Developer Survey: AI, Data Governance, and Secure Collaboration in Modern Workflows

A short, anonymous survey for developers and technical professionals across industries. We’re exploring common patterns, challenges, and opportunities when working with:

• Sensitive data

• Data structure and transformation

• External APIs and integrations

• Emerging tools like AI and workflow automation

1. Which of the following best describes your work focus?

Backend engineering

Frontend/web development

DevOps / Platform engineering

Security / Privacy

Product / Workflow automation

2. What types of sensitive data do you regularly interact with (or build systems around)?

Customer/user data (e.g., name, email, identifiers)

Financial data (e.g., transactions, balances)

Personally Identifiable Information (PII)

Healthcare or medical data (e.g., patient record, labs)

Internal documents or communications (e.g., contracts, emails)

Third-party vendor or partner data

Training or analytics datasets

3. When sharing data with external tools or vendors, how is trust and security typically managed?

We avoid sharing sensitive data externally

Data is manually filtered or anonymized

Data is masked/redacted using internal logic

RBAC or scoped API keys are used

We use data clean rooms or sandboxed tools

4. How is access to sensitive data managed internally?

(select all that apply)

Role-based access control (RBAC)

Attribute-based access control (ABAC)

API key scoping / OAuth permissions

Masking or redaction at the application level

Clean rooms or isolated environments

Manual rules / custom logic

Not applicable to my role

Prefer not to Say/ Cannot Say

5. Have you ever needed different levels of data visibility depending on the recipient?

Yes — some systems/tools only see partial data

Yes — visibility depends on user or team

No — access is uniform

6. Has data governance (e.g., policy setup, masking, approvals) ever delayed your projects?

Frequently — adds days/weeks to timelines

Occasionally — some added friction

Rarely — not a major blocker

If a tool could automatically control what data is visible based on context (who/what is accessing it), what would make you trust it?

(Free response or multiple choice)

Simulation/sandbox mode to preview behavior

Immutable audit logs

Explainable redaction/rehydration logic

Support for version control / rollbacks

Integration into existing APIs or workflows

None of the above (please specify)

8. In what scenarios would automatic, contextual data masking be helpful in your work?

(Examples: AI agents, automation workflows, plugin ecosystems, etc.)

(Free response)

Final (Optional): If you’re curious about what we’re laying the foundation for — and how it could unlock the next leap in AI, data, governance, and secure collaboration — drop your email below. We’d love to share more when the time is right.