I build AI systems, developer tools, creative media software, and energy-aware infrastructure.
The thread through my work is measurement and usable experimentation: LLM agents should be evaluated, production systems should be observable, creative tools should be tangible, and energy claims should be reproducible before they are optimized.
My current focus is the overlap between:
- LLM systems: tool-calling agents, retrieval, structured outputs, and evaluation loops.
- Backend systems: APIs, software architecture, automation, and production-facing developer tools.
- Creative tools: generative interfaces, audiobooks, and small web apps that are useful as tools, not only demos.
- Energy-aware software: measurement, benchmarking, profiling overhead, reproducibility, and regression detection.
- Research prototypes that become usable tools, not only demos.
Wattch is lightweight energy-profiling infrastructure for developers and AI coding agents.
It is a Rust daemon and CLI for low-overhead energy measurement, built around reproducible benchmarks and machine-readable reports. The long-term direction is IDE and MCP integration, so AI agents can detect energy regressions, reason about measurement confidence, and suggest greener code changes without hiding overhead or uncertainty.
Status: work in progress.
Recent public activity in May 2026 includes:
- Fractal Brushes - a generative-art web app for fractal and symmetry-based backgrounds. Open the live demo.
- Whispbook - a self-hosted audiobook studio for turning selectable-text documents into chaptered audio with subtitles.
- jreferral - recommends energy-efficient JVM configurations for Java software.
- IJoules - measures energy consumption of Python code on macOS / Intel CPU.
- Wattch - current project; Rust daemon and CLI for developer-facing energy profiling.
- whispbook - TypeScript audiobook tooling for document-to-audio workflows.
- Fractal Brushes - static frontend for generating artsy fractal and symmetry backgrounds. Live demo.
My PhD work focused on energy-aware software engineering: measurement, benchmarking, testing, optimization, language/runtime behavior, and reproducibility. Wattch builds on that foundation by turning the research concerns into developer infrastructure: repeatable runs, explicit overhead, structured reports, and tooling that can fit into an engineering workflow.
- chakib_belgaid_thesis - thesis source and materials.
Source: thesisBrainMap.svg · thesisBrainMap.drawio
- Measurable before optimized.
- Local-first when possible.
- Explicit about uncertainty and overhead.
- Useful to developers, not only impressive in demos.