Charles Vandendriessche

At Neomnia, we don't just create prompts. We design AI-powered production ecosystems: autonomous agents integrated with custom UX interfaces.

Expertise & Deliverables:

AI Agent Architect (Agentic Workflows): Design of multi-agent systems for automating content production (Marketing, Tech, Documentation). Each agent is specialized, self-correcting, and connected to your business tools (n8n, Make).

AI & UX Application Development: Creation of WebApps and specific interfaces to make AI accessible and actionable for non-technical teams. Focus on user adoption and streamlined workflows (Product Design).

Production Engineering (Ops): Audit of bottlenecks and redesign of processes to transition from manual execution to AI-assisted industrial production.

RAG & Data Structuring: Implementation of data infrastructures (Vector DB) to ensure agents produce reliable, sourced, and hallucination-free results.

Training Missions

1. RAG Architecture & LLMOps

This is the core. You need to demonstrate your ability to build reliable information retrieval systems.

Key concepts mastered: Vector Databases (Pinecone, Weaviate, Milvus), strategic chunking, Embeddings, and hallucination evaluation (RAGAS).

Frameworks: LangChain, LlamaIndex, or Haystack.

2. Autonomous Agent & Workflow Design

The transition from a simple "Chatbot" to an intelligent Agent that performs tasks.

Learning: AutoGPT, BabyAGI, or CrewAI (for multi-agent orchestration).

Skills: Tool-use (AI's ability to use APIs, browsers, or databases).

3. AI Product Management & UX Design

This is what differentiates you from pure developers.

Training: AI service design, cognitive psychology applied to conversational interfaces, and product roadmap management specific to AI lifecycles (which are iterative and non-linear).

Process Audit and Mapping: Identifying production bottlenecks (the "chaos" of 10 calls for one piece of information).

Semantic Standardization: Creating a common repository (Knowledge Base) so every employee can access the right information with one click. This is the essential foundation for any RAG system today.

Workflow Automation (Ops): Implementing management and automation tools to reduce project management time by X%.

Front-End & AI Architecture: Orchestrating business needs to translate them into high-performance internal tools (dashboards, structured content generators).