Course Outline

LLM Application Architecture and Design

  • Common OpenAI application patterns for assistants, copilots, and workflow automation
  • Choosing the right architecture for business requirements, reliability, and user experience
  • Moving from prototype code to maintainable application design

Prompting, Context, and Structured Outputs

  • Structuring system, user, and developer instructions for predictable behavior
  • Designing prompts for consistency, task control, and clearer responses
  • Using structured outputs to support downstream application logic
  • Managing context windows, conversation state, and response quality

Tool Use and Workflow Orchestration

  • Using function calling and tool-enabled workflows with external services
  • Validating inputs and outputs, handling errors, and applying fallback behavior
  • Designing multi-step flows for practical business tasks

Retrieval and Knowledge Grounding

  • Identifying when retrieval-augmented generation is appropriate
  • Preparing documents and chunking content for useful retrieval
  • Retrieving relevant context and grounding responses in trusted sources

Evaluation, Guardrails, and Operational Readiness

  • Defining quality criteria and testing workflows against expected outcomes
  • Reducing hallucinations and handling unsafe, irrelevant, or ambiguous requests
  • Monitoring usage, latency, token consumption, and cost
  • Preparing applications for deployment, support, and iterative improvement

Hands-On Implementation Workshop

  • Building a small end-to-end OpenAI application that combines prompting, structured output, tool use, and retrieval
  • Reviewing design decisions, common issues, and practical next steps for production use

Requirements

  • Familiarity with large language model concepts and API-based application development
  • Experience working with REST APIs, JSON, and prompt-driven application workflows
  • Intermediate programming experience in Python, JavaScript, or a similar language

Audience

  • Software developers building LLM-powered applications
  • AI engineers and technical leads designing OpenAI-based solutions
  • Product teams and solution architects responsible for production AI features
 7 Hours

Delivery Options

Private Group Training

Our identity is rooted in delivering exactly what our clients need.

  • Pre-course call with your trainer
  • Customisation of the learning experience to achieve your goals -
    • Bespoke outlines
    • Practical hands-on exercises containing data / scenarios recognisable to the learners
  • Training scheduled on a date of your choice
  • Delivered online, onsite/classroom or hybrid by experts sharing real world experience

Private Group Prices RRP from €2280 online delivery, based on a group of 2 delegates, €720 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.

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