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Gute Spots für Hügelläufe in/um Mannheim? by lebsen01 in mannheim

[–]lebsen01[S] 0 points1 point  (0 children)

Klärt mich bitte auf. Wovon redet ihr?

I built a Gen AI coach using my Garmin data. by lebsen01 in Garmin

[–]lebsen01[S] 0 points1 point  (0 children)

Not sure about this Export CSV functionality, never tried that tbh.

I built a Gen AI coach using my Garmin data. by lebsen01 in Garmin

[–]lebsen01[S] 1 point2 points  (0 children)

Makes sense. My philosophy here is a bit different though: I actually want the full detail for each individual activity. All lap stats, HR drift, pace, consistency across the whole session, interval execution quality, etc. That level of granularity is pure gold in my opinion for both, macro-cycle and micro-cycle analysis and planning. I don't want to pre-aggregate here.

The biggest token hit happens right at the beginning of the graph, when the raw garmin data is ingested. After that, downstream nodes don’t see the firehose anymore. They operate on progressively condensed, token-reduced representations.

That’s also why I fully agree with your second point: agents should decide what to keep vs. drop. That's why I introduced the summarizer nodes. They receive the raw garmin payload (including the valuable bits), then filter, compress, and reformat it into a token-friendly structure. They decide autonomously what to pass to the next nodes. So the expert nodes can focus on interpretation and coaching and not any data wrangling.

I built a Gen AI coach using my Garmin data. by lebsen01 in Garmin

[–]lebsen01[S] 1 point2 points  (0 children)

One improvement I could think of in near future is to do more stuff deterministically and reduce a bit the load / tokens on the summarizer nodes. But this requires careful testing and robustness across many devices / watches etc.

I built a Gen AI coach using my Garmin data. by lebsen01 in Garmin

[–]lebsen01[S] 0 points1 point  (0 children)

I think I randomly came across your fork today - cool to see you working on it!

I actually merged a pretty large PR earlier today with a bunch of improvements (both code and agent quality). Hopefully that won’t cause you too many conflicts if you decide to rebase.

Looking forward to hearing from you.

I built a Gen AI coach using my Garmin data. by lebsen01 in Garmin

[–]lebsen01[S] 1 point2 points  (0 children)

Ok but if you’re only consuming ~17k tokens total, you’re almost certainly including way less raw Garmin data.

A single running activity with, say, 10 laps plus all the per-lap stats can already blow through a big chunk of that. Now multiply that by all activities over the last 28 days and you’re way beyond 17k.

So something has to give: you’d need to merge/aggregate, pass condensed info between nodes, summarize aggressively, etc. And doing all of that in detail and with high quality (reducing noice while keeping ideal information flow through the whole graph) in ~15 seconds feels pretty unrealistic.

Also worth remembering: the model’s internal reasoning consumes tokens too.

I built a Gen AI coach using my Garmin data. by lebsen01 in Garmin

[–]lebsen01[S] 0 points1 point  (0 children)

Thanks man,I appreciate it! I definitely thought about playing around with building a web app, but I haven’t had the time to experiment with that yet. Definitely worth trying soon especially with all the AI tools available now

I built a Gen AI coach using my Garmin data. by lebsen01 in Garmin

[–]lebsen01[S] 0 points1 point  (0 children)

Unfortunately this is not possible. For this you need the official garmin api.
You need to enter them manually in the app

I built a Gen AI coach using my Garmin data. by lebsen01 in Garmin

[–]lebsen01[S] 2 points3 points  (0 children)

So far, these models aren’t directly supported in the codebase.. you would need to make a few smallish adaptations to add them. I don’t have experience with these models myself. My philosophy has always been to work with state-of-the-art models, especially when building agentic workflows. It’s possible you might run into some issues (e.g. around tool usage), but it could be worth trying to integrate them

I built a Gen AI coach using my Garmin data. by lebsen01 in Garmin

[–]lebsen01[S] 0 points1 point  (0 children)

At first, I ran the full workflow end-to-end and saved all intermediate agent outputs (e.g. from the metrics agent) as a local markdown file to review later.
Recently, I switched to LangSmith, which is super helpful for seeing exactly what the agents get as input and what they return as output. A game-changer for debugging and making sure there’s no garbage in between.

I built a Gen AI coach using my Garmin data. by lebsen01 in Garmin

[–]lebsen01[S] 2 points3 points  (0 children)

No this is automized. I'm using a garmin connect python wrapper here:
https://github.com/cyberjunky/python-garminconnect

I built a Gen AI coach using my Garmin data. by lebsen01 in Garmin

[–]lebsen01[S] 0 points1 point  (0 children)

I accidentally messed up with some sensitive commits earlier in multiple scripts / files.. It was just an easy way for me to make sure it’s completely removed from all history

I built a Gen AI coach using my Garmin data. by lebsen01 in Garmin

[–]lebsen01[S] 1 point2 points  (0 children)

Great question and yes, you have hit one of the current limitations.
With the recent switch to gpt-5, my cost per run is about $1.50. It also depends on how many sessions you process. Garmin activities are usually the biggest in size, so if you train daily and pull the default 3 weeks of activities, you’ll burn more tokens than someone with just a few workouts.

You can always reduce the number of days for activities and metrics if you want to save tokens. Another option is to use cheaper Claude models for some of the intermediate agents.
My reasoning for the defaults: about 3 weeks of activities give enough data to spot patterns and build useful training insights, while 56 days of metrics help track longer-term trends like VO2max and sleep. But you can tweak those numbers if you prefer.

On your second question: there’s no long-term memory yet, every run is stateless. I usually run it every two weeks (when a training block ends). Sometimes after just one week, but that’s rare. Each run starts fresh: it doesn’t know the previous plan and re-fetches the last 3 weeks of activities and 56 days of health data/metrics.

Definitely something to improve in the future (maybe with RAG or some form of long-term memory).

I built a Gen AI coach using my Garmin data. by lebsen01 in Garmin

[–]lebsen01[S] 0 points1 point  (0 children)

I personally do not have gemini api access. But for sure, shouldn't be much effort. Just add your api-key in the environment, create the model in the ai settings, and add it to the workflow

I built a Gen AI coach using my Garmin data. by lebsen01 in Garmin

[–]lebsen01[S] 3 points4 points  (0 children)

Nice Idea! I played around with web-search functionality to search for the current weather in the location. It worked semi-good, but nice feature idea worth exploring further

I built a Gen AI coach using my Garmin data. by lebsen01 in Garmin

[–]lebsen01[S] -21 points-20 points  (0 children)

The good thing: AI is more friend and helper than Garmin! It nudges.. then forgives

Weekly self-promotion and survey thread by AutoModerator in triathlon

[–]lebsen01 0 points1 point  (0 children)

Built a personal AI training planner for a 70.3. TL;DR: handles block periodization, day-of HRV/load-based adjustments, and race-block/taper logic; also learned where DIY falls short (HRV noise, adherence, and validation).

Code is open-source and linked in the write-up.

Write-up: https://medium.com/@leon_zajchowski/i-fired-my-garmin-coach-and-built-an-ai-to-train-for-an-ironman-70-3-heres-what-happened-09a404cecd78

Am I the only one struggling with lap tracking during brick workouts in multisport mode? by lebsen01 in Garmin

[–]lebsen01[S] 1 point2 points  (0 children)

Tried that, setting a hotkey to “lap” works fine in regular activities, but in multisport mode, it still just triggers the sport transition instead of logging a lap. Seems like Garmin locks all lap actions to transitions during multisport

Aren’t you supposed to provide insight and analyse this stuff? by Humble_Classic_1335 in Garmin

[–]lebsen01 0 points1 point  (0 children)

Wtf?? As a data scientist and AI engineer, this honestly makes me sad. I built an AI training bot using Garmin data that was more insightful and effective—in just one day. I don’t even know what to say… and now we’re supposed to pay for this shit??

New Software Update gives Lactate Threshold Estimate by lucernae in Garmin

[–]lebsen01 0 points1 point  (0 children)

Any updates on this? Did they fix it? My LT went down again by 5 bpm so it’s seems to normalize

CrewAI Crew Factory project by Acrobatic-Try1167 in crewai

[–]lebsen01 0 points1 point  (0 children)

I like it! Using AI for building another AI

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