Use AI without outsourcing judgment
Create one reusable, privacy-aware AI workflow that improves real work and includes verification.
Choose tasks where AI is useful and risk is manageable.
Write instructions with context, constraints, and a quality bar.
Verify claims and protect sensitive information.
Develop AI literacy as an accountable work process, not prompt memorization. The project makes task choice, privacy, verification, and human responsibility inspectable.
125 learn · 55 build · 25 review
Do the work in this order
- 01
Choose a low-risk, repeatable task with a clear human owner.
- 02
Define allowed inputs, protected data, constraints, and the quality standard before prompting.
- 03
Run the workflow on a fresh example and log every source or calculation that requires verification.
- 04
Insert one deliberately flawed output and confirm the stated control catches it.
The learner catches the seeded failure, verifies material claims outside the model, and can state who owns the final decision.
Complete the lesson sequence
Pass each lesson check and mark the work complete in the Life Starter player. Return here and the verified progress bar updates automatically.
- 1aiFind the right work for AIStart
- 2aiWrite strong instructionsStart
- 3aiDecompose complex workStart
- 4aiGround and verify outputsStart
- 5aiProtect data and rightsStart
- 6aiBuild a workflow libraryStart
Try the workflow on a new example and deliberately introduce one bad output. The stated checks should catch it.
Verified AI work recipe
A reusable workflow with inputs, instructions, checkpoints, sources, and a human approval step.
Describe the task, acceptable inputs, protected data, prompt or instructions, decomposition steps, verification method, failure conditions, and final human decision.
Task and quality bar are specific
Sensitive data is excluded
Important claims are independently checked
A person owns the final decision