Fundamentals of AI-Native Software Development

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.

AI Native Software Development Training Delivery Methods

• Online

• Upskill your whole team by bringing Private Team Training to your facility.

AI Native Software Development Training Information

• 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