'Its no longer enough for an app to tell you what to do. People want to know why': Fitness app Fitbod's founder on the reason behind the AI fitness boom

Date:
Sat, 20 Jun 2026 08:00:00 +0000

Description:
Allen Chen talks all things Fitbod, including whats coming in the coming months.

FULL STORY ======================================================================Copy link Facebook X Whatsapp Reddit Pinterest Flipboard Threads Email Share this article 0 Join the conversation Follow us Add us as a preferred source on Google Newsletter Subscribe to our newsletter It would be fair to say that AI and the rise of chatbots have kicked off a colossal gold rush for fitness
apps . The combination of generations' worth of training knowledge packed
into a device you carry to the gym in your pocket meant the best workout apps were already popular, but now they can adapt on the fly to your needs or queries.

Fitbod is one of those apps, and its one this writer knows very well, having used it for a couple of years. Its a workout app with a big focus on generating plans for your chosen goal, whether thats powerlifting or weight loss, and blends cardio exercises with an impressive catalog of strength exercises. I caught up with Allen Chen, Fitbods cofounder and CEO. Hes a UCLA computer science graduate whos also a NASM-certified personal trainer, making him something of a unicorn in the space. Latest Videos From Watch full video here: A decade under the influence (Image credit: Future) Fitbod launched in 2015, long before the letters A and I were shoehorned into just about any product. I asked Chen what the biggest changes in the development of fitness apps have been in the last 10 years.

The biggest shift is the move from generic training plans to truly personalized strength training, but the most striking thing is actually what hasnt changed, he said. You may like I was bored of my usual fitness apps,
but comprehensive fitness tracker BetterMe dwarfs them in terms of scale Meet CoachCube, the intelligent AI personal trainer that lives inside a Tron-style box room I've been using Google Health's new AI Coach for a week here's 3 things I liked about the Fitbit Premium revamp (and 2 I really didn't)

Resistance training was the core of health and fitness when we started, and
it remains the core today. It transcends trends. Youre seeing gyms actively swap out cardio equipment for free weights and functional training spaces because thats what members want.

What has changed is how people relate to their workouts. When Fitbod
launched, most users were following generic programs they found online, the same templates everyone else was running. Today, people expect personalization. They want a program that reflects their individual schedule, available equipment, recovery status, and fitness goals. Get daily insight, inspiration and deals in your inbox Sign up for breaking news, reviews, opinion, top tech deals, and more. Contact me with news and offers from other Future brands Receive email from us on behalf of our trusted partners or sponsors By submitting your information you agree to the Terms & Conditions and Privacy Policy and are aged 16 or over.

Whats new is that they also expect understanding and support, not just a recommendation. Its no longer enough for an app to tell you what to do.
People want to know why theyre seeing a certain exercise, weight, or workout structure, how it connects to their goals, and what to do when progress slows down. Thats the direction the category is moving in, and its a big part of where were investing.

Chen says Fitbod is tied to real strength-training inputs, and not generic broad-knowledge prompts. The foundation of Fitbod has always been adaptive workout planning. The first version of the app was about solving a hard algorithmic problem: given your workout history and muscle recovery state, whats the optimal workout today? That was genuinely novel in 2015.

The recent AI acceleration has dramatically expanded whats possible on top of that foundation. Were moving from simply generating the right workout to helping members understand their data, interpret their progress, and get more active coaching inside the app. What to read next I asked ChatGPT to build me a realistic weekly workout for a 54-year-old 5 things you need to know about Google Health Forget Whoop, Apple, Garmin, and all the rest when it comes to lifting weights, I've never found a better solution than a spreadsheet

Fitbod doesnt offer a chatbot like the Google Health Coach , but thats going to change soon, with an upcoming feature called Coach Chat. (Image credit: Google) We think about [Coach Chat] in four roles, Chen explains. First, as
an interpreter, it helps explain things like, 'How does Fitbod help me
improve my squat?' Second, as an analyst, it can summarize patterns and help diagnose issues like, Why has my squat plateaued recently?

Third, as a coach, it can guide the next step: 'How do I break out of this plateau?' And fourth, as a motivator, it can reinforce progress and help
users stay consistent when they feel discouraged.

Coach Chat is one part of a salvo of improvements that also includes Workout Insights. This will help users understand why exercises and weights are recommended. Chen says AI can make Fitbod feel much more human, more transparent, and more supportive.

When users hear AI, they sometimes expect instant magic. The reality is that the system gets materially better with more user data. Someone with six
months of logged workouts gets a fundamentally different experience than someone in week one. Keeping users consistent long enough to see that compounding effect, thats still the real product challenge.

This year alone, weve rolled out and expanded features like Focus Exercises, Exercise Percentiles, Injury Mode, Plate Calculator, Live Heart Rate, and broader localization work. Weve also been developing prototypes and internal tools, including Coach Chat, Chart Generation, Insights M0 and M1, an
Internal Evaluation Tool, and a Pydantic Insights Tool, all aimed at making the product smarter, more explainable, and more useful. Next steps (Image credit: Dean Drobot / Shutterstock) With AI becoming an increasingly common part of daily life, Chen says its going nowhere.

In two to three years, AI will have crossed the threshold from novelty to expectation. Users wont just want an app that generates a workout, theyll expect it to explain itself, adapt in context, and support them through the inevitable ups and downs of training.

Systems that can interpret training history, diagnose patterns, explain recommendations, and motivate users in a way that feels timely and personal. In other words, the best products wont just say, 'Heres your workout. Theyll also be able to say, Heres why today looks different, heres what to focus on, and heres what your recent data suggests.

Can users trust programs build by AI? Chen, unsurprising, says yes and he also doesnt think trustworthy AI coaches as a concept will devalue personal trainers or traditional programming.

Trust is a huge issue in AI fitness. If a user can understand why theyre
being asked to squat lighter today, or why a plateau might be happening, theyre far more likely to stay engaged and consistent.

As for devaluing traditional programs, Id argue the opposite. AI handles more of the science, interpretation, and day-to-day adaptation, which frees
coaches to focus on what theyre uniquely good at: judgment, accountability, and the human relationship. The best coaches will become more valuable, not less.

That trust is important when Fitbod (or another app) recommends you go for a PB when youre ready, but how does the company balance the need to push a user to a new goal witb the risk of injury?

Its something we take seriously. Any system generating workout
recommendations at scale carries injury risk if it isnt built with the right constraints, Chen acknowledges.

Most common failure modes are volume spikes, too much, too fast, and failing to respect recovery signals. Fitbods architecture is specifically designed to guard against that. The muscle recovery model tracks fatigue at the muscle-group level, and the system adapts recommendations based on training history, recovery, performance, and user feedback.

Were conservative with newer users, and the app is built to adjust if someone struggles with a weight, takes time off, or changes exercises.

That same philosophy carries into newer product work. Features like Injury Mode are part of a broader push to make Fitbod more supportive when real life interrupts training. And with future coaching features, we want to help users understand not just what to do, but when to scale, when to modify, and how to train more responsibly.

Responsible AI fitness isnt about pushing people harder at all costs. Its about helping them progress safely and sustainably.

Apple s Health app and Androids Health Connect functionality will have a
role to play in that future, too.

The long-term vision is a system that knows not just what you lifted last Tuesday, but how well youve been recovering, how your heart rate is
responding during training, and what that means for what you should do today. Over time, better data infrastructure makes it possible for coaching to
become more proactive.

"Instead of only reacting to what a user logged after the fact, the app can become better at helping them understand whats happening in the moment and what adjustment makes sense next. (Image credit: F8 studio / Shutterstock / Lloyd Coombes) Finally, I wanted to ask how best to take advantage of Fitbods feature set. Ive been using it for a while, but it never hurts to learn more.

Treat setup the way youd approach your first session with a personal trainer. Give it real information: your actual fitness level, your real goals, your actual schedule, and your real equipment. The quality of what Fitbod
generates is directly proportional to the quality of your inputs.

Second, log consistently, especially when you change something. When you swap exercises, adjust weights, change reps, or work through a plateau, that data helps the system learn. The program compounds with use.

Third, use the features that make progress visible. Focus Exercises [like squats, bench press, and other cornerstone lifts] are a great example because they help users stay anchored to lifts they care about most. Metrics, percentiles, charts, and insights all matter because they turn vague feelings into something measurable. Thats especially important on the days when progress feels invisible.

And more broadly: strength training is one of the highest-leverage health investments most people can make. It affects metabolism, bone density, injury resilience, longevity, and day-to-day quality of life. If youre not doing it, start. If you are, get more systematic about it. Thats exactly what were building Fitbod to support. Follow TechRadar on Google News and add us as a preferred source to get our expert news, reviews, and opinion in your feeds. Make sure to click the Follow button!

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Link to news story: https://www.techradar.com/health-fitness/fitness-apps/its-no-longer-enough-for -an-app-to-tell-you-what-to-do-people-want-to-know-why-fitness-app-fitbods-fou nder-on-the-reason-behind-the-ai-fitness-boom


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