◆ Apache Airflow

Access execution date as a variable

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 taskIn the daily inventory report DAG, get the execution date for today's run and use it to query…+
In the daily inventory report DAG, get the execution date for today's run and use it to query the database for all records processed on that specific date. The query needs to filter by the exact run date.
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 weekly financial reconciliation DAG runs, make sure the execution date variable is…+
Before the weekly financial reconciliation DAG runs, make sure the execution date variable is used consistently across all tasks. If a task needs to query data from the previous day's run, ensure it correctly calculates and uses 'yesterday's' date based on the current execution date. I need confidence that the date logic is solid for historical data pulls.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CDecide — diagnose the stuck momentThe monthly data archival DAG just ran on November 1st, but it archived data for November…+
The monthly data archival DAG ran on the first of the month, but it archived data for the current month instead of the previous month.
The monthly data archival DAG just ran on November 1st, but it archived data for November instead of October. I'm afraid we've moved live data into cold storage prematurely, impacting ongoing reports. I can't tell if the execution date variable was misinterpreted, or if the date calculation logic is flawed for month-start runs. What's the likely diagnosis for archiving the wrong month's data, and what's the best next move to correct this without losing data?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternI constantly lose time and introduce bugs because I struggle with correctly calculating…+
I frequently make mistakes when calculating relative dates (yesterday, last month) based on the execution date.
I constantly lose time and introduce bugs because I struggle with correctly calculating relative dates – like yesterday's or last month's data – based on the DAG's execution date. What habit should I change in how I approach date variable manipulation to ensure I consistently use the correct dates for data filtering and processing, avoiding off-by-one errors or pulling the wrong period's data?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?

Questions people actually ask

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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.