◆ Apache Airflow

Define parallel tasks in a DAG

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 taskIn the 'daily_etl_pipeline', make sure the 'clean_customer_data' and 'clean_product_data' tasks…+
In the 'daily_etl_pipeline', make sure the 'clean_customer_data' and 'clean_product_data' tasks run in parallel, as they don't depend on each other, to speed up the overall pipeline.
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 'monthly_billing_cycle' pipeline, the 'generate_invoices' task and the…+
For the 'monthly_billing_cycle' pipeline, the 'generate_invoices' task and the 'send_payment_reminders' task can run at the same time after the 'calculate_customer_charges' task finishes. This will significantly cut down the time it takes to complete the billing run, getting invoices out to customers faster.
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'm trying to optimize the 'quarterly_reporting_pipeline' by running several data preparation…+
I'm trying to optimize the 'quarterly_reporting_pipeline' by running several data preparation steps in parallel.
I'm trying to optimize the 'quarterly_reporting_pipeline' by running several data preparation steps in parallel. The 'aggregate_sales_data' and 'prepare_marketing_metrics' tasks seem independent, but I'm unsure if the underlying database can handle both queries running simultaneously without contention, potentially slowing both down. Should I run them in parallel and monitor performance, or keep them sequential to avoid potential database bottlenecks and ensure the report is accurate on Friday?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternI frequently find bottlenecks in my pipelines where tasks that could run concurrently are…+
I often find bottlenecks in my pipelines because tasks that could run concurrently are running sequentially.
I frequently find bottlenecks in my pipelines where tasks that could run concurrently are running sequentially, causing unnecessary delays for our business users waiting on data. I'm losing time identifying these opportunities after the fact. What habit should I change to proactively identify and implement parallel execution for independent tasks during the initial pipeline design phase?
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.