How to Practice Yoga With AI

A yoga sequence has an order for a reason. A typical class starts with centering and breath, then warm-ups for the spine and hips, then standing poses, balances and floor work. It ends with a cool-down and a resting pose such as Savasana. Styles differ: Vinyasa links poses with the breath in a continuous flow; Hatha usually holds poses, with pauses between them; Yin holds passive floor poses for several minutes; and Restorative yoga uses props for full support. When you ask an AI for a sequence, name the style, your experience, the time you have, your props and any health conditions. That gets far better results than simply asking for a yoga routine. Dedicated apps such as Down Dog build sequences from settings like level, duration and focus. General chatbots can do similar work and explain why each pose is included. But they sometimes put poses in an unsafe order or pitch them above your level, so read the sequence before you start. Pose-feedback apps use computer vision. A pose-estimation model, such as Google's MediaPipe Pose, detects landmarks like shoulders, hips, knees and ankles in each video frame. The app then compares your joint angles with a target. This can catch obvious problems, such as a bent back leg in Warrior II. A single 2D camera struggles with depth, loose clothing, poor lighting and poses where limbs overlap. The biggest misconception is that you need to be flexible to start. Flexibility is a result of practice, not a requirement. Safety depends on modifications: blocks to bring the floor closer, straps for reach, a chair for balance, and bent knees in forward folds. Never force lotus through the knees. Headstand and shoulder stand load the neck and are best learned in person. People who are pregnant, or who have glaucoma, uncontrolled high blood pressure or recent injuries, should get medical advice about inversions and other poses.