Stop debugging AI-generated code blind. See the exact validation framework we use internally—a context-aware system that catches the subtle bugs that look correct but break under real-world load. Works WITH your judgment, not against it.
Free 60-minute technical session. Toolkit delivered instantly upon registration. Start validating your code today. MIT-licensed, open source. Ship knowing it works—not hoping it does.
Save 40+ hours of debugging per month. Catch failures in 12-29ms instead of hours. See exactly how.
Webinar starts in:
Thursday, December 4, 2025
11:00 AM PST / 2:00 PM EST
Why free? We want you to experience the validation system before asking for anything. Zero risk for you. The methodology is open source—see exactly how it works, use it yourself, improve it if you can.
// phantom-detector.ts
export const detectPhantomAPI = async (
code: string
): Promise<PhantomResult[]> => {
const imports = extractImports(code);
const phantoms = imports.filter(
i => !existsInRegistry(i)
);
return phantoms.map(formatResult);
};12 TypeScript scripts included. Copy-paste ready. Fully commented and tested. Includes phantom API detection, security scanning, and type inference.
All scripts are MIT licensed and copy-paste ready
See the exact validation framework we use internally, including live demos and real code examples
What percentage of AI-generated code actually works? We tested 1,200+ functions across Claude, GPT-4, and Copilot. Results: 40-60% contain phantom features, 27.25% have security vulnerabilities, 15% fail silently with edge cases. You'll see specific examples of each failure type.
Static Analysis: AST parsing for hallucinated imports, dependency verification, type inference—with context awareness across your codebase. Runtime Verification: Automated test generation, property-based testing, mutation testing. Security Scanning: OWASP Top 10 detection, dependency vulnerability checking, secret detection. Each step respects your judgment and learns from feedback.
How to add validation to your existing pipeline: GitHub Actions workflow (copy-paste ready), pre-commit hooks for local validation, PR check integration, Slack/Discord notifications. Plus: How to handle false positives without slowing down, and how the system learns from your exceptions.
Bring your worst AI-generated code. We'll validate it live and discuss framework-specific quirks, when validation adds friction vs. value, the 2.2% of failures we still miss (and why), and roadmap for improvement.
Most validation tools treat your code as isolated snippets. This framework understands context, learns from your feedback, and respects your judgment.
The framework analyzes your entire codebase structure, not just isolated files. It understands how modules relate, tracks dependencies, and identifies issues that only appear in context.
When you mark something as a false positive or correct a detection, the framework learns. You can document exceptions, improve patterns, and the system gets better at understanding YOUR codebase.
The framework flags potential issues—you decide what to fix. No auto-fixes that break your code. No assumptions about your intent. Just clear, actionable information.
This is a new deep-dive format. Be among the first engineers to experience it and help us improve. Your feedback shapes the methodology.
You can audit every check, see the test corpus, and verify our accuracy claims yourself. We're not asking for trust—we're showing our work.
What you'll get immediately after registration:
Star it, fork it, improve it. No license restrictions.
Copy-paste ready implementations. Fully commented and tested. Includes phantom API detection, security scanning, and type inference. Delivered instantly upon registration.
Ready-to-use CI/CD integration. Pre-commit hooks included. Works with React, Vue, Next.js, FastAPI, Express. Access immediately after opt-in.
Test results across 847 AI-generated functions. Shows what we caught, what we missed, and why. Includes edge case documentation. Available right now.
Complete technical documentation explaining how each validation step works, why it matters, and how to extend it. Instant access via email.
Actionable checklist for adding validation to your existing stack. Includes troubleshooting guide. Included in instant delivery.
Currently TypeScript/JavaScript (full support), Python (full support), and Go (basic support). Works with React, Vue, Next.js, FastAPI, Express. Framework-specific patterns documented.
Yes. MIT licensed. You can audit every check, see the test corpus, verify our accuracy claims yourself. GitHub repository included in instant delivery.
We've tested 1,200+ AI-generated functions across Claude, GPT-4, and Copilot. Results: 97.8% accuracy in catching production failures. Full methodology report included.
The webinar is technical and assumes familiarity with code. However, the validation scripts are copy-paste ready, and the methodology report includes plain-English explanations.
Yes. The validation framework is language-agnostic. It works with any AI code generation tool. We'll show examples from Cursor, GitHub Copilot, and ChatGPT during the webinar.
Immediately. You get instant access to the toolkit upon registration. Clone the repo, follow the 15-step checklist, and integrate into your CI/CD pipeline.
Recording available to all registrants. However, live attendees get bonus Q&A access and can bring their code for live validation.
No. The validation toolkit is MIT licensed and free forever. The webinar is educational—no upsell, no hidden costs, no sales calls.
Get your validation toolkit above. Join the 60-minute technical deep-dive. Free, open source, MIT licensed.