The AI Evaluation Field Test
A four-phase SeedStacking exercise to turn one AI tool you already use into proof you can trust. Stop testing AI on the easy stuff. Test it on your real work.
SeedStacking Resource
Why this exists
A model can ace a benchmark and still fumble your Tuesday afternoon. The companies building AI now simulate real deployment before they trust a model. You can build the small, daily version of that habit for yourself. It is called evaluation literacy, and it is the difference between trusting a tool and verifying one. Work the four phases below on one tool. Budget about 90 minutes total, or do one phase a day for four days.
Throw it one hard, real question
Pick one AI tool you lean on. Do not give it a demo question. Give it a genuinely messy, specific task from your actual week, the kind with a right answer you can check. Watch what comes back. That is your baseline. You just ran your first field test.
Run the three questions
Use the interactive field test below to score the same tool against the three questions that build evaluation literacy. Be honest. The goal is not to pass the tool, it is to know it.
Field Test: Three Questions
Build your one-tool evaluation rubric
Turn your answers into a reusable rule. Write three lines you will apply to this tool from now on: where you trust it, where you double-check it, and where you will not use it at all. That rubric is yours. It is sharper than any vendor spec sheet because it is built from your real work.
Share your field test, sharpen someone else’s
Post your field test summary in the community and add the one thing that surprised you. Then read one other member’s test and ask them a question about their verdict. Teaching your evaluation out loud is how the skill takes root, in you and in the people around you.
Run this with people who get it
The Harvest Kernel community is where educators and professionals share their field tests and build evaluation literacy together, one small win at a time. It is free.