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Course Outline
Introduction to GPT-5 and Developer Capabilities
- Key features of GPT-5, including multi-modality and agent capabilities
- Model selection, 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 reasoning with concise prompting and few-shot techniques
- Testing prompts and defining clear acceptance criteria
APIs, SDKs, and Local Development Workflow
- Integrating GPT-5 APIs, using SDKs, and managing authentication and secrets
- Local development practices, including mocking responses and sandboxing
- Handling versioning, request/response schemas, and error management
Building Agents and Tool Integrations
- Architecting safe agent systems and designing tool interfaces
- Implementing routing, orchestration, and fallback strategies
- Managing rate limits, concurrency, and transactional integrity
Testing, Evaluation, and Validation
- Creating automated test suites for prompts and behavioral verification
- Conducting red-teaming, fuzz testing, and analyzing adversarial examples
- Measuring accuracy, hallucination rates, and user satisfaction metrics
Deployment, Monitoring, and Observability
- Implementing CI/CD patterns for model-driven features and canary releases
- Utilizing logging, tracing, and telemetry for prompt-level observability
- Configuring alerting, SLA considerations, and incident response protocols
Security, Privacy, and Cost Optimization
- Addressing data handling, PI/PHI compliance, and context sanitization
- Enforcing access controls, 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 with calling REST APIs or utilizing SDKs
- Familiarity with fundamental 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.
