◆ Apache Airflow

Structure an Airflow project

This is real work, not a feature someone invented — it comes from real job ads and real questions people asked. Below are four ready AI prompts: get it done, make it easy for the next person to say yes to, work out the right move when you are stuck, and stop it coming back.

4prompts
See the prompt↓All Apache Airflow tasks

The same task, four prompts

today's deadline · the next reviewer · the stuck moment · the pattern
AExecute — do the immediate taskSet up a new project for the fraud detection team within our data pipeline orchestration…+
Set up a new project for the fraud detection team within our data pipeline orchestration system, ensuring all necessary directories and initial configuration files are in place so they can start defining their DAGs by end of day.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
BImprove — make it easier to acceptBefore the fraud team starts building out their directed acyclic graphs (DAGs), structure their…+
Before the fraud team starts building out their directed acyclic graphs (DAGs), structure their data pipeline project with a clear separation for DAGs, plugins, and custom operators. Include a robust README that details how to add new components and manage dependencies, making it easy for new team members to onboard and contribute without breaking existing workflows.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CDecide — diagnose the stuck momentI've just set up the new data pipeline project for the fraud detection team, but I'm unsure if…+
I just finished setting up the new Airflow project for the fraud team, but I'm worried about future maintenance.
I've just set up the new data pipeline project for the fraud detection team, but I'm unsure if the directory structure I've chosen will scale as they add more complex DAGs and custom hooks. I'm afraid of creating a tangled mess that will be impossible for new engineers to navigate. What's the best way to organize this project for long-term maintainability and easy onboarding?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternI've noticed that our data pipeline projects often start clean but quickly become difficult to…+
Our Airflow projects frequently become unmanageable as they grow.
I've noticed that our data pipeline projects often start clean but quickly become difficult to manage, with DAGs and custom code scattered everywhere. This makes debugging a nightmare and slows down new feature development. What habit should I change in how I initially structure projects to prevent this sprawl and ensure long-term clarity and efficiency?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?

Questions people actually ask

honest answers, no sign-up

Every task here was seen in the real world. Someone doing the job named it, a real job ad asked for it, or a lot of people asked about it online.

If nothing real showed a task, it is not on the page. That is the whole rule.

They are the same job approached four ways, because what you need depends on where you are.

Get it done today. Make it easy for the next person to say yes to. Work out the right move when you are stuck. Learn the pattern so the job stops coming back.

For most of these jobs it can carry the heavy thinking - draft it, sort it, check it, rehearse it with you.

It cannot sit in your chair, take the blame when a number is wrong, or notice what nobody wrote down. Let it do the first 80%. Keep the last 20% that is truly yours.

No. Copy any prompt and paste it into the AI you already use. No account, no score, no wall in the way.

Any of them. The prompts describe the work rather than naming a product, so they are not tied to one assistant.

That is also why they keep working when you switch.

Change it freely. Every prompt is a starting line, not a rule.

Put in your real numbers, your real names and your real deadline. The more you make it yours, the better the answer comes back.

The tasks come from real job ads, published job data and the questions people ask in public forums.

The steps come from Apache Airflow's own documentation, with practitioner sources for the traps the manual does not mention.

Push once. Ask it to sharpen the weakest part and to say what it assumed.

Most wrong answers come from a missing detail rather than a bad prompt - tell it the thing it could not know.