The Art of Debugging: Fixing Bugs in No-Code and AI-Generated Apps

If you've built an app with tools like Bubble, Glide, Adalo, or integrated AI logic with tools like Make or Zapier, you've likely encountered this scenario: something’s off. Maybe a form doesn't submit, a database query fails silently, or an AI-generated workflow misfires. Debugging in no-code platforms feels different than in traditional development, but it's just as crucial.

Here’s how to approach debugging with confidence in your no-code and AI stack.

1. Understand the Execution Flow

No-code platforms often abstract logic behind visual workflows. Before you start patching things, trace the entire execution path:

• What triggers your workflow?
• What happens step-by-step?
• Which external services (APIs, GPT outputs, databases) are involved?

Use built-in features like Bubble's step-by-step debugger, Make’s execution logs, or console outputs where available to map the sequence of events.

2. Isolate the Problem

One of the fastest ways to resolve a bug is to reduce your app into a minimal reproducible example. Try:

• Duplicating the app or page and stripping it down.
• Re-running only the problematic workflow with test data.
• Replacing AI-generated components temporarily with static logic to see if the error persists.

Isolation can help determine whether the issue lies in user input, logic design, or something else entirely.

3. Test AI Inputs Rigorously

When your logic involves prompting AI models (e.g., GPT or Claude), ensure clarity and consistency in your prompt structure. AI-generated bugs often stem from vague or inconsistent instructions.

Tips:
- Use structured output formats like JSON or Markdown when expecting results from LLMs.
- Implement fallback logic for incomplete or invalid AI responses.
- Maintain a test log of prompts and corresponding outputs during development.

4. Log Everything

Many platforms now offer internal logging or support plugins that make debugging easier.

• In tools like Bubble, use custom logging workflows.
• For Zapier/Make, enable execution history and monitor step results.
• Even in spreadsheets or databases, create audit columns for inputs and outputs over time.

Logging is your insight into app behavior when direct debugging tools are limited.

5. Ask the Community with Context

No-code forums (like the /r/nocode subreddit), Discord groups, and platform-specific communities are gold mines. But when asking for help:

• Provide screenshots or screen recordings.
• Describe what you expected vs. what actually happened.
• Share sanitized versions of your setup when possible.

The more context you give, the better the help you’ll receive, and others will benefit from your clarity.

6. Turn Bugs into Systemized Tests

Once you squash a tricky bug, don’t just move on, turn it into a test case or checklist for future changes.

• Use checklists before pushing updates that involve sensitive workflows.
• Schedule periodic tests of mission-critical app components, especially those dependent on 3rd-party APIs or AI logic.

In no-code, proactive testing isn't just for big teams, it's how solo makers scale reliably.

Bonus Tip: Embrace Breakpoints and ‘Preview As’ Features

Many no-code tools now allow simulated environments:

• Bubble’s ‘Preview as user’ helps reproduce permission-related issues.
• Adalo and Glide offer role-based view testing.

These features prevent the classic “works on my account” bug chase and save countless hours.

Debugging in the no-code + AI era might lack traditional breakpoints and console logs, but with the right mindset and tools, it's absolutely manageable. Every bug fixed not only improves your app, it levels you up as a creator.

Remember: the best builders aren’t the ones who avoid bugs; they’re the ones who know how to fix them fast, learn from the process, and future-proof the app moving forward.