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Fundamentals of AI-Native Software Development
Course 4726
1 DAY COURSE

Course Outline

This course provides a structured, enterprise-focused approach to designing AI-native software systems that are secure, observable, scalable, and ready for production deployment. Attendees learn how modern generative AI applications are architected using foundation models, retrieval-augmented generation (RAG), structured prompt controls, and operational monitoring practices.

The course introduces the AI-Native Production Stack™, a five-layer framework for designing and evaluating AI-powered applications in enterprise environments. The course focuses on architecture, operational readiness, and governance rather than basic AI concepts or live coding.

Through guided walkthroughs, architecture diagrams, and structured activities, attendees learn how to evaluate model vendors, design prompt and context layers, apply guardrails, monitor usage and cost, and assess AI systems for deployment readiness.

Fundamentals of AI-Native Software Development Benefits

  • Course Benefits

    • Organizations struggle to move generative AI projects from prototype to production
    • Many teams lack architectural guidance for building secure and scalable AI systems
    • Developers and architects are unsure how to control model output, cost, and risk
    • Enterprises need governance, monitoring, and guardrails for AI deployments
    • AI initiatives fail due to poor design rather than poor models

    Prerequisites

    • Working knowledge of software development concepts
    • Familiarity with REST APIs or service-based applications
    • General understanding of generative AI concepts
    • Prior experience integrating foundation models is not required.

  • Prerequisites

    • Attendees should have a working knowledge of AI tools (ChatGPT, Copilot, Gemini)
    • Labs will be based on the licensed version of Copilot

AI Native Software Development Training Outline

Learning Objectives

Module 1: The AI-Native Production Stack

Module 2: Foundation Model Strategy and Vendor Tradeoffs

Module 3: Production Prompt Engineering and Control Layer

Module 4: Context Layer and Retrieval-Augmented Generation (RAG)

Module 5: Operations, Monitoring, and Governance for Production AI

Course Dates
Attendance Method
Note about the Certification Exam

When you register for the course, you will be prompted to choose Y/N to take the exam. Please select yes, as all HHS CISO employees are required to attempt the exam if one is offered for the course. Please be advised, if your course if funded by DIR, the Certification Organization has agreed to provide DIR the pass/fail status of your exam. DIR will only share this information in an aggregated report to state leadership that reflects total exam pass or fails. No individual names of any students will be included in any reports.

DIR requires that you submit the request for your exam voucher within one month of the last day of your course. DIR requires that you take your exam within six months of the last day of your course.

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