Assess how content filter false positives affect developer productivity, workflow disruption, and tool adoption decisions. Designed for developer experience researchers and tooling teams seeking actionable improvement priorities from software practitioners.
What's Included
AI-Powered Questions
Intelligent follow-up questions based on responses
Automated Analysis
Real-time sentiment and insight detection
Smart Distribution
Target the right audience automatically
Detailed Reports
Comprehensive insights and recommendations
Template Overview
22
Questions
AI-Powered
Smart Analysis
Ready-to-Use
Launch in Minutes
This professionally designed survey template helps you gather valuable insights with intelligent question flow and automated analysis.
Sample Survey Items
Q1
Chat Message
Welcome! This survey explores your recent experiences with content filters and false positives in developer tools.
Your participation is voluntary, and you may stop at any time. There are no right or wrong answers—we are interested in your honest opinions. All responses are confidential and will be reported in aggregate only.
The survey takes approximately 5–7 minutes. Please answer based on the last 30 days and omit any sensitive or proprietary data.
Q2
Multiple Choice
In the last 30 days, have you used any developer tools that enforce content moderation or safety filters?
Yes, in the last 30 days
No, not in the last 30 days
Q3
Multiple Choice
Which types of developer tools with content filters have you used in the last 30 days? Select all that apply.
Rank the following improvements by how much they would reduce the impact of false positives. Place the most impactful improvement first.
Drag to order (top = most important)
Clearer policy definitions in tools
Better detection models (precision/recall tuning)
Use more context (file type, repo trust, role)
Faster and more transparent appeal or override process
Granular admin and user controls
Improved UI messaging and guidance
Q16
AI Interview
Based on your responses in this survey, please share any additional thoughts or experiences about false positives or content filter design in developer tools.
AI InterviewLength: 2Personality: [Object Object]Mode: Fast
Reference questions: 5
Q17
Dropdown
What is your primary role?
Backend developer
Frontend developer
Full-stack developer
DevOps/SRE
ML/AI engineer
Security engineer
Engineering manager
QA/Testing
Other
Q18
Dropdown
How many years of professional software development experience do you have?
Less than 1 year
1–3 years
4–6 years
7–10 years
11–15 years
16–20 years
More than 20 years
Q19
Dropdown
What is your organization size?
1 (just me)
2–10
11–50
51–200
201–1,000
1,001–5,000
5,001+
Q20
Dropdown
Where are you primarily located?
North America
Europe
Latin America
Asia
Africa
Oceania
Prefer not to say
Q21
Multiple Choice
Which programming languages do you use most often? Select all that apply.
JavaScript/TypeScript
Python
Java/Kotlin
C/C++
C#/.NET
Go
Ruby
Rust
Swift/Objective-C
PHP
SQL
Other
Q22
Chat Message
Thank you for your time. Your feedback will help improve content filter design in developer tools and reduce the impact of false positives on developer workflows.
Frequently Asked Questions
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AI interviews conduct adaptive conversations with respondents. The AI asks follow-up questions based on what the respondent says, probing for clarity and depth. You control the personality, tone, model (Haiku, Sonnet, or Opus), and question mode (fixed count, AI decides when to stop, or time-based).
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