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Duration 14 hours (2 days)
Course Outline
Overview of GPT-5 and Developer Potential
- Core features of GPT-5, including multi-modality and agent capabilities
- Selecting appropriate models and navigating pricing structures and usage limits
- Addressing ethical implications and enterprise governance standards
Prompt Engineering and System Architecture for Consistency
- Advanced prompt patterns, system messages, and context optimization
- Comparing chain-of-thought reasoning with concise prompting and few-shot methods
- Validating prompts and defining clear acceptance criteria
APIs, SDKs, and Local Development Environment
- Interacting with GPT-5 APIs, utilizing SDKs, and managing authentication and secrets
- Setting up local development environments, simulating responses, and utilizing sandboxes
- Managing version control, request/response schemas, and robust error handling
Agent Development and Tool Integration
- Structuring secure agent architectures and defining tool interfaces
- Implementing routing, orchestration, and fallback mechanisms
- Managing rate limits, controlling concurrency, and handling transactional integrity
Testing, Evaluation, and Verification
- Creating automated test suites for prompt behavior and outcomes
- Conducting red-teaming, fuzz testing, and analyzing adversarial examples
- Measuring accuracy, hallucination frequency, and user satisfaction metrics
Deployment, Monitoring, and Observability
- Implementing CI/CD pipelines for model-driven features and managing canary releases
- Utilizing logging, tracing, and telemetry for prompt-level visibility
- Configuring alerts, managing SLAs, and executing incident response protocols
Security, Privacy, and Cost Efficiency
- Managing data handling, considering PI/PHI implications, and sanitizing context
- Enforcing access controls, maintaining audits, and meeting compliance requirements
- Optimizing token usage through batching and implementing caching strategies
Recap and Path Forward
Requirements
- An understanding of at least one programming language such as Python or JavaScript
- Experience calling REST APIs or SDKs
- Basic familiarity with 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.
