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Duration 14 hours
Course Outline
Overview of GPT-5 Capabilities and Developer Standards
- Key capabilities of GPT-5, including multi-modality and autonomous agent features
- Model selection criteria, pricing structures, and operational limits
- Ethical frameworks and enterprise governance protocols for government use
Prompt Engineering and System Architecture for Reliability
- Advanced prompt patterns, system message configuration, and context optimization
- Comparative analysis of chain-of-thought reasoning versus concise directives and few-shot learning
- Prompt validation methodologies and defining acceptance criteria for public sector outputs
API Integration, SDK Implementation, and Local Development
- GPT-5 API invocation, SDK integration, and secure authentication and secrets management
- Local development environments, response mocking, and isolated sandbox testing
- Version control strategies, request/response schema standards, and comprehensive error handling
Agent Development and Secure Tool Integration
- Architecting secure agent frameworks and standardized tool interfaces for government operations
- Logical routing, task orchestration, and resilient fallback mechanisms
- Rate limit management, concurrency controls, and transactional integrity considerations
Testing, Evaluation, and Validating System Performance
- Automated testing frameworks for prompt behavior and functional consistency
- Red-teaming exercises, fuzz testing, and adversarial scenario analysis
- Establishing metrics for accuracy, hallucination rates, and end-user satisfaction
Deployment, Continuous Monitoring, and Observability
- CI/CD integration patterns for AI-enabled features and controlled canary release strategies
- Comprehensive logging, distributed tracing, and telemetry for prompt-level visibility
- Alerting configurations, service level agreement (SLA) adherence, and incident response protocols
Security, Privacy Compliance, and Cost Efficiency
- Data handling standards, PII/PHI protection, and rigorous context sanitization procedures
- Granular access controls, audit logging, and regulatory compliance checkpoints for government applications
- Optimizing token usage, implementing batch processing, and leveraging caching strategies
Conclusion and Strategic Implementation Path
Requirements
- Proficiency in at least one programming language, such as Python or JavaScript.
- Practical experience with invoking REST APIs or utilizing Software Development Kits (SDKs).
- Fundamental familiarity with machine learning and artificial intelligence concepts, as well as JSON data structures.
Target Audience
- Software Engineers
- Machine Learning Engineers
- DevOps and Site Reliability Engineering (SRE) Professionals
Testimonials (1)
Able to pivot upon audience suggestions - ie able to create a real AI agent scenario on the spot.
