Best questions for api developers survey about error handling and debugging

Here are some of the best questions for an API developers survey about error handling and debugging, along with tips on how to craft them. You can build an in-depth, conversational survey in seconds using Specific’s AI survey generator built for this audience and topic.

Best open-ended questions for error handling and debugging surveys

Open-ended questions invite API developers to share nuanced experiences, giving you context that’s lost with checkboxes. They’re essential when you want to uncover challenges, learn about workflows, or explore pain points you didn’t anticipate. We love starting surveys with these to uncover genuine insights that drive real improvement.

1. Can you describe your most recent challenge with API error handling?

2. What’s your typical process for debugging errors returned by a third-party API?

3. Tell us about a confusing or misleading error message you’ve encountered recently.

4. How do you usually identify the root cause of an API failure?

5. What resources or tools do you rely on most for debugging?

6. Share an example where poor documentation made error handling harder.

7. What frustrates you the most about current API error responses?

8. Describe a time when misunderstanding an HTTP status code led to a bug or delay.

9. If you could change one thing about how APIs handle errors, what would it be?

10. How has the use (or lack) of AI tooling impacted your debugging process?

Open-ended questions catch the specific situations that turn into costly production fires, and they give us real-world stories we can act on. Given that up to 75% of developers report issues with API error handling, often citing inconsistent messages and inadequate docs as the big offenders, these questions are gold for capturing actionable feedback. [1]

Single-select multiple-choice questions for API debugging surveys

Single-select multiple-choice questions work best when you want to quantify responses or gently ease people into a deeper conversation. They also lower friction for busy developers—sometimes it’s easier to pick an option than type out a whole explanation. Use these when you want clean data that’s simple to analyze, or when you plan to follow up based on their choice.

Question: What’s your biggest obstacle when debugging API errors?

• Lack of clear error messages

• Poor documentation

• Difficulty reproducing errors

• Understanding HTTP status codes

• Other

Question: How do you usually handle unrecognized API exceptions?

• Implement a generic catch block

• Log and escalate the issue

• Retry the request automatically

• Consult community forums or docs

Question: Have you used any AI-powered tools to assist with API debugging?

• Frequently

• Occasionally

• Not yet, but interested

• No, and not interested

When to follow up with "why?" It’s essential to ask “why?” after a dev selects a particular pain point—it invites them to elaborate. For instance, if someone picks “Lack of clear error messages,” a smart follow-up like, “Can you share a recent error message that was unclear to you?” gets you specifics you can actually use to improve your API. This approach is also validated by the 29% of developers who report negative debugging experiences in post-release environments, where clarity is crucial. [3]

When and why to add the "Other" choice? Always include an “Other” option when not all possible answers are obvious. This opens the door for responses and follow-ups you’d never anticipate, allowing unexpected insights to surface—maybe there’s a workflow pain point you weren’t even aware existed.

NPS question for API developer experience

The Net Promoter Score (NPS) isn’t just for customer-facing products—it works beautifully for internal tools and APIs, too. By asking, “How likely are you to recommend our API error handling and debugging experience to a fellow developer?” on a 0–10 scale, you measure overall satisfaction and spot both your biggest fans and most frustrated detractors. With developer experience for debugging split—53% positive pre-release, but 29% negative in production [3]—the NPS lens helps you prioritize improvements where they matter most. You can instantly generate a tailored NPS survey using the Specific NPS survey builder for API debugging.

The power of follow-up questions

Follow-ups are where the magic happens. Instead of settling for vague responses, smart surveys ask clarifying questions in the moment—producing deeper insights than any spreadsheet, and transforming “meh” data into stories you can act on. In our experience, automated AI follow-up questions are a game changer for technical surveys like this.

Specific’s platform uses AI to generate sharp follow-ups based on the developer’s answer, dynamically probing for full context in a way that feels natural. This doesn’t just save time (no more chasing respondents over email), it makes the entire process conversational and engaging—exactly what busy API developers appreciate.

• API Developer: “I struggle with error messages.”

• AI follow-up: “Can you share a recent example of an error message you found confusing?”

How many followups to ask? Typically, 2-3 well-timed follow-ups give you the details you need, but you can always configure the survey to let respondents skip ahead once you have the key info. Specific lets you set the intensity and maximum depth so you control the conversation’s flow—no fatigue, just insight.

This makes it a conversational survey: The dynamic, real-time probing makes your data collection feel like an actual chat—not a boring form—keeping developers engaged all the way through.

AI response analysis, rich insights, easy review: Thanks to modern AI, analyzing even hundreds of nuanced, text-heavy responses is simple. Here’s how AI survey response analysis makes sense of developer feedback—no more hours spent coding answers or guessing trends.

Automated follow-ups are still new in survey workflows—try generating a survey with Specific and see the difference: you’ll instantly get richer stories and actionable input, not just shallow statistics.

Prompts for using ChatGPT or GPTs to generate better survey questions

If you’d rather draft your own API developer survey about error handling and debugging (or want to go deeper), prompts for ChatGPT or other GPTs are a great starting point. Here’s a simple but effective way to get results:

Start by asking:

Suggest 10 open-ended questions for API developers survey about error handling and debugging.

You’ll get even better output if you provide context—such as your role, what kind of API you manage, your goals, or common pain points your team faces. For example:

I’m a product manager for a SaaS featuring a REST API. Our customers often report trouble handling ambiguous errors and struggle with debugging in production—help me generate 10 open-ended survey questions to diagnose their main pain points more precisely.

To organize your questions, go further:

Look at the questions and categorize them. Output categories with the questions under them.

From there, scan the categories and pinpoint areas where you want to dive deeper. Then prompt:

Generate 10 questions for categories “error documentation” and “AI-powered debugging tools”.

This approach rapidly gives you a structured, relevant survey, and—much like with Specific’s AI survey builder—helps you home in on the feedback that matters most.

What is a conversational survey for API developers?

A conversational survey approaches respondents like a real-time chat, instead of a static form. Each question adapts based on the developer’s previous answers, making the process more engaging—and, crucially, surfacing richer, actionable details than traditional surveys. AI survey generation is fundamentally different, and better, than manual survey creation:

Why use AI for API developers surveys? AI’s flexibility means you no longer settle for mediocre, “one-size-fits-all” surveys. You get conversation, not interrogation—and with Specific, the experience is first-in-class for both survey creators and developer respondents. Curious how to do it? Here’s a step-by-step guide to creating your own conversational API developer survey.

When you use a conversational survey powered by AI, you multiply your ability to collect, understand, and act on developer feedback—at scale, with no extra legwork.

See this error handling and debugging survey example now

Get started with conversational surveys that drive real API improvements. Experience Specific’s AI-powered approach—capture rich stories, clarify issues in real time, and see what’s possible when developers actually want to participate in your survey.