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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.
- Selecting the right models and understanding pricing structures and usage limits.
- Ethical considerations and enterprise governance frameworks.
Prompting and System Design for Reliable Outputs
- Effective prompt patterns, system messages, and context engineering.
- Comparing chain-of-thought and concise prompting, along with few-shot techniques.
- Testing prompts and defining clear acceptance criteria.
APIs, SDKs, and Local Dev Workflow
- Interacting with 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 safe agent architectures and effective tool interfaces.
- Routing logic, orchestration, and fallback strategies.
- Managing rate limits, concurrency control, and transactional integrity.
Testing, Evaluation, and Validation
- Creating automated test suites for prompts and behavioral outcomes.
- Red-teaming, fuzz testing, and handling adversarial examples.
- Tracking metrics for accuracy, hallucination rates, and user satisfaction.
Deployment, Monitoring, and Observability
- CI/CD patterns for model-enabled features and canary release strategies.
- Implementing logging, tracing, and telemetry for prompt-level observability.
- Setting up alerting systems, SLA considerations, and incident response protocols.
Security, Privacy, and Cost Optimization
- Data handling practices, PI/PHI considerations, and context sanitization.
- Access control, auditing processes, and compliance checkpoints.
- Optimizing token usage through batching and caching strategies.
Summary and Next Steps
Requirements
- A solid grasp of at least one programming language, such as Python or JavaScript.
- Practical experience with calling REST APIs or utilizing SDKs.
- Fundamental knowledge of ML/AI concepts and JSON data structures.
Target Audience
- Software engineers.
- ML engineers.
- DevOps and SRE engineers.
Testimonials (1)
Able to pivot upon audience suggestions - ie able to create a real AI agent scenario on the spot.
