Why Virtual & Smartwatch Coaches Suck (and here’s the fix)

May 28, 2025 | By DLake

Audio

Video

Strava is Pace-IST and doesn’t care about short-distance people. And to be fair, neither do most running apps. There, I said it.

I ran my fastest 1 mile (1.6km) race at 4:54 when I hit 40 years old, and because it’s a 1 mile run… I think I got 10 kudos. But if I walk-run 30kms at an easy pace – 50 people will say “Wow- great job!” —- one is objectively much harder effort than the other.

In this episode, I’m breaking down why AI and virtual coaches are totally failing the health and fitness industry and what needs to change to make these tools actually helpful for runners like you and me. Spoiler: it’s not about more metrics; it’s about better insights.

Let’s start ignoring our favorite “Training unproductive” status update after your hardest run ever.

Listen to audio podcast below on your next run or watch video the video above to learn more

Picture This Beautiful Scenario

Imagine this: You finish one of your most challenging workouts, and Garmin hits you with the dreaded “Training Unproductive.”

Wait.. what?! My heart rate was pinned in zone 5 for 7 minutes, and I almost passed out, and that was unproductive?

This is the problem with most fitness tech. They’re obsessed with data, but they fail at giving actionable advice. Strava is too busy rewarding ultra marathoners doing 100-mile 24-hour races and KOM chasers. Garmin just nags you about recovery metrics that make no sense half the time, and whoop’s rest recommendation is like throwing a magic eight ball down the stairs to see where it lands – shouts to D.C. Rainmaker.

Here’s the deal: Running apps prioritize generic data over actionable insights. They can tell you your heart rate, pace, and distance, but when it comes to answering the big questions—like “What should I do next?” or “Am I really losing fitness one day after a race?”—they fall flat.

Why These Apps Miss the Mark

Let’s break this down:

Data vs. Insights

• Data is raw: heart rate, distance, pace. It’s the “what.” What is pointless and leads to so what if there is no how and why following it.
• Insights: now these are good because they’re actionable: eg, “Do this next.” Now this is the “why” and “how.”

Here’s the problem: most apps stop at data. They don’t connect the dots. Garmin, Strava, and even Apple assume everyone is either a Couch-to-5K beginner or an elite marathoner chasing best times every 3 days. There’s no middle ground.

This is like if Google Maps only gave you directions for driving, but didn’t work for walking or cycling.

Like seriously… Why don’t these apps ask us why we’re training? If Strava asked, “What’s your goal for this run… this week… this month… this quarter or this year?”—and adjusted their insights accordingly— I would be many light-years ahead of where I am now.

Garmin is constantly saying I lack anaerobic training. But I do a lot of base training with lots of VO2 max sprint work and even some tempo efforts.

I just found out (by experimenting) that it’s based on speed and pace and not energy systems used.

So – if i did an easy run and my hr never got over z2 but I did 10x strides/sprints at 95% – i would get a few points for anerobic.

This is confusing because I thought anaerobic meant an energy system, like being aerobic in z1, z2, and anaerobic glycogen stores in z3-z5 – this is confusing, they should say that. I did a post on Instagram, and everyone was confused.

It wants me to do sprints and blow up my Achilles. What if I could tell it that I am doing strides, but I have to cater to my Achilles and back down on the rigid training stimulus zones.

So if the apps are built for beginners, what happens when you’re not a beginner anymore?

Here’s a quick history of how we got to this mess

• 2009-2012: Strava launches, and suddenly everyone becomes obsessed with being “King/Queen of the Mountain.” Runners and cyclists start taking weird detours just to grab segments. The gamification addiction begins.
• 2013-2015: Social fitness explodes. Your aunt’s dog walker is now sharing their “Morning Power Walk!” complete with pace analytics and heart rate zones they don’t understand. Everyone becomes an amateur exercise physiologist.
• 2016-2018: Enter the “streaks” era. Apps start rewarding consistency over quality. People start running with the flu just to keep their streak alive. Because obviously, that’s healthy.
• 2019-2021: Covid running boom and virtual racing — AI enters the chat. Instead of making things better, it just adds more confusing metrics. Now your watch tells you your “Training Load Focus” is off while you’re just trying to enjoy a casual jog.
• 2022-Present: The algorithmic arms race. Every app tries to outdo the others with more complex metrics. Meanwhile, runners are still just wondering, “Should I run hard today or take it easy?”

The result? A perfect storm of overcomplication, social pressure, and misaligned incentives. We’ve created a monster that values virtual badges over actual athletic development.

But here’s where it gets really interesting—and concerning.

The “Cater to the Average” Trap

Here’s something I finally figured out that most don’t know: these apps are built for the average runner—and by “average,” I mean the newbie who’s just trying to finish a 5 K. That’s fine, but what about the rest of us?

For experienced runners, progress is incremental. We’re chasing tiny gains over months, not dramatic beginner curve transformations that happen in weeks. But these apps don’t get that. Instead, they serve up generic responses like “Great run!” or “You’re overtraining,” without considering the bigger picture.

(Reword this) However, I will say that when used correctly, Strava’s metrics like fitness, freshness, form, fatigue, and relative effort can be incredibly accurate training tools. I’ve seen this firsthand with several runners I coach – when they input clean, accurate data consistently, these metrics provide valuable insights into their training progression and recovery needs. The key is understanding how to interpret these numbers in the context of your specific training goals and being diligent about logging accurate data.

Stravas fitness freshness and form feature, while quite complex and valuable, still falls flat for me. If you don’t continue to train long and hard after a long or hard effort your “fitness” declines quick.

This incentivises people to keep pushing through rest days and recovery weeks to keep that fitness score high. Unacceptable. How about taking into account the whole picture and that a recovery week at 50% volume is what you need to improve your fitness to run your fastest marathon in 13 weeks. Nope… that’s too hard.

The truth is, very few runners fall in the “average.” Average is the mean of all the outliers…. Everyone’s goals, fitness levels, and training needs are unique. But these apps treat us all the same.

(Transition)

So, how does gamification and streaks make this “one size fits all” approach even worse?

The Gamification Problem

Last – let’s talk about gamification. It’s fun… until it isn’t.

These apps push you to chase arbitrary milestones: segment KOMs, fitness streaks, and PRs. But here’s the problem: this behavior leads to burnout, overtraining, and a toxic obsession with numbers.

Think about it: how many times have you skipped a recovery run because you didn’t want your fitness score to drop? Or pushed through an injury to maintain that all-important streak?

I know too many folks who do this and are also the runners who have to end their run on an even number.

Instead of rewarding smart training decisions, like slowing down for an easy day or taking a rest day altogether, these apps glorify run hustle culture and can make the unaware susceptible to appeasing the masses and constantly putting up “epic run.s”

We’ve turned running into a numbers game, and the algorithms are winning.

From gamification gone wrong to algorithms that can’t tell the difference between a recovery jog and a tempo run, it’s clear that our current running tech is stuck in the Stone Age of AI — but there’s hope if we’re willing to take control of our own data destiny.

The Finish Line: A Better Future for Running AI

The solution is pretty clear: we need apps that prioritize goal-specific feedback over generic metrics. Imagine opening your running app and seeing your actual training priorities front and center – not just arbitrary numbers, but metrics that matter for YOUR goals.

Picture daily intention setting displayed like Instagram stories, where your followers can support your specific training journey. Or progress tracking that shows direct correlations between today’s workout and your long-term goals.

This isn’t just about better algorithms – it’s about building a community that understands and supports each runner’s unique journey.

If you’ve dealt with frustrating AI fails from your running apps, I want to hear about them! Drop a comment below with your worst “AI coach fail” moment. Was it a watch telling you that your marathon best time was “unproductive”? Or maybe Strava suggesting you should do hill sprints during your recovery week?

Let’s change this!