New jobs of the AI era

AI evaluator and QA tester

New role

Checks how an assistant or agent answers before launch and after every change: builds test questions, hunts for errors, made-up answers and ways to trick the system. Without that kind of check, customers are the ones who report the problems.

  • 6 lessons
  • 5 tools
  • 4 resources
  • Checked: October 2026

Where this job sits on the map

In the same group: 14 of 100 professions.

What changes

  1. You can't check a model's answers once and be done: when the model or its instructions change, the whole set of examples is rerun.

  2. Attack testing is now part of the job: attempts to make the assistant break its rules or reveal data (red teaming).

  3. Part of the grading is done by another model, but the grading rules and the borderline cases stay with a person.

AI drafts, the person decides

How the work splits here: AI prepares a draft, the person checks it and makes the call.

AI makes the draft

What AI does

  • Comes up with many test questions, including trick ones
  • Grades answers against set criteria
  • Compares two versions of an assistant on the same set of questions
  • Groups errors by type and writes a summary
You check itRead it, check the facts, fix it. Without this check the draft goes nowhere.
You decide and stay responsible

What stays with the person

  • Deciding what counts as a right answer in this field
  • Test cases drawn from your customers' real situations
  • The verdict: "ready to launch" or "too early"
  • Describing the risks in plain language for management

What to learn first

6 lessons from the course, in order. Start with the first one.

  1. How an LLM works inside, explained without mathStarting from zeroHow a language model works inside: tokens, context, temperature and hallucinations, explained without math.Start here
  2. How to write a good promptUserHow to give AI a task: the five parts of a good prompt, Plan Mode, and how to refine an answer instead of starting over.
  3. AI ethics and safety: hallucinations, attacks, biasUserHallucinations, prompt injection, bias, privacy and copyright: how not to trust AI blindly.
  4. MLOps for indie builders: monitoring, drift and retraining without a DevOps teamEngineerMLOps without a DevOps team: call tracing, prompt regression tests, cost control and prompt versioning.
  5. Evals: skills that improve themselvesEngineerEvals for skills: tests, pass rate, checking that the skill triggers and a data-driven improvement loop.
  6. Prompt injection defense, the top security threat of 2026EngineerPrompt injection: six attack types, eight layers of defense, red team tests and an incident response plan.

Which tools to use

  • An AI assistant for long documents, analysis and code, with Claude Code and Cowork on paid plans.

    Freemium
  • OpenAI's mainstream AI assistant: chat, voice, images, the Work agent and Codex.

    Freemium
  • Google's assistant, built into Gmail, Docs and Sheets, with Deep Research, Gemini Live and Canvas.

    Freemium
  • Google's free studio for Gemini: Build mode creates an app from a description or sketch.

    Freemium
  • Gemini in Google Sheets: tables, formulas and data analysis from a description.

    Paid

Ready-to-use materials

  • Assess the risk, spot the signs of a made-up answer and run a 5-minute check before you act on what AI says.

    Free
  • Go through an AI answer claim by claim: what's right, what's doubtful, where it's wrong and what to check at the source.

    Free

How to earn with AI

We don't promise income: results depend on your niche, your market and your work.

  • Job

    If you're a tester or work in customer support, take on checking your company's AI assistant: question sets, bug reports, repeat runs.

  • Service

    Testing a chatbot or assistant before launch: a question set, a report on errors and risks, and a recheck after the fixes.

  • Product

    A ready-made set of test questions and criteria for assistants in one industry, for example online stores.

Similar professions

Checked: October 2026