Data, AI & Digital Transformation Consulting — Canada | Senegal | International
Agentic AI
Training
Two complementary tracks to master agentic AI: adoption strategy for leaders and technical agent design for development teams.
Mastering agentic AI, from strategy to code
From strategic vision to technical implementation
Agentic AI represents a major paradigm shift: systems capable of reasoning, planning, and acting autonomously to accomplish complex objectives. Bennen Technologies offers structured training in two distinct tracks, designed to meet the specific needs of decision-makers and technical teams.
Our pedagogical approach draws on our field experience in highly regulated environments. Each module combines theory, real-world case studies, and hands-on workshops. Participants leave with concrete tools, proven decision frameworks, and skills that are immediately applicable.
Both tracks can be taken independently or in combination, depending on participant profiles and objectives. We also adapt the content to each client's industry and organizational context.
Key Deliverables
- Complete training materials (slides, guides)
- AI use case evaluation framework
- Personalized adoption roadmap
- Code examples and reference architectures
- Access to practice environments
- Bennen Technologies participation certificate
- Post-training follow-up (30 days)
Enterprise Strategy in Agentic AI
Designed for executives, managers, and decision-makers. This track covers the fundamentals of agentic AI, strategic challenges, organizational adoption models, and key success factors for sustainable transformation.
Foundations & strategic challenges
Understanding what agentic AI is, its real capabilities, its limits, and the transformations it drives in business models and organizational processes.
Adoption & change management
Building an AI-friendly culture, managing organizational resistance, defining roles and responsibilities, and driving transformation with appropriate success indicators.
AI leadership & governance
Developing a clear AI vision, aligning stakeholders, managing ethical and regulatory risks, and establishing an AI agent governance framework adapted to sector-specific requirements.
High-impact use case selection
Structured method to identify, evaluate, and prioritize agentic AI use cases based on business value, technical feasibility, and risk level — to maximize the ROI of adoption.
AI Agent Programming & Design
Designed for developers, architects, and technical teams. This track covers the technical foundations of AI agents, development frameworks, multi-agent architecture patterns, and integration with existing systems.
Technical foundations of AI agents
AI agent architecture, reasoning loops (ReAct, Chain-of-Thought), memory, tools, and orchestration. Understanding fundamental patterns before coding.
Frameworks & implementation
Mastering LangChain, LangGraph, AutoGen, and CrewAI to design simple agents and multi-agent systems. Integration with Azure OpenAI, Claude, and Gemini.
Multi-agent architecture & orchestration
Architecture patterns for multi-agent systems: supervisor agents, specialized agents, inter-agent communication, state management, and error handling in production.
Hands-on workshops on real use cases
Design and implementation of AI agents on concrete use cases: research agents, process automation, integration with enterprise APIs and databases.
Technologies & Platforms Covered
Complementary Services
Ready to master agentic AI?
Contact us to discuss the format best suited to your team — in-person, virtual, or hybrid training, tailored to your sector.