This article will guide you on how to create an API developers survey about error handling and debugging—fast and effortlessly. With Specific, you can build a smart survey in seconds, perfectly suited for developer feedback.
Steps to create a survey for API developers about error handling and debugging
If you want to save time, just generate a survey with Specific—it’s that easy.
Tell what survey you want.
Done.
You honestly don’t need to read any further. AI takes care of the heavy lifting, building the survey using expert-level knowledge. It doesn’t just stop at basic questions—it intelligently asks follow-up questions so you get deeper, actionable insights, saving you loads of time compared to any manual approach.
Why collecting feedback on error handling and debugging matters
Surveys targeting API developers on error handling and debugging aren’t just a nice-to-have—they’re a core strategy for improving product quality and developer happiness. Here’s the reality: 43% of app developers spend between 10% and 25% of their time debugging application errors discovered in production, pulling them away from building new features and slowing down progress [1].
If you’re not running these surveys, you’re missing out on discovering what slows your team down the most.
Without structured feedback, you’re flying blind on where your error handling falls short and where your debugging process causes friction.
Getting these insights directly from your API developers means you can prioritize fixes and improvements with real impact.
The importance of API developer recognition surveys and the benefits of developer feedback can’t be overstated. With 38% of developers dedicating up to a quarter of their time to fixing bugs [2], understanding their pain points around error handling is a shortcut to smarter development cycles and fewer production headaches.
What makes a good survey on error handling and debugging
Certain best practices truly matter—especially when you want high-quality and actionable responses from API developers. Your survey questions should:
Be clear, unbiased, and concise
Encourage open, honest sharing by sounding conversational (not robotic)
Avoid jargon overload while still being technical enough for the audience
Directly relate to daily developer pain points and real use cases
Here’s a quick guide for visual comparison:
Bad Practices | Good Practices |
|---|---|
Vague: “What do you think about bugs?” | Specific: “Which error types do you spend the most time debugging?” |
Leading: “You find our error handling great, right?” | Neutral: “How would you rate our error handling in your recent projects?” |
Passive: “Bugs are fixed, yes?” | Active: “Describe the process you follow for fixing bugs after they’re found in production.” |
Ultimately, the real measure of a successful survey is the quantity and the quality of responses you get. We want both—enough responses for robust insights, and deep, thoughtful answers to move your team forward.
Question types and examples for API developers survey about error handling and debugging
Not all questions are created equal; a mix of types drives both response rate and insight depth. If you want to dig deeper, you’ll find more examples and tips in our best questions for API developers survey about error handling and debugging guide.
Open-ended questions give respondents space to explain, vent, or share insight you might not expect. They’re perfect when you want stories or in-depth feedback. Here are two examples:
What’s the biggest frustration you face when debugging API errors?
Describe a recent experience where error handling in our platform saved you time or caused a delay.
Single-select multiple-choice questions streamline analysis and are best when you want to measure frequency or preferences. For example:
Which of these best describes how you usually discover errors in production?
Automated monitoring alert
User-reported issue
Manual QA checks
Other
NPS (Net Promoter Score) question uncovers sentiment at a glance and can serve as a loyalty metric. You can generate a custom NPS survey for API developers on this topic in just one click. Example:
On a scale of 0 to 10, how likely are you to recommend our error handling and debugging tools to a fellow developer?
Followup questions to uncover "the why" aren’t just fluff—they’re crucial. Use them when you want context and reasons, not just surface answers. For instance, if someone selects “User-reported issue” from the example above, follow up with:
What usually makes these errors hard to detect before users report them?
This approach digs into underlying causes rather than just collecting stats. If you’d like a full rundown on crafting expert-level prompts, our in-depth article can help you go further.
What is a conversational survey
A conversational survey is more than just a list of questions—it’s an interactive chat that responds to each answer, probing when needed and moving naturally to the next topic. With AI, you’re not just automating question delivery; you’re leveling up the entire feedback experience.
Manual Surveys | AI-generated Conversational Surveys |
|---|---|
Static, can feel cold or tedious | Dynamic, feels like a genuine conversation |
Requires manual QA and tweaking | Uses expert knowledge to structure and phrase each question |
No real-time probing for more info | Smart follow-ups push for clarity and context |
Often lower response rates | Higher engagement thanks to interactivity |
Why use AI for API developers surveys? The difference is clear: using an AI survey generator lets you move extremely fast, while maintaining quality and getting conversational, context-rich insights you’d normally only find in interviews. With tools like Specific, building AI survey examples is as easy as typing your goal, whether you need a full set of technical questions or a hyper-focused probe on error handling. The conversational survey format stands out for developer audiences because it matches their expectation for quick, targeted interactions (not a boring old form).
Specific offers best-in-class user experience for conversational surveys—making both creation and feedback collection genuinely smooth and rewarding. Curious what it’s like? Check out our guide on how to create a survey using AI.
The power of follow-up questions
Dynamic follow-up questions are a game-changer in developer surveys. Instead of getting stuck with generic or unclear responses, Specific’s AI asks real-time follow-ups—just like a skilled researcher—to dig deeper and clarify answers, unlocking insights most surveys miss. These automatic AI follow-ups don’t just save your team time (no more chasing via email!)—they help every response feel like a real discovery session that adapts on the fly.
API developer: “Sometimes bugs slip into production.”
AI follow-up: “Can you share what typically makes these bugs hard to catch in your current workflow?”
How many followups to ask? In most cases, 2-3 targeted followups per open-ended question uncover all the context you need. The right survey builder lets you tune this, so respondents aren’t overwhelmed. In Specific, you can choose how many follow-ups before moving to the next question—keeping it snappy and insightful.
This makes it a conversational survey: Rather than a bland form, you get a real conversation—one that adapts and goes deeper where it matters, so API developers can truly share their struggles and breakthrough moments.
Analyze responses simply with AI: Even if you end up with loads of open-text answers, AI makes it easy to analyze survey responses from API developers. You can summarize, theme, and dig for patterns with the efficiency only AI delivers.
Automated followups are still a new concept—give it a try by generating a survey and see how the process feels (and how much richer the responses are!).
See this error handling and debugging survey example now
Create your own survey for API developers—get high-quality insights, drive better error handling initiatives, and see the power of AI-driven, conversational feedback today.