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ChatGPT AI Agent Builder – designing and deploying AI agents without coding

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Training process

Training needs analysis

If you have specific requirements regarding the training programme, we will carry out a training needs analysis for you. This will guide us on which aspects of the programme should receive greater emphasis, so that the training programme meets your specific needs.

What will you gain?

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Differentiate agents from chatbots - You will learn how to tell an AI agent apart from a basic chatbot and choose the right approach for a process, instead of building something too limited or unnecessarily complex.

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Design workflows without coding - You will understand the canvas and operating logic of Agent Builder, so you can create task flows, decisions, and data paths on your own without coding or relying on developers.

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Break processes into steps - You will learn how to turn a broad business goal into a clear sequence of agent actions, making your solutions more predictable, easier to manage, and simpler to expand over time.

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Improve agent prompts - You will practice writing prompts for individual workflow stages, separating system instructions from task context, and fixing common issues that reduce the quality of agent responses.

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Build conditional logic - You will master agents that react to different scenarios using if/else logic, exceptions, and alternative paths, so you can support more complex business cases with confidence.

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Use documents and data - You will learn how to feed an agent with user inputs and content from PDF, DOCX, and text files, so it can analyze information, make decisions, and act in real context.

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Test and optimize your agent - You will learn scenario testing, debugging, and versioning methods that help you catch errors faster, reduce response time, and control the operating cost of your solution.

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Prepare for company rollout - You will understand how to deploy agents for employees and customers, assign responsibilities in the team, and maintain quality, security, and governance across the organization.

Training programme

1. Introduction to AI agents

  • what an AI agent is vs a chatbot,
  • differences: prompt → workflow → agent,
  • examples of agent applications in companies,
  • when it is not worth using agents.

2. ChatGPT AI Agent Builder Architecture

  • what Agent Builder is and where it operates,
  • the concept of canvas / workflow,
  • types of elements (nodes):
    • input / output
  • LLM tasks,
  • decisions and conditions,
  • tools and integrations,
  • data flow in the agent.

3. Designing agent logic

  • process thinking vs prompt thinking,
  • breaking the process into steps,
  • designing:
    • sequential agents,
    • decision-making agents,
  • exercise:
    • an agent responding to customer inquiries,
    • an agent analyzing a document and making a decision.

4. Prompting in agents

  • differences: one-time prompt vs prompt in workflow,
  • system instructions vs task context,
  • context management,
  • typical errors in agent prompts,
  • exercise: improving the effectiveness of the agent's responses.

5. Multi-step agents and logical conditions

  • If / else in Agent Builder,
  • agents responding to different scenarios,
  • exception and error handling,
  • exercise: HR agent / offer agent.

6. Integrations and data

  • working with documents (PDF, DOCX, text),
  • use of user input data,
  • integrations with tools (MCP concept),
  • boundaries and security of data access.

7. Testing and optimization of agents

  • scenario testing,
  • workflow debugging,
  • optimization of costs and response time,
  • versioning of agents.

8. Deployment of agents in the organization

  • where an agent can be launched,
  • scenarios:
    • internal (employees),
    • external (clients),
  • roles and responsibilities,
  • governance and quality control.

What are the prerequisites for participating in the training?

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Basic AI tool usage - You should be comfortable using ChatGPT or similar tools and know how to phrase prompts, because the training builds on AI usage at the level of processes and agents.

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Process thinking - You should be able to describe a simple process step by step, identify decisions and exceptions, and understand links between stages, because agent design depends on it.

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Working with documents and data - You should be comfortable handling documents and input data, understand their role in a task, and judge what information is needed before a decision can be made.

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Business environment awareness - You should understand how processes work in your company or team, so you can design realistic rollout scenarios, testing approaches, and clear roles and responsibilities.