Deep dive · module 70 of 100
From experiment to routine
Turn a working AI application into a fixed habit in your team.
After this lesson
You can describe the steps to turn an experiment into a routine.
In view · An improvement loop
What works becomes a routine
Save prompt, steps, conditions, and checkpoints.
Ask colleagues to test the same approach on a small task.
Incorporate the proven approach into the team procedure and continue to adjust.
Part 1 of 3 · Document
Your preference for less movement is on. Choose each part yourself.
Document what works
Write down the prompt, the steps, and the checkpoints.
Share with the team
Let others try the approach and provide feedback.
Make it the standard
Add it to the team agreements or the prompt library.
New practice example
From explanation to a usable result.
Moving from test to routine requires repeatability, an owner and a visible stop when deviations occur.
Fictional practice situationA fictitious team has created one good AI summary. Now it wants to use the same approach weekly for notes with different writing styles.
View a possible solution
This is how it can be done
Test five different notes, including one with contradictory agreements. Save prompt, checklist and error cases. Agree on who maintains the procedure and when to revert to manual work.
Why this works
A successful demonstration is not yet a reliable routine. Variation in input makes other errors visible.
Make it slightly more difficult
Write a short work instruction for a new colleague who has not seen the test. Can they find the same source and controls?
Extra practice, at your own pace. You do not need to submit anything. This does not count towards an automatic assessment.
Your workplace · learning by doing
Make something. See what changes.
Checking the AI connection… You can already view the written example.
Present your assignment to Ende.
Read the answer, change one thing, and compare.
Previously held
New version
You remain in control
What do you want to improve in your next attempt?
On this device only. AI answers remain only in this page memory. This is self-review, not a grade.
Why this approach works
A successful demonstration is not yet a reliable routine. Variation in input makes other errors visible.
A step further
Write a short work instruction for a new colleague who has not seen the test. Can they find the same source and controls?
Try & discover · no obligation
Put the steps in a workable order
Move the steps with the arrows. Check whether each step has its necessary input and control.
What does a step depend on?
- Determine the goal must precede Create a concept
- Collect permitted source information must precede Create a concept
- Create a concept must precede Check the concept
- Check the concept must precede Use the result
Move a step and then check the sequence. The arrows also work with your keyboard.
This model checks dependencies, not duration, capacity, or actual execution. With multiple agents, the human decision remains a separate step.
This trial works locally with fictitious data and does not count towards your lesson completion. It starts anew with a new lesson or reload.
A prompt to get you started
Describe in 4 steps how to convert a working AI approach from an experiment to a team routine.
Apply it
A trial with meeting notes works for the creator. A colleague cannot find the input or control criteria anywhere.
Which approach best fits this situation?
- Immediately make it a mandatory routine for everyone.
- Document input, prompt, control and owner before sharing the workflow.
- Only share a polished end result as an instruction.
With JavaScript, you can check your approach and receive immediate feedback.
Test your insight
What is needed to turn an experiment into a routine?
- Only save the prompt.
- Document, share, and include in the team agreements.
- Nothing.
Extra practice
Choose one application that works well and note how you would share it with colleagues.
Document the action list prompt, put it in the shared library, and briefly explain it in the team meeting.
