Stop hiring the wrong developers. Use Data instead.
Most engineering teams don't fail because of a lack of technical skill—they fail because of misalignment in how they work, communicate, and solve problems.
In this video, I break down GitSyntropy, a multi-agent AI system I built that uses real GitHub behavioral data and psychometric profiling to score team compatibility and simulate the impact of new hires. No more "vibes-based" hiring. We’re using data to predict human friction before it happens.
🌟 Key Features:
Multi-Agent Pipeline: Built with LangGraph and Claude 3.5 to analyze commit patterns, PR activity, and chronotypes.
Monte Carlo Hire Simulations: Predict how a specific candidate will change your team's "Health Score" across 8 behavioral dimensions.
Async Optimization: Automatically detects peak-hour gaps and recommends working models (e.g., "Shift to async-first").
Adaptive Psychometrics: A Computerized Adaptive Testing (CAT) workspace that builds a behavioral profile faster than traditional surveys.
The Tech Stack:
Backend: FastAPI (Async), SQLAlchemy, LangGraph (Multi-agent orchestration).
Frontend: Astro (Islands architecture), React, Tailwind CSS, Framer Motion.
Database: Supabase (PostgreSQL) + asyncpg.
AI: Anthropic Claude (Streaming synthesis), WebSocket-based progress tracking.