Risks of Vibecoding

Why This Section Matters

Vibecoding democratises software development, but it also introduces risks that traditional developers have spent decades learning to mitigate. As a legal professional, you already understand risk management. Apply that same rigour here.

This isn't meant to discourage you. It's meant to make you a responsible vibecoder.

Technical Risks

1. Code You Don't Understand

The Risk: AI generates code that works but you can't explain why. When it breaks, you can't fix it.

Why It Matters for Legal Tech: A document generator that produces incorrect output could result in professional liability. If you can't diagnose why it happened, you can't prevent it recurring.

Mitigation:

Ask the AI to explain what the code does in plain language
Request comments in the code
Test extensively before any real-world use
Have a developer review critical applications

2. AI Hallucinations

The Risk: Large language models can generate plausible-looking code that is fundamentally wrong. The AI may:

Invent function names that don't exist
Use outdated syntax or deprecated methods
Create logic that appears correct but produces wrong results
Reference libraries or APIs incorrectly

Why It Matters for Legal Tech: A statute citation tool that confidently generates fake case references is worse than no tool at all.

Mitigation:

Verify outputs against known correct results
Test with edge cases
Never assume generated code is correct
Use AI models with larger context windows and more recent training data

3. Security Vulnerabilities

The Risk: AI-generated code may contain security flaws including:

SQL injection vulnerabilities
Cross-site scripting (XSS)
Authentication bypasses
Data exposure
Insecure data storage
Hard-coded credentials

Why It Matters for Legal Tech: Legal data is among the most sensitive. A security breach could expose privileged communications, violate data protection laws, and destroy client trust.

Mitigation:

Never deploy vibecoded applications to production without security review
Use established authentication providers rather than building your own
Never store sensitive data in vibecoded applications
Keep applications internal/sandboxed where possible
Assume every input could be malicious

4. Dependency and Supply Chain Risks

The Risk: AI may incorporate third-party libraries or packages that:

Contain their own vulnerabilities
Are no longer maintained
Have licensing restrictions
Could be compromised in future updates

Why It Matters for Legal Tech: Your application's security is only as strong as its weakest dependency.

Mitigation:

Understand what packages are being used
Prefer well-maintained, widely-used libraries
Lock dependency versions
Audit dependencies for known vulnerabilities

5. Scalability and Performance

The Risk: Code that works for 10 users may fail catastrophically at 1,000. AI often generates "happy path" code that doesn't handle:

High concurrent usage
Large data volumes
Network failures
Database timeouts

Why It Matters for Legal Tech: An e-discovery tool that crashes mid-review could lose critical work or corrupt data.

Mitigation:

Load test before any significant deployment
Implement proper error handling
Use managed services that handle scaling
Design for failure (save frequently, enable recovery)

Professional and Ethical Risks

6. Confidentiality and Privilege

The Risk: Using vibecoding tools with client data may compromise:

Attorney-client privilege: Information shared with AI providers may waive privilege
Confidentiality obligations: AI training data practices vary by provider
Work product protection: Generated outputs may not be protected

Why It Matters for Legal Tech: This is an existential risk.

Mitigation:

NEVER input confidential client data into vibecoding tools
Use synthetic or anonymised data for development
Review AI provider terms regarding data retention and training
Consider enterprise AI solutions with enhanced privacy commitments
Consult your bar's ethics guidance on AI use

7. Competence and Supervision

The Risk: Bar rules require lawyers to provide competent representation. Using technology you don't understand may breach this duty.

Lawyers must:

Understand AI capabilities and limitations
Maintain competence in technology affecting their practice
Supervise AI use as they would any other tool

Why It Matters for Legal Tech: "The AI made an error" is not a defence to malpractice.

Mitigation:

Understand how your tools work at a conceptual level
Verify all outputs before relying on them
Maintain human oversight of AI-assisted work
Document your review process

8. Unauthorised Practice of Law

The Risk: Legal tech tools that provide legal advice or draft legal documents could:

Constitute unauthorised practice if used without lawyer supervision
Expose users to reliance on incorrect information
Create liability for the tool creator

Why It Matters for Legal Tech: Even well-intentioned tools can cross ethical lines.

Mitigation:

Include clear disclaimers that tools don't provide legal advice
Design tools to assist lawyers, not replace them
Require lawyer review of outputs
Consider jurisdiction-specific UPL rules

9. Bias and Fairness

The Risk: AI models reflect biases in their training data. Legal tech tools may:

Produce biased risk assessments
Favour certain outcomes based on demographic factors
Perpetuate historical inequities in the legal system

Why It Matters for Legal Tech: Biased tools in criminal justice, lending, employment, or other areas can cause real harm to real people.

Mitigation:

Test tools across diverse scenarios
Be sceptical of AI risk scoring
Maintain human decision-making for consequential matters
Monitor outcomes for disparate impact

Business and Operational Risks

10. Vendor Lock-In and Dependency

The Risk: Your application may depend on:

Specific AI providers whose terms or pricing may change
Platforms that could shut down
APIs that may be deprecated

Why It Matters for Legal Tech: Client systems need long-term stability.

Mitigation:

Understand your dependencies
Have contingency plans
Export and backup data regularly
Avoid single points of failure

11. Intellectual Property Uncertainty

The Risk: Questions remain about:

Who owns AI-generated code
Whether AI output can be copyrighted
Liability for AI that reproduces copyrighted material

Why It Matters for Legal Tech: Commercialising AI-generated tools has unresolved IP implications.

Mitigation:

Review AI provider terms regarding output ownership
Document your creative contributions
Consider IP insurance for commercial products
Stay informed as law evolves

12. Maintenance Burden

The Risk: Software requires ongoing maintenance:

Security patches
Dependency updates
Bug fixes
Feature additions

If you built it quickly without understanding, maintaining it will be difficult.

Why It Matters for Legal Tech: Abandoned tools become security liabilities.

Mitigation:

Document what you build
Plan for ongoing maintenance
Consider whether you'll maintain or sunset each tool
Don't create tools you can't support

Risk Assessment Framework

Before building or deploying any vibecoded legal tech, ask:

Impact Assessment

What's the worst case if this tool fails?
Who could be harmed and how?
Is this tool handling sensitive data?
What are the professional responsibility implications?

Technical Assessment

Have I tested this thoroughly?
Has anyone with technical expertise reviewed it?
What dependencies does it have?
How will it be maintained?

Deployment Decision

Is this for internal use only or client-facing?
Am I treating this as experimental or production?
What disclaimers and limitations are appropriate?
Who approved this use?

The Bottom Line

Vibecoding is transformative, but it's not a shortcut to production-ready software. Every tool you build should be treated as a prototype until proven otherwise through:

Rigorous testing
Security review
Human oversight
Appropriate use limitations

The lawyers who will thrive in the vibecoding era are those who combine its creative power with professional responsibility and healthy scepticism.