Automated Fitness Coaching with Strava

This workflow is designed for triathletes, fitness coaches, and sports enthusiasts who want to leverage their Strava activity data to improve performance and receive personalized coaching. It is particularly beneficial for:

• Athletes looking to enhance their training through data analysis.
• Coaches wanting to provide tailored feedback based on detailed performance metrics.
• Fitness enthusiasts who seek motivation and structured improvement plans based on their activity history.

This workflow addresses the challenge of analyzing and interpreting Strava data to provide actionable insights for athletes. It transforms complex activity data into understandable feedback, helping users:

• Identify areas for improvement in their training.
• Receive personalized coaching tips based on performance metrics.
• Stay motivated with structured plans and goal-setting.

1. Strava Trigger: The workflow begins by listening for updates on Strava activities via a webhook. When an activity is updated, it triggers the workflow.
2. Code Node: The incoming activity data is processed to add new fields if necessary, preparing it for further analysis.
3. Combine Everything: The data is flattened into a single string format, making it easier to analyze.
4. Fitness Coach: The flattened data is sent to a LangChain agent that acts as a triathlon coach, analyzing the data and providing personalized coaching feedback.
5. Structure Output: The feedback is structured into various sections for clarity, including headings, lists, and paragraphs.
6. Convert to HTML: The structured output is then converted into HTML format for easy readability.
7. Send Email: Finally, the HTML content is sent as an email to the user, providing them with insights and recommendations based on their recent activity.