Workout Reserve and the Future of AI Coaching

PART 2: Workout Reserve and the Future of AI Coaching

💥 Dr. Andrea Zignoli wants you to understand that Workout Reserve is not just another performance metric—it’s a breakthrough in how we track and interpret what athletes can actually do in real time.

In Part 2 of this deep-dive on the Training Science Podcast, Andrea and Paul explore why traditional models like W′ fall short, and how Workout Reserve offers a more flexible, mechanical (not physiological) way to understand athlete capability. Plus, they tackle the future of AI coaching—how RAG-AI and Large Language Models are reshaping how athletes and coaches engage with data.

📊 Why Workout Reserve works when W′ doesn’t ⚙️ How mechanical models sidestep physiological guesswork ⏱️ Real-time fatigue, durability, and “limiting tau” explained 🧠 The future of AI coaching: RAG-AI, LLMs, and agents in training platforms

Speakers:

Prof. Paul Laursen https://www.paullaursen.com/

Dr. Andrea Zignoli https://andreazignoli.github.io/