How to Evaluate a New AI Tool in Thirty Minutes (Before It Eats a Weekend)
Most tool evaluations sprawl into weeks of half-configuration. This thirty-minute protocol, one real task, two failure probes, one integration check, kills bad candidates fast.
The problem with evaluating AI tools is not that it is hard, it is that it is unbounded. A trial can eat a weekend in configuration, a week in comparison, and a quarter in half-adopted limbo. I have compressed my evaluation into thirty minutes with a fixed protocol, and its brutality is the feature: most tools should fail in ten, and the ones that survive deserve your time.
Minutes one to five: write the job description before touching the product. One sentence for the task it must do, one for how it must connect to what already exists, one for the constraint that would make you quit, pricing, privacy, output format. This is the checklist the demo cannot negotiate with, and writing it first prevents the evaluation from drifting into admiration. You are not shopping for impressive; you are hiring for a vacancy.
Minutes six to fifteen: one real task, end to end. Not the sample file in the onboarding flow, the actual thing from your actual desk this week, with its ugly inputs and its real output requirements. The end-to-end rule is where evaluations live or die, because tools excel at demos and stumble at edges, and the edges, the export format, the missing integration, the way it handles your actual volume, are precisely what the demo was engineered to skip. If the tool cannot finish the real task in this window, that is a verdict, not a warm-up.
Minutes sixteen to twenty-five: two failure probes. First, the ugly input: the worst-case version of the material the tool will actually receive, the noisy audio, the contradictory brief, the corrupted file, because you need to know whether it fails loudly or fails confidently. Second, the load test: your real volume, not a sample, because per-request costs and rate limits only reveal themselves at scale, and a tool priced fine at ten units can be absurd at four hundred. Note exactly how it fails; a tool that tells you what went wrong is worth more than a marginally better one that shrugs.
Minutes twenty-six to thirty: the decision, with three questions. Did it complete the real task; did its failures communicate; and, the question people skip, what would switching cost, because a marginally better tool inside an established stack is usually a loss. Then write one line, hire, reject, or revisit-with-conditions, and honor it. The protocol's value compounds over time, because the written verdicts become a record of what you actually valued, and the pattern in your own hires, the integrations you always need, the failure modes you never forgive, is the most useful product requirement document you will ever write. Thirty minutes, most candidates dead, your weekends returned.