Heidelberg AI Curriculum

4books in this track

L02 · Power user

Who is affectedYour team sees a bad document or a wrong figure

Frame a Problem Your Team Agrees On

Turn a vague request like "we need an AI tool for X" into a one-page problem statement your team signs off: who has the problem, what's hard, what a useful result looks like and how you'll know. Includes a short stakeholder conversation and an assistant that challenges your framing.

Outcome: A one-page problem statement for a real request in your team, with who, what's hard, a useful result, a test and a list of what's out of scope, which passes when two colleagues have read it and signed it with no open objection.

Power user15 minLast edited: Sep 23, 2026

L03 · Builder

Who is affectedColleagues depend on something you built

T17-L03

Explore What Already Exists Before You Build

Before you build something colleagues will depend on, scan how the job is done today, what products, papers and examples exist, and what you can reuse. Use an AI research mode for the scan, check its claims against real sources, run one small experiment and rewrite the problem.

Outcome: A two-page exploration note with how it's done today, what exists, a checked source for every claim, one experiment and a revised problem statement, which passes when a colleague can open every source and find the claim it supports, and the two people who signed the original statement accept the revision.

Builder18 minLast edited: Sep 23, 2026

L04 · Integrator

Who is affectedCompany or lab systems and real data are in the loop

T17-L04

Run a Pilot with Real Users and Real Data

Test a solution on real work before your lab or company depends on it. Set the pilot's scope, success criteria and data permissions before day one, keep a way back, measure what matters, and end with a written go, change or stop decision that follows rules you set in advance.

Outcome: A pilot plan and a results note for a real pilot, which pass when the criteria and decision rule are dated before the start, data permissions are confirmed in writing, every criterion (including harm) has a measured result, and the go, change or stop decision follows the rule and is signed by the person who decides.

Integrator18 minLast edited: Sep 23, 2026

L05 · Operator

Who is affectedWork stops when it breaks, and it must survive you leaving

T17-L05

Decide Which Problems Deserve Building

Put every AI project your lab or company runs or wants on one sheet, as problems. Score each by value, effort, risk and who keeps it running after you leave, retire what no longer earns its upkeep, and keep a decision log a successor can follow without you.

Outcome: A ranked portfolio of every running and proposed item with four scores and a decision each, plus a decision log, which passes when every kept or built item has a named keeper and backup other than you, and a colleague who wasn't involved can answer three questions about past decisions from the log alone.

Operator17 minLast edited: Sep 23, 2026