This article provides a complete, practical walkthrough of the Code Strava Send Triggered n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Advanced setup in 1-2 hours. One‑time purchase: €69.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:
   AI Triathlon Coach with n8n: Automate Personalized Fitness Coaching from Strava to Email & WhatsApp
   
   Meta Description:
   Discover how to automate personalized triathlon coaching using n8n, Strava, and Google Gemini. This smart workflow delivers tailored training advice via email or WhatsApp, making data-driven athletic improvement seamless.
   
   Keywords:
   n8n automation, Strava API, Google Gemini, triathlon coach, fitness workflow, AI training assistant, personalized coaching, swimming cycling running, fitness automation, WhatsApp fitness bot, email training tips, AI triathlon advisor
   
   Third-Party APIs Used:
   
   1. Strava API – For receiving real-time activity updates (webhook trigger).
   2. Google Gemini (PaLM) API – For AI-driven analysis and feedback generation (Large Language Model Chat integration).
   3. Gmail API – For sending performance feedback via email (Google OAuth2 authentication).
   4. WhatsApp Business Cloud API – For delivering personalized coaching insights via WhatsApp.
   5. SMTP API (OCI) – For sending styled HTML emails as a coach (generic SMTP support).
   
   —
   
   Article:
   
   Automate Your Fitness Journey: How This n8n Workflow Turns Your Strava Data into a Personalized Triathlon Coaching Experience
   
   As fitness and tech cultures intertwine, automation platforms like n8n are making it possible to interpret athletic data like never before. This article walks through an intelligently designed n8n workflow that transforms raw Strava activity data into personalized coaching insights—delivered straight to your inbox or even to your WhatsApp.
   
   At the heart of this automation is a virtual Triathlon Coach—a GPT-powered agent fine-tuned to understand your unique training needs across swimming, cycling, and running. Designed by workflow architect Amjid Ali, this automation exemplifies how a blend of APIs, AI, and thoughtful data engineering can revolutionize your training regimen.
   
   Let’s break down how this intelligent system works.
   
   Step 1: Strava Activity as the Trigger
   
   The journey begins with the Strava Trigger node listening for activity updates—whether it's a morning swim, a hilly bike ride, or an evening run. Once a new activity is recorded or updated in your Strava account, it automatically fires off the rest of the workflow.
   
   This event-based trigger removes the need for manual monitoring, ensuring your workout data is effortlessly captured the moment it's logged.
   
   Step 2: Flatten and Prepare the Data
   
   The captured raw JSON from Strava is often deeply nested and hard to read. Enter the Combine Everything node—a Code node that recursively flattens this structured data into a readable and coach-friendly string format.
   
   This transformation is essential for making the data more digestible for the AI and suitable for prompt injection.
   
   Step 3: AI-Powered Triathlon Coach Analysis
   
   Now for the magic moment: an AI-based agent powered by Google Gemini (formerly PaLM) steps in. The "Fitness Coach" node is heavily primed with coaching expertise—capable of evaluating metrics like pace, heart rate, stroke efficiency, and cadence. Not only does it assess your performance, it tailors its advice according to your experience, goals, and recent trends.
   
   Example capabilities include:
   
   - Recommending brick workouts (e.g., bike + run)
   - Suggesting recovery strategies
   - Offering swim drills based on stroke count and pace
   - Analyzing cadence, power zones, and even time-of-day training impact
   
   All feedback comes back structured, motivational, and most importantly—actionable.
   
   Step 4: Structuring the Output
   
   Once the AI returns its coaching output, a code module called "Structure Output" neatly classifies its content into headings, paragraphs, bullet points, or numbered lists. This segmentation ensures not only readability but also enhances visual appeal in the next step.
   
   Step 5: Convert to HTML
   
   Whether you're receiving feedback by email or chat, a raw text format might not do it justice. The "Convert to HTML" node styles the structured content, applying paragraphs, heading tags, unordered and ordered lists to transform plain text into a clean HTML document.
   
   Step 6: Multichannel Delivery: Email or WhatsApp
   
   Here’s where personalization and convenience meet. You can choose your preferred channel:
   
   - Email: The Gmail node or a standard SMTP node sends the HTML report with subject lines like “New Activity on Strava,” making it perfect for archiving and reviewing.
   - WhatsApp: Prefer real-time chat interaction? The WhatsApp Business Cloud API can deliver the same insights directly into your messenger app. Your AI coach is now just a ping away.
   
   Optional Enhancements and Notes
   
   The workflow contains helpful sticky notes for onboarding, such as guidance on generating a Strava API key or instructions for adapting the coach to suit race preparations or performance plateaus. Additionally, there’s a warm nod from the workflow's creator, encouraging community sharing and offering learning resources for those inspired to create their own workflows.
   
   The Takeaway
   
   This n8n automation isn’t just a series of nodes—it's a full-fledged virtual coaching assistant. Ideal for triathletes, fitness enthusiasts, and even amateur hobbyists looking to make sense of their Strava data, the combination of real-time data ingestion, AI analysis, and omnichannel output provides a one-of-a-kind experience.
   
   By integrating Strava, Google Gemini, email, and WhatsApp, this workflow offers a glimpse into how the future of athlete training could (and should) look: smart, seamless, and story-rich with data-driven insights.
   
   Ready to level up your fitness smartly? This might just be the perfect companion to guide your training—one email, or WhatsApp message, at a time.
   
   —  
   Created by: Amjid Ali  
   Explore other automation projects and full courses at [Syncbricks Learning Portal](http://lms.syncbricks.com)  
   Support the creation of more templates at [PayPal](http://paypal.me/pmptraining)

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.