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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
