Production Projects
AI systems built with real constraints — real metrics, real costs, real results.
Featured Projects
GitHub Copilot Agent Pipelines
FeaturedSeven specialized Copilot agents that form a structured development workflow for a legacy Servoy enterprise application with 10,000+ functions, 1,000+ files, and 22 modules. Neo4j graph-powered code intelligence, cross-model orchestration, and a self-improving knowledge loop where every code review makes every agent smarter.
Ask Your Database Anything: The Metabase Version
FeaturedAn AI-powered system that converts plain English questions into complete six-card Metabase dashboards in under 30 seconds, 100% SQL success rate on a 90.5-million-row production database, embeddable in any React application via the Metabase SDK.
Ask Your Database Anything: Native React Dashboards
FeaturedType a question, get a six-card dashboard rendered with native React charts in under 30 seconds, no Metabase, no Java, no BI server. 100% SQL success rate against a 90.5-million-row production database.
RAG Document Assistant: From Single-Purpose Chatbot to Multi-Repository Document Platform
FeaturedA RAG-based document assistant that ingests 51,000+ chunks across 4 file formats, answers natural language questions in under 3 seconds using hybrid search with cross-encoder re-ranking, and required zero frontend changes to transform from a single-purpose chatbot into a general-purpose document platform.
Obsidian Notes Pipeline: AI-Powered Knowledge Management
FeaturedA full-stack RAG application that transforms YouTube videos into interconnected Obsidian notes -- 1,000+ notes, 2,757 auto-generated links, 5,000 searchable chunks, and a chatbot with 2.5s latency, all for $1.50.
Job Search Agent: AI-Powered Career Pipeline
FeaturedAn automated job search system that monitors 1,975 companies across 11 ATS platforms, processes 58,807 jobs weekly through a 6-phase AI pipeline, and delivers 311 qualified matches for $5.04 per run.
Adversarial Agent Testing
FeaturedAI agents that attack each other to find vulnerabilities. Red Team probes, Blue Team defends, a Referee scores both -- all using Claude Code with worktree isolation. Two rounds of live exercises against a real target drove ASR from 65% CRITICAL to 47% HIGH, with a regression wave proving patches hold at 20% and an escalation wave exposing architectural gaps at 85.7%.
Claude Code Bootstrap Framework
FeaturedAn agent swarm that builds agent swarms. A 12-step pipeline where Claude Code agents analyze any codebase and generate complete Claude Code infrastructure -- agent teams, hooks, skills, and slash commands -- in 30-55 minutes. Three production migrations validated. The second was harder but faster.