For those who prepared for the GRE during the mid-2010s, these videos weren't just tutorials; they were a lifeline. Here is a look back at why the 2017 iteration of Magoosh Premium set a standard for online GRE prep. In 2017, many competing GRE prep courses were still shipping heavy textbooks or offering grainy, hour-long lecture hall recordings. Magoosh took a different approach. Their 2017 Premium video library was built on the "micro-lesson" concept.
The 2017 videos are remembered fondly because they represented the last "handcrafted" era. Every joke, every slide, and every practice problem felt curated by a human who had taken the GRE 50 times, rather than generated by an algorithm. Yes—with a caveat. The GRE's structure (Quant, Verbal, Analytical Writing) has not fundamentally changed since 2017. The math is the same. The vocabulary is the same. The logic games (Text Completion, Sentence Equivalence) are identical. -GRE Magoosh- Magoosh Premium Videos 2017
This modular approach allowed students to study during a commute, a lunch break, or in the 15 minutes before bed. The 2017 library was the perfect middle ground—robust enough to be thorough, but concise enough to prevent burnout. The heart of the 2017 experience was the instructors. Mike McGarry (affectionately known as "The Test Magician") handled the bulk of the Quantitative section. With his booming voice, dry humor, and encyclopedic knowledge of math traps, Mike turned even the most math-phobic English majors into competent problem-solvers. For those who prepared for the GRE during
However, the GRE did remove the "Analyze an Argument" essay task in late 2023 (replacing it with a broader "Analyze an Issue" task). Therefore, if you find a 2017 archive, skip the "Argument" essay videos. The rest? Timeless. The Magoosh Premium Videos of 2017 represent a specific golden age in test prep. They proved that a digital-native company could beat the dinosaurs (Kaplan, Princeton Review) by focusing on personality, brevity, and deep strategy. Magoosh took a different approach