Send us a text Happy New Year and welcome to 2026! In this Rapid Fire Q&A episode of Between 2 Racks, the KILO Crew kicks things off with a quick update on what’s ahead this year, including the final live course dates at our facility, upcoming travel seminars, and what online courses are coming next. Then we dive into your questions, starting with the difference between “optimal reps” and context driven rep selection, and why the internet’s obsession with one perfect rep range is missing...
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Send us a text Happy New Year and welcome to 2026! In this Rapid Fire Q&A episode of Between 2 Racks, the KILO Crew kicks things off with a quick update on what’s ahead this year, including the final live course dates at our facility, upcoming travel seminars, and what online courses are coming next. Then we dive into your questions, starting with the difference between “optimal reps” and context driven rep selection, and why the internet’s obsession with one perfect rep range is missing...
Rapid Fire Q&A: Big Picture Thinking, Parallel Periodization & Much More
Between 2 Racks
50 minutes
2 months ago
Rapid Fire Q&A: Big Picture Thinking, Parallel Periodization & Much More
Send us a text In this Rapid Fire Q&A, the KILO Crew zooms out to big picture program design. We cover how to plan mesocycles in the context of a macrocycle, why intensity drives quality selection, and where parallel periodization actually fits. You will hear when to use phase undulating models, how to prevent interference, and how to balance variation with mastery so progress does not stall. 00:00 Welcome & Introduction 00:19 Designing a Mesocycle: Strength Qualities & Over...
Between 2 Racks
Send us a text Happy New Year and welcome to 2026! In this Rapid Fire Q&A episode of Between 2 Racks, the KILO Crew kicks things off with a quick update on what’s ahead this year, including the final live course dates at our facility, upcoming travel seminars, and what online courses are coming next. Then we dive into your questions, starting with the difference between “optimal reps” and context driven rep selection, and why the internet’s obsession with one perfect rep range is missing...
