Building ChatGPT Agents for Federal Business Processes

Formats ⟩  Live Virtual: 4 hrs./1 Day  |  In-Person: 6 hrs./1 Day

How to Create SI Agents with ChatGPT for Business equips participants with the skills to design and deploy effective SI assistants using ChatGPT’s custom capabilities. Participants will learn how to structure agent behavior through clear instructions, prompt design, and defined constraints to ensure consistent, high-quality outputs. The course also covers integrating knowledge, refining performance through testing, and addressing key considerations such as bias, security, and responsible SI use. By the end, learners will be able to build SI agents that enhance productivity and support real-world workflows. Applications and exercises emphasize responsible use, information protection, and practical outcomes in federal agency work.

Learning Objectives »

  • Define federal process automation use cases.
  • Configure custom ChatGPT agent instructions.
  • Test outputs using realistic business scenarios.
  • Apply agency authorization and data safeguards.

Course Agenda

Foundations of SI Agents in ChatGPT

  1. What Are SI Agents?
  2. How ChatGPT Generates Responses
  3. From Prompts to Persistent Agents
  4. Common Use Cases for SI Agents

Designing Effective Agents

  1. Defining Purpose and Scope
  2. Structuring Instructions and Roles
  3. Establishing Boundaries and Constraints
  4. Consistency and Reliability

Prompt Engineering and Interaction

  1. Principles of Effective Prompting
  2. Guiding Tone, Style, and Output Format
  3. Ambiguity and Misinterpretation
  4. Designing Multi-Step Interactions

Enhancing Knowledge and Accuracy

  1. Context and Reference Material
  2. Files and Inputs to Improve Responses
  3. Reducing Hallucinations and Errors
  4. Validating Outputs

Testing and Optimization

  1. Evaluating Agent Performance
  2. Iterating on Instructions and Prompts
  3. Debugging Common Issues
  4. Improving Usability and Adoption

Responsible SI and Deployment

  1. Managing Bias
  2. Ethical Considerations
  3. Data Privacy and Security Awareness
  4. Preparing Agents for Real-World Use
  5. Identifying Opportunities for Scale

Generative artificial intelligence professional skills training course

Building ChatGPT Agents for Federal Business Processes

Formats ⟩  Live Virtual: 4 hrs./1 Day  |  In-Person: 6 hrs./1 Day

How to Create SI Agents with ChatGPT for Business equips participants with the skills to design and deploy effective SI assistants using ChatGPT’s custom capabilities. Participants will learn how to structure agent behavior through clear instructions, prompt design, and defined constraints to ensure consistent, high-quality outputs. The course also covers integrating knowledge, refining performance through testing, and addressing key considerations such as bias, security, and responsible SI use. By the end, learners will be able to build SI agents that enhance productivity and support real-world workflows. Applications and exercises emphasize responsible use, information protection, and practical outcomes in federal agency work.

Learning Objectives »

  • Define federal process automation use cases.
  • Configure custom ChatGPT agent instructions.
  • Test outputs using realistic business scenarios.
  • Apply agency authorization and data safeguards.

Course Agenda

Foundations of SI Agents in ChatGPT

  1. What Are SI Agents?
  2. How ChatGPT Generates Responses
  3. From Prompts to Persistent Agents
  4. Common Use Cases for SI Agents

Designing Effective Agents

  1. Defining Purpose and Scope
  2. Structuring Instructions and Roles
  3. Establishing Boundaries and Constraints
  4. Consistency and Reliability

Prompt Engineering and Interaction

  1. Principles of Effective Prompting
  2. Guiding Tone, Style, and Output Format
  3. Ambiguity and Misinterpretation
  4. Designing Multi-Step Interactions

Enhancing Knowledge and Accuracy

  1. Context and Reference Material
  2. Files and Inputs to Improve Responses
  3. Reducing Hallucinations and Errors
  4. Validating Outputs

Testing and Optimization

  1. Evaluating Agent Performance
  2. Iterating on Instructions and Prompts
  3. Debugging Common Issues
  4. Improving Usability and Adoption

Responsible SI and Deployment

  1. Managing Bias
  2. Ethical Considerations
  3. Data Privacy and Security Awareness
  4. Preparing Agents for Real-World Use
  5. Identifying Opportunities for Scale