Course Objective & Scope
“Agent” appears in every product pitch, yet most teams cannot clearly say what separates an agent from an ordinary chatbot or rule-based automation. This programme explains the core building blocks of an agent (LLM, instructions, tool calling, memory, control loop) in plain language with live examples.
Participants try agent features in ChatGPT, Claude and Gemini as well as no-code agent builders, sketch a simple agent, compare autonomy levels and produce a first use case assessment checklist for a case adapted to their organisation.
Who Should Attend?
- Managers and business unit leaders who will decide on agent projects
- Process improvement, digital transformation and innovation teams
- Product managers and business analysts who will work with agents
- No technical prerequisites; basic everyday use of generative AI is enough
Key Takeaways
- Distinguish correctly between agents, assistants and workflow automation
- Explain the components of an agent (model, tools, memory, loop) on a diagram
- Define the right autonomy level and human checkpoints for a task
- Sketch a simple agent prototype with a no-code tool
- Prioritise candidate use cases by value, risk and feasibility
Curriculum
From Chatbot to Agent: Concepts and Terminology
- Differences between assistants, workflows and agents
- Autonomy levels and examples of agentic systems
Anatomy of an Agent
- LLM, system instructions and tool calling
- Short- and long-term memory, the observe–decide–act loop
Hands-on with Agent Platforms
- Agent features in ChatGPT, Claude and Gemini
- No-code agent builders such as Copilot Studio and n8n
Sketching a Simple Agent
- Writing the task definition, tool list and success criteria
- Observing faulty behaviour and improving instructions
Risks, Limits and Human Control
- Hallucination, wrong tool use and prompt injection risk
- Approval points and allocation of responsibility
Choosing the First Use Case in Your Organisation
- Value–risk–feasibility matrix
- Use case assessment checklist
Other Courses in This Category
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Agentic AI for executives: impact on business models, processes and organisation, function-by-function use cases, investment and ROI assessment, operational risk, governance and redesigning teams that work alongside agents.
- Live Course
- 5 modules
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Hands-on programme on how LLMs use APIs, databases and internal systems via function calling / tool calling: tool schema design, argument validation, error handling and a working agent built on OpenAI, Claude and Gemini APIs.
- Live Course
- 6 modules
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Method for turning business processes into agentic workflows: separating deterministic steps from LLM decisions, prompt chaining, routing, parallelisation and evaluator–optimizer patterns, implemented in n8n or Power Automate.
- Live Course
- 6 modules
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Developer programme on building autonomous agents with LangGraph, the OpenAI Agents SDK and the Claude Agent SDK: state management, tool integration, loop control, tracing and a deployment-ready agent for an organisational case.
- Live Course
- 6 modules
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Technical programme on how agents plan and execute multi-step tasks: ReAct, plan-and-execute, task decomposition, reflection and replanning, using reasoning models, and loop termination strategies.
- Live Course
- 6 modules
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Agent memory and context management for long-horizon tasks and multi-session interactions: working memory, episodic and semantic long-term memory, context compaction, and persistent memory architecture with Mem0 and LangGraph Store.
- Live Course
- 5 modules
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