Expertise & Sharing
As an IT consultant, author and tech entrepreneur, I support organizations in designing, modernizing and evolving their software systems, as well as integrating generative AI into business activities and software delivery. I also share my experience through articles, training, conferences and active involvement in technical communities.
My expertise lies at the intersection of software engineering, systems architecture, fullstack development, applied artificial intelligence, and technical sharing.
Design of robust applications, modular architectures, APIs, Java backend, Spring, Quarkus, hexagonal architecture, microservices and enterprise systems.
Integration of LLMs, RAG, AI agents, Spring AI and conversational systems into concrete business applications.
Web, mobile and backend application development with an approach oriented towards quality, maintainability, performance and business value.
Articles, conferences, training and educational content around software engineering and applied AI.
My path has been built between corporate missions, open source contributions, technical training and entrepreneurial projects. I intervene as an IT consultant, software architect, fullstack developer, trainer, speaker and founder of Gad Digital.
Learn more about my backgroundSupporting companies in various sectors: financial services, fintech, games, education, public services, industry and health.
Active participation in Java and AI projects (Spring AI) and publication of libraries like Toon4j.
Mentoring developers and introducing young people to robotics, home automation and embedded systems.
Published by Orange AVA, this book is dedicated to Java design patterns, modern software architecture and the design of robust, maintainable and scalable applications.
View the book
Gad Digital is the technology company I founded to transform my expertise into concrete solutions, products and support. Through Gad Digital, I lead initiatives around digital solution development, applied AI and technical training.
Discover Gad DigitalBlog
RAG Without a Dedicated Vector Database: Simplifying Infrastructure Without Moving the Problem
An embedded vector store can simplify a RAG system, provided we understand where persistence, availability, and operational responsibilities move.
Observe Before Optimizing
Before optimizing an LLM system, you need to make its decision chain visible so you can understand what it actually does beyond the displayed answer.
Freezing the Behavior of an LLM System Before Evolving It
Changing the model is not enough to guarantee behavioral stability. Characterization tests help protect business invariants and govern the evolution of LLM systems.
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