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Duration 14 hours
Course Outline
Introduction to GPT-5 and Developer Capabilities
- Key capabilities of GPT-5, including multi-modality and agent features.
- Model selection, along with understanding pricing structures and usage limits.
- Ethical considerations and enterprise governance frameworks.
Prompting and System Design for Reliable Outputs
- Prompt patterns, system messages, and context engineering techniques.
- Comparing chain-of-thought reasoning with concise prompting and few-shot methods.
- Prompt testing methodologies and establishing clear acceptance criteria.
APIs, SDKs, and Local Development Workflow
- Calling GPT-5 APIs, using SDKs, and managing authentication and secrets.
- Local development practices, including mocking responses and sandboxing.
- Versioning, request/response schemas, and robust error handling.
Building Agents and Tool Integrations
- Designing secure agent architectures and defining tool interfaces.
- Implementing routing, orchestration, and fallback strategies.
- Managing rate limits, concurrency control, and transactional logic.
Testing, Evaluation, and Validation
- Developing automated test suites for prompts and agent behaviors.
- Applying red-teaming, fuzz testing, and adversarial examples.
- Tracking metrics for accuracy, hallucination rates, and user satisfaction.
Deployment, Monitoring, and Observability
- CI/CD patterns for model-enabled features and implementing canary releases.
- Logging, tracing, and telemetry for prompt-level observability.
- Setting up alerting, defining SLA considerations, and incident response.
Security, Privacy, and Cost Optimization
- Data handling practices, PI/PHI considerations, and context sanitization.
- Access control mechanisms, auditing processes, and compliance checkpoints.
- Optimizing token usage through batching and caching strategies.
Summary and Next Steps
Requirements
- Proficiency in at least one programming language, such as Python or JavaScript.
- Practical experience in calling REST APIs or utilizing SDKs.
- Fundamental understanding of ML/AI concepts and JSON data structures.
Audience
- Software Engineers
- ML Engineers
- DevOps / SRE Engineers
Testimonials (1)
Able to pivot upon audience suggestions - ie able to create a real AI agent scenario on the spot.
