Email Not Sending? Debugging in AI Full-Stack Apps

The Vibe Coding Trap: When Emails Just Will Not Send and You Have No Idea Why

So you have gotten 85 percent of your app built. Most of the functionality is working. Now you are focusing on the UX and decide to add email notifications beyond the usual login and forgotten password.

You look for the best solution, ask AI to help, and everything seems fine. The AI generates some code, you plug in your SendGrid API key, and emails just wont send.

No emails. No errors in the logs. No obvious signs of failure.

And if you are lucky, after hours of debugging, you find the culprit. But in most cases, this is where users give up. Stuck in an endless loop of 500 or 404 errors with no clear reason why things are failing.

This guide will break down the problem, explain why it happens, and show you how to fix it. Let’s get into it.just 

The Problem: Dynamic Preview Deployments & Base URLs

Many AI-powered development platforms deploy new versions of a site with a unique URL each time. While great for testing, this creates problems when working with services like SendGrid, which requires a static base URL in environment files (.env).

Why This Becomes an Issue
  • Preview deployments change the base URL, causing email API requests to fail.
  • Static URLs don’t exist in preview environments, making it difficult to configure email services.
  • Serverless functions (e.g., Netlify & Vercel) handle API requests dynamically, meaning your SendGrid API call might hit the wrong URL.

 

If not handled properly, emails will fail with 500 errors, and debugging becomes a nightmare.

Solution: Debugging & Fixing SendGrid API Calls in AI-Powered Dev Tools

Step 1: Implement Debug Logs for Email API Calls

To ensure successful email sending in environments like Replit, co.dev, loveable, and bolt.new, follow these structured debugging steps:

Why Console Logging is Not Enough

While console logging can help debug issues locally, it is not a reliable or safe method for tracking API requests in production or serverless environments.

  • Security Risk: Logging API requests in the console can expose sensitive data, including API keys and email payloads, making them vulnerable to exploitation.
  • Limited Visibility: Console logs disappear after a session ends, making it difficult to trace issues that occur in deployed environments.
  • No Centralized Record: When debugging serverless functions or preview environments, developers (Vibe Coders) need a persistent, accessible log rather than scattered console messages.

Instead, a structured debug log should be implemented to capture all API requests in a secure and centralized way.

Before fixing anything, you need visibility into what’s failing.

Implementation
  • Capture all API requests and responses related to emails.
  • Log request URLs, response statuses, and errors.
  • Display logs in an accessible debug panel.
AI Prompt

💡 “Generate a function that logs all API requests related to email sending. The function should capture request URLs, response statuses, and any errors in a structured, readable format for debugging. Additionally, create a page at /debug/api-logs where all logged API requests can be viewed in real-time.”

Step 2: Create a Dynamic URL Resolver for API Calls

Since preview environments create new URLs for each deployment, you need a way to determine the correct base URL dynamically. Without a consistent base URL, API calls can fail, leading to email-sending issues and webhook failures. The /debug/url-resolver page serves as a real-time diagnostic tool, displaying the resolved base URL and key environment details, such as whether the app is running locally, in preview, or in production. This visibility allows developers (Vibe Coders) to verify that their API calls are targeting the correct endpoint and helps troubleshoot potential mismatches before they impact functionality.
AI Prompt

💡 “Generate a function that dynamically determines the correct base URL based on the deployment environment (local, preview, production). It should support Netlify and Vercel, default to localhost when needed, and log the resolved URL for debugging. Additionally, create a page at /debug/url-resolver where the resolved URL can be viewed in real-time, along with environment details.”

Steps to Implement:

  1. Detect the environment:
    • Check if running locally, in preview, or in production.
    • Use environment variables like NEXT_PUBLIC_BASE_URL, VERCEL_URL, or NODE_ENV.

Implement a utility function:
 

const getBaseURL = () => {
    if (process.env.NEXT_PUBLIC_BASE_URL) {
        return process.env.NEXT_PUBLIC_BASE_URL;
    } else if (process.env.VERCEL_URL) {
        return `https://${process.env.VERCEL_URL}`;
    } else {
        return ‘http://localhost:3000’;
    }
};

2. Test with multiple functions and ensure URL resolution logs are visible.

Step 3: Automatically Adjust Base URLs in Preview Deployments

Now that we can track and test these specific changes, we can update the base URLs for seamless deployment and configure environment variables to always reference the latest preview URL. This step is essential because preview deployments generate a new URL each time, which can cause API requests to fail if they depend on a static base URL.

By automatically setting the latest preview URL in the environment, we ensure that all outgoing API calls including those for email sending are directed to the correct endpoint. This prevents broken workflows, failed webhooks, and unexpected issues in production or testing environments.

AI Prompt

💡 “Generate a script that automatically updates the base URL in environment variables during deployment on Netlify or Vercel. The script should detect the latest preview URL and set it dynamically using CLI tools.”

Netlify Example:

netlify env:set NEXT_PUBLIC_BASE_URL $(netlify url –json | jq -r ‘.url’)

Step 4: Iterate and Continuously Improve with AI Feedback

Debugging is not a one-time process; it’s an iterative cycle. The best way to refine API error handling is to constantly feed errors back to the AI tools and adjust the implementation accordingly. Additionally, developers (Vibe Coders) should ask AI-powered debugging assistants what they need in order to identify and resolve issues more effectively.

This step ensures that errors are not just logged but actively diagnosed and corrected using AI-driven insights.

Implementation:
  • Continuously log API errors and refine error handling based on AI suggestions.
  • Ask AI tools to analyze recurring failures and suggest improvements.
  • Implement auto-recovery mechanisms where possible.

Conclusion

By implementing structured debugging logs, dynamic URL resolution, and automatic preview URL handling, you can prevent email failures when working with AI-powered development tools. Platforms like Replit, co.dev, loveable, and bolt.new are powerful, but require extra handling when integrating services like SendGrid.

With the improved AI prompts included in this guide, you can leverage AI-powered coding assistants to implement these fixes more efficiently.

ABOUT THE AUTHOR
Cameron Becker

Is an MSc Digital Marketing student who consults with businesses and individuals across Africa, Europe, and the Middle East. He has 8+ years of experience in digital marketing and marketing automation.

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