked, what happened and whether the final state was correct.
Include a case with no valid answer
Give a research assistant a question that the supplied documents do not answer. Give a scheduling workflow conflicting constraints. Give a parser an incomplete record.
A useful tool should make uncertainty visible or ask for missing information. If it quietly invents a value, the problem is not just the incorrect answer. The workflow also needs a way to stop that answer reaching the next system.
For tools that can change data, test in a disposable environment using harmless examples. Inspect the state after failure as well as after success. A partly completed operation can leave more work than a clean rejection.
Repeat the important cases
Models and connected services can behave differently across runs. A tool may also depend on changing search results, rate limits or external availability.
Repeat the cases whose failure would matter most. Track whether the same error recurs, whether a retry fixes it and whether the tool explains what went wrong. Do not average a severe permission mistake into an otherwise high success score.
Keep the exact model and tool settings alongside your results where available. A later product update can improve one task while making another worse.
Count your own intervention
Record how often you rewrite the prompt, correct a fact, supply a missing file or finish the operation yourself. Include the time spent checking an apparently successful answer.
Our workflow cost guide explains why a cheap request can still produce an expensive result. For many routine jobs, the largest difference between tools is the amount of supervision they need.
Separate a failure of the tool from a failure of the setup. If the task requires a file you never provided, fix the test. If the tool claims it read a file it could not access, keep that as a product failure.
Decide the scope of the first rollout
You do not need a single verdict that the tool is either good or bad. It may be reliable for short summaries but unsuitable for sending customer messages without review.
Write down the tasks it may perform, the checks still required and the situations that should return to a person. Reuse the test set after changing the prompt, model or integrations. That turns the initial trial into a practical maintenance tool.
