Building S&C Programmes in Action Apps’ Workout Builder
This post explores Action Apps’ new Workout Builder tool, the latest feature in their athlete data management system.
Strength and conditioning programming is rarely just about writing an isolated workout. Practitioners need to manage exercise libraries, session templates, athlete maximums, training blocks, programme progressions, athlete assignments, gym delivery and reporting.
That process can quickly become fragmented if different parts of the workflow are managed across separate spreadsheets, documents, apps or dashboards.
Action Apps has developed a new Workout Builder feature to bring this process together within their athlete management system. In the accompanying video, I provide a walkthrough of the tool, from building individual exercises through to longer-term programmes, athlete assignment, reporting and AI-assisted session generation.
The aim is not simply to make a programme look more organised. The value is in connecting the plan, the delivery and the review process in one place.
From Exercises to Programmes
One aspect I like about the Workout Builder is that the programming area is structured from smallest to biggest. You start with individual exercises, then build these into blocks, workouts and longer-term programmes. These programmes can then be assigned to athletes and tracked through the system.
This reflects how many practitioners actually work. We might have individual exercises we use regularly, common warm-up blocks, strength blocks, rehab circuits or session templates that are repeated and adapted across a squad. Equally, if you prefer a different workflow, you can bounce between these different levels.
At the time of recording, the exercise library included more than 1,300 pre-built exercises, each with embedded videos, tags and metadata. However, the system is customisable, so the library can also be adapted to reflect the exercises, terminology and progressions used within a specific team or organisation.
For many environments, the real value is in having a clean and relevant library that reflects what the team actually uses. More exercises doesn't automatically mean better!
Building Workouts and Programmes
From there, exercises can be grouped into blocks and built into full workouts.
A block might be a warm-up, activation series, trunk circuit, hamstring block or any other repeated section of a session. Rather than rebuilding that from scratch each time, it can be saved and dropped into a workout when needed.
The workout itself can then be edited by changing the exercises, order, sets, reps, rest periods and loading prescription. Everything is customisable. The system allows for different prescription methods, including absolute load, percentage of 1RM, percentage body weight, RPE, reps in reserve (RIR) or manual entry.
Once the workouts are created, they can be organised into a longer-term programme. In the video, I demonstrate how sessions can be placed across a calendar, copied, moved and structured into different training phases.
There are also options to apply periodised changes across the programme, so prescriptions can increase or decrease over time without manually editing every week.
Of course, the practitioner still needs to decide whether those changes are appropriate. But as a starting point, especially when managing a larger group of athletes, that type of automation can reduce a lot of repetitive admin.
Connecting Planning, Delivery and Reporting
Programmes can be assigned to athletes, delivered through the athlete app or gym view, and then tracked through the reporting dashboards. That means the practitioner can see not only what was planned, but what was actually completed.
Closing the loop is just as important to load monitoring off the field, as it is on it. We need to know whether the athlete completed the session, what load they used, how adherence is tracking, and how that work accumulates over time.
In the reporting section, practitioners can review information at squad, athlete and programme level. This includes session completion, adherence, actual weights completed, tonnage, RPE and other useful training information.
That creates a more connected workflow: exercises feed into sessions, sessions feed into programmes, programmes are assigned to athletes, and the completed work feeds back into the reporting process.
AI Builder and Return to Play Context
The Workout Builder also includes an AI Builder feature. As with the previous Action Apps videos on their AAVA and RTP features, I think this needs to be framed carefully. AI should not remove the practitioner from the process, but it can be useful when it helps us work more efficiently and connect information that already exists within the system.
In the video, I show how the AI Builder can generate a workout based on the selected goals, guidance and notes. More interestingly, it can also connect with the Return to Play module and pull through injury context from an athlete’s rehabilitation plan.
That is where the wider athlete management system becomes particularly useful.
Instead of treating programming and rehabilitation as separate workflows, the AI Builder can use information from the athlete’s RTP plan to help generate a more contextually relevant draft session. If you haven't already seen the AI-generated rehab tool, check out the post here.
The key word there is draft. The practitioner still needs to review the session, check the exercises and prescription, and decide whether it is appropriate for the athlete in front of them. AI can help create a starting point, but it should not replace the critical thinking required to programme well.
AI should not remove the practitioner from the process, but it can be useful when it helps us work more efficiently and connect information that already exists within the system.
Final Thoughts
For me, the value of the Workout Builder is not any one feature in isolation. It is the way the different parts connect. The exercise library connects to blocks. Blocks connect to workouts. Workouts connect to programmes. Programmes connect to athlete assignment and gym delivery. The completed work then connects back into reporting.
That is much more useful than a static programme document that sits separately from the athlete’s wider data.
It also creates opportunities for AI to support the practitioner in a more meaningful way, because the system has access to more context. Rather than generating something from a blank prompt, the AI Builder can draw on the athlete’s plan, selected guidance and available evidence within the system.
There are still caveats, and the practitioner remains central to the process. But used in that way, AI can support planning without replacing professional judgement.
There is more within the feature than I could cover in one video, so this is very much an overview and there's more to come on this. However, it gives a useful insight into how practitioners can bring together programme planning, delivery and reporting in one connected workflow.
It is not just about building workouts. It is about creating a clearer link between what was planned, what was delivered, what the athlete completed and what the practitioner does next.
📄 Explore more:
Learn more about Action Apps
Watch the full demonstration: Action Apps Workout Builder and AI-Driven Programme Planning
This article is supported by Action Apps. For more information about their services, visit their website.
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