BTP_INTEGRATIONintermediate
Generative AI Hub and SAP AI Core
Understand SAP's generative AI hub on SAP AI Core, including model access, prompt engineering, orchestration, grounding, model lifecycle, security, observability and enterprise AI governance.
Overview
Understand SAP's generative AI hub on SAP AI Core, including model access, prompt engineering, orchestration, grounding, model lifecycle, security, observability and enterprise AI governance.
Lessons in this topic
- Generative AI Hub Part 1: SAP AI Core, Generative AI Hub and How They RelateSAP AI Core is the runtime and lifecycle foundation for AI on BTP; the generative AI hub is a capability within it (plus SAP AI Launchpad) for accessing and orchestrating LLMs. Learn the relationship between AI Core, AI Launchpad and generative AI hub, the extended service plan requirement, resource groups, and the models available (third-party and SAP's own, like SAP-RPT-1.5 and SAP-ABAP-1).
- Generative AI Hub Part 2: Deployments, Prompts and Consuming ModelsGet hands-on: create an orchestration deployment, call it with the SAP Cloud SDK for AI (Python, Java or JavaScript), understand prompt templating, model configuration, and how a single orchestration deployment lets you swap models without redeploying — plus restricting which models are allowed.
- Generative AI Hub Part 3: Production Patterns — Grounding, Data Masking, Content Filtering and EvaluationMove from prototype to production: grounding responses in your own data (retrieval-augmented generation), masking sensitive data before it reaches the model, content filtering for safety, inference observability, and evaluating outputs before trusting them in business processes.
Interview questions covered
- What are the most important concepts in Generative AI Hub and SAP AI Core, and how do they connect to Generative AI Hub and SAP AI Core Fundamentals in a real SAP landscape?
- A project team is working on Generative AI Hub and SAP AI Core. Using the Production GenAI on SAP: Grounding, Orchestration, Evaluation and Guardrails scenario, how would you approach the requirement from design through validation?
- A production issue is reported in Generative AI Hub and SAP AI Core around Getting Started with Generative AI Hub and SAP AI Core. How would you troubleshoot it systematically and avoid the common failure patterns?
- What design decisions and trade-offs matter most when implementing Generative AI Hub and SAP AI Core, particularly for Generative AI Hub and SAP AI Core Fundamentals?
- You inherit an existing Generative AI Hub and SAP AI Core implementation covering Production GenAI on SAP: Grounding, Orchestration, Evaluation and Guardrails. What would you review before changing it, and what would make you confident the change is production-ready?