What makes a good AI training task, with examples
Most AI training tasks aren't worth training on. Seven things that separate the useful ones, with weak and strong examples from our expert reviews.
AI labs pay experts to write tasks that teach and test their models. Most tasks that get written are not worth training on. Here’s what separates the useful ones, from the reviews our experts do every week.
1. It has one defensible answer
A good task has an answer a second expert would independently agree with. If two specialists would argue, the task teaches the model to guess.
- Weak: “What’s the best treatment for high blood pressure?” (depends on the patient)
- Strong: a short patient case with age, readings and existing conditions, asking which first-line medicine guidelines recommend and why
2. It can’t be looked up
If the answer is one search away, the task measures retrieval, not reasoning. Good tasks combine facts in a way no single page does.
- Weak: “What year was the Indian Contract Act passed?”
- Strong: a two-paragraph business scenario, asking whether a valid contract was formed and which section decides it
3. It’s hard for today’s models, not just for people
We test every draft against several current models. If they all get it right, it’s well written but won’t move anyone’s model forward. The useful tasks sit just beyond what models can do now.
4. The wrong options are plausible
For multiple-choice tasks, each wrong answer should be one a smart person could reach by a common mistake: a sign error, a misread condition, an outdated rule. Obviously wrong options let models win by elimination.
5. It explains the reasoning, step by step
The answer alone tells a model what; the explanation teaches it how. Our writers include the steps an expert would take, including where people usually go wrong.
6. It’s written by someone who does the work
A practising lawyer knows which detail changes the outcome of a case. A physician knows which symptom matters. That judgment is the whole value of an expert-written task, and it’s why we vet writers before they write anything.
7. It’s original
No copying from textbooks, past exams or the internet, and no AI-generated drafts. Recycled tasks may already be in training data, which makes them useless for testing.
How we check
Every task goes through a second-expert review, a search test and a model test before it’s accepted. Writers get feedback on every rejected task, and their acceptance rate decides who writes more.
If your team needs expert-written tasks in science, medicine, law, finance or Indian languages, request a sample.