◆ Apache Airflow

Create conditional tasks in Airflow

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

The same task, four prompts

today's deadline · the next reviewer · the stuck moment · the pattern
AExecute — do the immediate taskThe end-of-month financial close DAG needs to run. If it's a weekday, send the summary to the…+
The end-of-month financial close DAG needs to run. If it's a weekday, send the summary to the finance director. If it's a weekend, just archive the results without sending any emails.
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 acceptFor the daily customer data sync, if the 'new customers' count from yesterday is over 5,000,…+
For the daily customer data sync, if the 'new customers' count from yesterday is over 5,000, then trigger the 'welcome email campaign' task. Otherwise, just proceed with the standard data update without sending any emails.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CDecide — diagnose the stuck momentOur new marketing campaign is live, and we need to process data differently based on its…+
Our new marketing campaign launched, and now the daily data pipeline needs to adapt based on its performance.
Our new marketing campaign is live, and we need to process data differently based on its success. If the campaign's conversion rate exceeds 2% by noon, we need to immediately trigger a high-priority 'upsell offer generation' task. If it's below 1%, we need to trigger a 'campaign optimization report' instead. I'm not sure how to make this decision point reliable and automated within the existing daily pipeline.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternI'm constantly losing time manually checking the results of data processing tasks and then…+
I often find myself manually triggering different follow-up tasks based on the outcomes of earlier data processing.
I'm constantly losing time manually checking the results of data processing tasks and then deciding which subsequent tasks to run. This leads to delays and missed opportunities, especially for time-sensitive marketing campaigns. What habit can I change to automate these 'if-then' decisions within my data pipelines, so the right follow-up action is taken immediately based on specific data thresholds or outcomes?
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.