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Course Outline
Overview of GPT-5 and Developer Capabilities
- Key features of GPT-5, including multi-modality and agent capabilities
- Model selection, pricing structures, and usage limitations
- Ethical guidelines and enterprise governance frameworks
Prompting Strategies and System Design for Reliability
- Advanced prompt patterns, system messages, and context engineering
- Comparing chain-of-thought vs. concise prompting and few-shot techniques
- Validating prompts and defining clear acceptance criteria
APIs, SDKs, and Local Development Workflows
- Interacting with GPT-5 APIs, SDK utilization, authentication, and secrets management
- Setting up local development environments, mocking responses, and sandboxing
- Managing versioning, request/response schemas, and comprehensive error handling
Architecting Agents and Tool Integrations
- Designing secure agent architectures and defining tool interfaces
- Implementing routing, orchestration, and fallback mechanisms
- Managing rate limits, concurrency, and transactional integrity
Testing, Evaluation, and Validation Frameworks
- Creating automated test suites for prompt behavior and consistency
- Conducting red-teaming, fuzz testing, and adversarial example analysis
- Tracking metrics for accuracy, hallucination rates, and user satisfaction
Deployment, Monitoring, and Observability
- Applying CI/CD patterns for model-driven features and managing canary releases
- Implementing logging, tracing, and telemetry for prompt-level insights
- Configuring alerting systems, SLA management, and incident response procedures
Security, Privacy, and Cost Optimization
- Handling sensitive data, PI/PHI considerations, and context sanitization
- Enforcing access controls, auditing, and compliance checkpoints
- Optimizing token usage, implementing batching, and leveraging caching strategies
Wrap-up and Future Directions
Requirements
- Proficiency in at least one major programming language, such as Python or JavaScript.
- Hands-on 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 / SRE Engineers
14 Hours
Testimonials (1)
Able to pivot upon audience suggestions - ie able to create a real AI agent scenario on the spot.
