u/Helloimlost_

Dear GMAC Team,
I have taken the GMAT multiple times over the past two years, and I wanted to share some feedback about the recent versions of the exam.
The exam now feels much more dense and time-pressured than before, especially in Data Insights but also across other sections. Many questions seem to require too much reading, interpretation, and multi-step reasoning for the time provided. The issue is not just that the questions are difficult, but that the overall balance between question complexity and available time feels unfair.
Even strong test takers may understand how to solve the questions but still not have enough time to properly process them. The experience increasingly feels like managing overload rather than demonstrating reasoning ability.
I also wanted to ask whether AI or machine-learning tools are being used in question creation or exam calibration, because the style and density of recent questions feel noticeably different from earlier versions of the GMAT.
I hope this feedback is useful as you continue reviewing the exam experience.

Dear GMAC Team,
I have taken the GMAT multiple times over the past two years, and I wanted to share some feedback about the recent versions of the exam.
The exam now feels much more dense and time-pressured than before, especially in Data Insights but also across other sections. Many questions seem to require too much reading, interpretation, and multi-step reasoning for the time provided. The issue is not just that the questions are difficult, but that the overall balance between question complexity and available time feels unfair.
Even strong test takers may understand how to solve the questions but still not have enough time to properly process them. The experience increasingly feels like managing overload rather than demonstrating reasoning ability.
I also wanted to ask whether AI or machine-learning tools are being used in question creation or exam calibration, because the style and density of recent questions feel noticeably different from earlier versions of the GMAT.
I hope this feedback is useful as you continue reviewing the exam experience.

My org is considering introducing Prefect for orchestration instead of Airflow because our current scale probably doesn’t justify the operational overhead of Airflow yet.

From a data engineering career perspective, is deeply learning Prefect (DAGs, retries, dependencies, validations, observability, backfills, etc.) enough to transition smoothly later into Airflow/Azure/cloud DE stacks?

Or does not working directly with Airflow early on become a disadvantage when switching roles later?

Would love perspectives from people who’ve made that transition.