Agentic AI Agent Development Training focuses on the practical design and creation of intelligent AI agents that can plan, reason, act, and collaborate autonomously. This course teaches participants how to build agentic AI agents from scratch by defining goals, behaviors, tools, and workflows. The training is framework-agnostic and emphasizes real-world agent design patterns used across modern AI platforms.

• Understand the fundamentals of Agentic AI and autonomous AI agents
• Design and develop AI agents with reasoning and decision-making capabilities
• Integrate LLMs, APIs, tools, and external data sources into AI agents
• Build multi-step task execution workflows using AI agents
• Implement memory, context handling, and prompt engineering techniques
• Deploy and evaluate AI agents for real-world automation use cases

• AI and automation professionals
• Product managers and solution designers
• Business analysts and innovation teams
• Consultants and digital transformation leaders
• Professionals building AI agents

• Completion of Agentic AI Essentials or equivalent knowledge
• Basic understanding of AI concepts and workflows
• No programming or advanced technical background required

• Designing goal-driven agentic AI agents
• Defining agent behaviors, tools, and constraints
• Building single-agent and multi-agent systems
• Managing agent autonomy and execution
• Applying governance and responsible AI practices

By the end of this training, participants will be able to design, build, and evaluate agentic AI agents for real-world applications. Learners will gain the confidence to create intelligent agents that operate autonomously while remaining aligned with business goals and responsible AI principles.

Foundations of Agentic AI Agent Design
• Agent goals, roles, and responsibilities
• Planning, reasoning, and execution loops
• Managing context, memory, and state

Designing Agent Behaviors and Actions
• Tool usage and action selection
• Decision-making and conditional logic
• Preventing agent drift and failures

Building Single-Agent Systems
• End-to-end agent workflow design
• Task decomposition and sequencing
• Validating agent outputs

Multi-Agent Systems and Collaboration
• Role-based agent teams
• Communication and coordination patterns
• Conflict resolution and task delegation

Human-in-the-Loop Agent Design
• Oversight, approval, and intervention models
• Balancing autonomy and control
• Trust and accountability mechanisms

Business and Enterprise Use Cases
• Agentic AI for automation and productivity
• Research, analysis, and decision support agents
• Cross-functional enterprise scenarios

Hands-on Agent Building Workshop
• Designing and testing agentic AI agents
• Real-world agent development scenarios
• Participant practice and feedback

• Fundamentals of Agentic AI and AI agent architectures
• Prompt engineering and reasoning workflows
• Tool/API integration with AI agents
• Multi-agent and task orchestration concepts
• Memory and context management implementation
• Mini project or practical AI agent development exercise

• Participation in hands-on agent-building exercises
• Practical agent design assignment
• Knowledge-based assessment

Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.

Participants who successfully complete the training and evaluation will receive an AcadNXT Certificate of Completion in Agentic AI Agent Development, validating their skills in building autonomous AI agents.