Engineering Self-Evaluation Generator

The Challenge

Performance review season means engineers scrambling to remember 6 months of contributions. Digging through PRs, Jira tickets, and Slack threads to build a compelling self-review takes hours.

The AI Desk Solution

AI Desk analyzes your contributions across systems and generates a structured self-evaluation with evidence.

The Workflow

Step 1: Define Review Period

Input: "Self-eval for H2 2025"
Sources: GitHub, Jira, Slack, Google Docs

Step 2: Contribution Analysis

• PRs merged and reviewed
• Projects delivered
• Technical leadership moments
• Collaboration patterns

Step 3: Structured Output

📝 Self-Evaluation: H2 2025

PROJECT HIGHLIGHTS

Search Performance Optimization
├── Led front-end performance audit
├── Reduced load time by 42%
├── PRs: 23 merged, 45 reviewed
└── Impact: Improved user satisfaction scores

TECHNICAL CONTRIBUTIONS
├── Avg PRs/week: 8.5
├── Code reviews: 156
├── Design docs authored: 3
└── Incidents resolved: 7

LEADERSHIP & MENTORSHIP
├── Onboarded 2 new engineers
├── Led architecture review for auth system
└── Created performance testing playbook

KEY METRICS
├── Lines of code: ~12,000
├── Test coverage improved: +8%
└── Bug escape rate: 2% (team avg: 5%)

Value Proposition

• Time Saved: 3 hours per review cycle
• Evidence-Based: Real data, not memory
• Comprehensive: Nothing forgotten