Senior Technology Leader | 25 Years Experience | CTO / Fractional CTO / Senior C# Developer
Building scalable solutions and leading high-performance teams
I'm a senior technology leader with 25 years of development experience, 15+ years building scalable applications and 7+ years leading international development teams. I transform technology organizations from startup-phase to enterprise-grade while achieving market leadership positions.
My approach: Remove bottlenecks and dependencies for sustainable growth—both in code architecture and team dynamics.
- Senior C# Developer positions
- Technical Architecture consulting
Focus Areas: FinTech, RegTech, Enterprise SaaS, Start-ups needing technical foundation, AI/ML applications
Location: Amsterdam area (Weesp, Naarden, Almere, Bussum, Hilversum) or remote/hybrid
AI-powered energy management for ME/CFS patients and cancer survivors with mitochondrial dysfunction
(Personal Energy Monitor, Predictor & Analytics Logger)
Tech Stack: Rust, Deno, Burn (ML), DuckDB-WASM, LSTM/TFT models
What it does: Privacy-first health analytics that discovers personal crash patterns from wearable data. Predicts Post-Exertional Malaise (PEM) risk using HRV, heart rate, sleep, and activity metrics—helping users avoid energy crashes that can last days or weeks.
Who it helps:
- ME/CFS patients - Manage energy envelopes and prevent debilitating crashes
- Cancer survivors - Navigate recovery with mitochondrial damage from chemotherapy/radiation
- Long COVID patients - Understand post-viral energy patterns and pacing
Business Value: Personalized ML models identify individual warning signs and safe activity levels. All data processed locally in the browser for complete privacy—no health data leaves the user's device.
Self-improving multi-agent orchestration system with NER and knowledge graph capabilities
Tech Stack: Rust, libSQL/Turso, GLiNER, Tree-sitter, MCP Server
What it does: Enables AI agents to coordinate as a swarm using stigmergy (environment-based coordination), eliminating context bloat while enabling massive parallelization. Self-improving system that learns optimal execution strategies over time.
Key Crates:
- fab-swarm - Core CLI and MCP server with 40+ tools, self-healing swarm orchestration
- fab-brain - Personal knowledge graph with semantic search, "second brain" for AI-assisted knowledge curation
- fab-learn - Learning system that tracks outcomes, learns optimal tier routing over time
- fab-entity - High-performance graph-based NER with GLiNER (NAACL 2024 SOTA zero-shot entity extraction)
- fab-codebox - Tree-sitter AST cache with query REPL for code intelligence (40+ languages)
- fab-lint - Fast technical debt linter with jj integration
What Makes It Different:
- Nano-agents: Deterministic tasks execute in ~50-500μs without LLM calls (vs. seconds for traditional agents)
- Stigmergy over messaging: Agents coordinate through shared environment, not message passing (avoids N² message explosion)
- Auto-improving: fab-learn tracks which model tiers work best for each task type, continuously optimizing
- Self-healing: Automatic recovery from crashed agents with zero downtime
- Production-ready: Follows hexagonal architecture, comprehensive testing with cargo-llvm-cov (44% coverage)
Practices Followed:
- Hexagonal architecture with clean separation of concerns
- Dependency injection for testability
- Circuit breaker pattern for external API resilience
- Rate limit pooling for distributed systems
- Graceful shutdown with LIFO cleanup ordering
Performance analyzers for C# 11-14 and .NET 9-10
Tech Stack: C#, Roslyn Analyzers, .NET 9-10 RC1
What it does: 23 Roslyn analyzers providing 10-200x performance improvements for C# codebases
Business Value: Catches performance anti-patterns at compile-time before they reach production, eliminating costly refactoring cycles
Complete C# 14 implementation of Google's ReasoningBank with self-learning capabilities
Tech Stack: C# 14, .NET 10, TensorPrimitives, SIMD (AVX-512/ARM SVE), Microsoft Agent Framework
What it does: Production-ready AI memory engine built on Google's ReasoningBank architecture, fully implemented in C# 14 with .NET 10's native TensorPrimitives and SIMD vectorization for 30-250x performance improvements.
Self-Learning Capabilities:
- 9 Modern RL Algorithms: MCTS, DQN, Dueling DQN, Rainbow, A2C, PPO, SAC, Q-Learning, Multi-Agent systems
- Reflexion Memory: Self-critique and learning from failures
- Skill Library: Pattern consolidation with k-means clustering
- Causal Memory Graph: Pearl's do-calculus for understanding cause-and-effect
- Propensity Score Methods: IPW (Inverse Probability Weighting) for causal inference
Key Features:
- Hardware-accelerated vector operations with TensorPrimitives (AVX-512/ARM SVE)
- Zero-allocation hot paths with Span for maximum performance
- Microsoft Agent Framework integration for AI workflow orchestration
- 340+ tests with 90-95% coverage
- 20 NuGet packages ready for production
- Docker support with multi-stage builds
Performance:
- 30-250x faster than JavaScript implementation
- Batch operations: 50,000 vector inserts/sec, 100,000 deletes/sec
- 75% memory reduction compared to Node.js (200MB vs 800MB for 1M vectors)
Status: 100% complete, production-ready, fully documented with 25+ guides
Code graph analysis and visualization tool
Tech Stack: Rust, Graph Algorithms, Matryoshka Embeddings
What it does: Analyzes codebases as graphs to identify patterns, dependencies, and architectural structure. Multi-language support (Rust, Python, TypeScript, C#) with incremental parsing that only re-scans changed files.
Key Features:
- Graph-based code analysis - Transform codebases into queryable dependency graphs
- Multi-language parsing - Support for 4+ languages
- Incremental scanning - Only re-parse modified files for performance
- Claude Code integration - MCP server for AI-assisted code exploration
| Area | Technologies |
|---|---|
| Languages | C#, Rust, TypeScript, Python, SQL |
| Frameworks | .NET, ASP.NET Core, React, Node.js |
| Databases | PostgreSQL, SQL Server, Redis, Elasticsearch |
| Cloud | Azure, Cloudflare, Fly.io, Docker |
| Architecture | Modular Monoliths, Microservices, Event-Driven, DDD, SOLID |
| Leadership | Team Building, Technical Strategy, Agile/Scrum |
| Metric | Value |
|---|---|
| Years Experience | 25+ |
| Leadership Experience | 7+ years leading teams |
| Active Repositories | 35+ |
| Primary Focus | C#, Rust, TypeScript, Python |
| Recent Achievement | Transformed Reptune tech from startup to enterprise-grade, achieving top-3 global market position |
- Fractional CTO - Helped startups scale from MVP to enterprise-grade architecture, led international teams through critical transformation phases
- Technical Lead - Architected FinTech, RegTech, and SaaS solutions
- Email: [Available upon request]
- Location: Amsterdam area, Netherlands
- Open To: New opportunities, connections, and collaborations