STAS.run VS Diffyn

STAS.run's answer

STAS is the only coaching system that creates a live data pipeline between sports watches and ChatGPT. Instead of asking athletes to describe their workouts in chat, STAS automatically pulls every session from Intervals.icu, classifies it (Easy/Threshold/Interval/Long/Race), calculates VDOT from Daniels' Running Formula, tracks CTL/ATL/TSB trends, and feeds structured data — including splits, HR zones, and wellness metrics — directly into a Custom GPT. The AI coach sees what a human coach would see, not what the athlete remembers to type.

Diffyn's answer:

Addresses workflow and change management on LLM prompts, provide teams with traceability and visualization of tests across multiple models, provide deeper understading into efficiency of these prompts.

STAS.run's answer

Most AI coaches (Runna, TrainAsONE, Garmin Coach) use closed algorithms — you can't see the reasoning or adjust the approach. STAS uses ChatGPT as the coaching engine, so every recommendation is transparent and conversational. You can ask "why this workout?" and get a real answer based on your actual data. Plans are written directly to your Intervals.icu calendar. And STAS is free — you only need a ChatGPT subscription you may already have.

Diffyn's answer:

Diffyn is the platform that specializes on both change management and multi-model analysis.

STAS.run's answer

Next.js (TypeScript, App Router), PostgreSQL with Prisma ORM, Intervals.icu API for training data, Mistral AI for workout classification and condition analysis, OpenAI Custom GPT for the coaching interface, grammy framework for Telegram bots, and Docker Compose with Caddy for deployment. VDOT calculations use Daniels' Running Formula tables implemented in code.

Diffyn's answer:

React, Next.js, POSTGRESQL

STAS.run's answer

Self-coached endurance athletes — primarily runners training for half marathons, marathons, and ultras — who track workouts with Garmin, Polar, COROS, or Suunto watches and want data-driven coaching without hiring a human coach. Also triathletes and cyclists who use Intervals.icu as their analytics hub. Typical user: intermediate to advanced, trains 4-6 days/week, cares about periodization and metrics.

Diffyn's answer:

Professionals incorporating LLMs or AI tools in their workflow and wants to keep track of changes and test their prompts.

STAS.run's answer

I'm a runner who got tired of screenshotting Garmin stats into ChatGPT and getting generic advice back. The AI had no idea about my training load trends, fatigue levels, or pace history — it was just guessing. So I built a pipeline that feeds real watch data into a Custom GPT through Intervals.icu. What started as a personal hack became a full system: automated workout classification, VDOT tracking, condition monitoring, and a Telegram bot for post-run reports. Now it coaches me and a small group of athletes daily.

Diffyn's answer:

I started working on Diffyn when I notice that prompting has become an essential part of work across many industries. While there are version control platofrms like github, they are not designed for just prompt management are can be overkill such applications, it is also not integrated natively with various LLMs and relevant tools for users to validate ideas and visualise results properly.

STAS.run's answer

Independent marathon and ultra runners in Europe training without a coach Triathletes using Intervals.icu as their central analytics platform Garmin and COROS users who want AI-powered training plan generation Runners preparing for specific goal races (sub-3:30 marathon, first ultra, etc.) Athletes returning from injury who need careful load management