How does an AI workout planner work?

Profile → planning

Start with a goal, experience level, available equipment and a realistic weekly schedule. Mylus store descriptions identify these as inputs to personalized planning. Accurate constraints are more useful than an ambitious schedule you cannot follow.

Training → feedback

A generated program is a starting point. Record what you actually completed and how the work felt. Completion, effort and pain convey different information: missing a session because of travel is different from stopping a set because of pain.

Feedback → adjustment

Review training patterns alongside changes in equipment, schedule and goals. AI can help explain options, but every logged session does not imply an immediate autonomous rewrite. Check the saved prescription and understand any proposed change before using it.

Questions and answers

Can AI create a personalized program?

It can propose a program using the constraints you provide. Personalization is only useful when the proposed exercises, workload and schedule are feasible. Review the output and correct inaccurate inputs.

Does a plan change after every session?

Do not assume that it does. Logging feedback and applying an adjustment are separate steps. Stable, repeatable sessions also make progress easier to interpret.

What makes feedback useful?

Record what changed and why: available time, missed sessions, completed work or unexpected discomfort. Specific context is more actionable than saying only that a workout was bad.