We evaluate reasoning, not just output
Final code alone is no longer enough. Dipin reads how candidates define, test, and refine ideas while working with AI.
What Dipin Evaluates
What Dipin Evaluates
Dipin does not evaluate only final code. We evaluate reasoning, verification, and decision quality shown while collaborating with AI.
We transform AI collaboration into measurable signals
Prompts, revisions, alternatives, and self-verification are reconstructed into one evidence-backed decision timeline.
We produce trustable hiring evidence
Instead of opaque scoring, we deliver explainable forensic insight that hiring teams can actually use.
Six dimensions we evaluate
Spec Compliance
How accurately requirements are interpreted and implemented
Data Modeling & Integrity
Quality of domain modeling and data integrity decisions
Reliability & Safety
Resilience and guardrails across failure scenarios
Maintainability & Readability
Code clarity and maintainability for team collaboration
Efficiency & Performance
Performance and cost-aware optimization judgment
AI Synergy
Critical and productive use of AI, not blind dependence
What Dipin reads from your process
- How problem framing evolved from vague to concrete
- Whether AI suggestions were accepted or rejected with rationale
- How strategy shifted after failed attempts
- How risks were managed through testing and validation
Experience it yourself
Start with Quick Demo to experience the framework, then request a demo meeting for team adoption.