Orchestrate

Learning paths

Not everyone needs every topic. Pick the path for your role: each one is a short route through the curriculum, in the right layer for you.

Executive essentials

Executives, business owners and steering committees

Where AI pays off in SAP, what it costs, what can go wrong, and how to govern it. No code.

Foundational layer · 20 topics · 17 live · about 2 h of reading so far

  1. The SAP Business AI landscape: where every piece sits
  2. Where AI creates value in S/4HANA processes
  3. Embedded AI across SAP applications
  4. Buy vs. build for SAP AI
  5. AI for SAP ECC customers before they migrate
  6. AI in S/4HANA migration projects
  7. Is your SAP data ready for AI?
  8. The AI business case
  9. Token economics
  10. Defining success metrics with the business
  11. Data security and PII in AI systems
  12. Agent permissions and SAP authorizations
  13. MCP security in 2026: lessons from the first exploited vulnerabilities
  14. AI governance for SAP programs
  15. The EU AI Act: what SAP customers need to do and when
  16. What SAP TechEd 2026 changed for AI builders
  17. An AI roadmap and operating model for an SAP customer
  18. SAP's API policy and third-party agents: what a renewal must saySoon
  19. Where should an agent live?Soon
  20. Which agent exists where: the S/4HANA Cloud agent catalogueSoon

Sales and pre-sales

Account teams, pre-sales and solution advisors

Explain SAP's AI offerings accurately, qualify use cases, and shape a credible proposal.

Foundational layer · 15 topics · 12 live · about 2 h of reading so far

  1. The SAP Business AI landscape: where every piece sits
  2. Where AI creates value in S/4HANA processes
  3. Embedded AI across SAP applications
  4. Joule and Joule Studio
  5. Joule agents and agent orchestration in SAP
  6. Document AI, built and bought
  7. Buy vs. build for SAP AI
  8. AI for SAP ECC customers before they migrate
  9. The AI business case
  10. AI opportunity assessment: AI, automation or neither?
  11. Scoping and estimating an AI engagement
  12. Technical storytelling: one architecture, five audiences
  13. Which agent exists where: the S/4HANA Cloud agent catalogueSoon
  14. Where should an agent live?Soon
  15. SAP customer stories as patternsSoon

Functional consultant

SAP functional and process consultants

Design AI into SAP processes you already know: data, grounding, agents, approvals and adoption. Mostly no code; a few deep layers where hands-on helps.

Foundational layer · 20 topics · 20 live · about 3 h of reading so far

  1. What an SAP forward deployed engineer does
  2. Where AI creates value in S/4HANA processes
  3. Calling your first SAP API Deep
  4. The SAP data model for AI engineers: tables, CDS views and OData
  5. Is your SAP data ready for AI?
  6. Time-series forecasting for SAP planning
  7. Anomaly detection in finance and procurement
  8. Explaining model predictions to the business
  9. RAG fundamentals: the architecture end to end
  10. Grounding on SAP data without breaking authorizations
  11. Asking SAP data questions in plain language: text-to-SQL and its limits
  12. Agents from first principles
  13. SAP tools for agents
  14. Joule and Joule Studio
  15. Designing human approval into AI workflows
  16. Embedded AI across SAP applications
  17. Document AI, built and bought
  18. Discovery: interviewing the customer
  19. Process mining to find AI opportunities
  20. Adoption and change management for AI

Developer fast track

Developers and architects who want to build on SAP now

Straight to building: models, retrieval, agents and security on SAP, skipping the machine learning math (come back to Units 2 to 4 later). When a step needs SAP access, do that unit's setup topic first.

Deep layer · 20 topics · 20 live · about 13 h of reading so far

  1. Set up your computer for this course
  2. Python and APIs for AI engineers
  3. Calling your first SAP API
  4. Secrets, API authentication and OAuth
  5. Set up for Unit 5: SAP generative AI hub access
  6. Choosing and calling LLMs
  7. Prompt and context engineering
  8. Structured outputs and function calling
  9. SAP Generative AI Hub and the orchestration service
  10. Building an AI API
  11. CAP and side-by-side extensions for AI
  12. RAG fundamentals: the architecture end to end
  13. SAP HANA Cloud vector engine
  14. Grounding on SAP data without breaking authorizations
  15. LLM evaluation fundamentals
  16. Agents from first principles
  17. The Model Context Protocol (MCP)
  18. Observability for AI systems
  19. Prompt injection and tool poisoning
  20. Agent permissions and SAP authorizations

Solution architect and integration lead

Solution architects, integration leads and senior consultants moving into design roles

How an SAP enterprise is wired end to end, how its systems integrate, and how to design and review AI solutions that fit the landscape.

Deep layer · 20 topics · 20 live · about 13 h of reading so far

  1. The SAP data model for AI engineers: tables, CDS views and OData
  2. How an SAP enterprise is wired: organizational structure
  3. Master data that every module depends on
  4. Document flow and how logistics becomes finance
  5. Order-to-cash, end to end
  6. Procure-to-pay, end to end
  7. Record-to-report, end to end
  8. Landscape and deployment: editions, systems and the migration approach
  9. Fit-to-standard and extension choices: where each requirement should live
  10. Roles and authorization design across modules
  11. Data migration: strategy, objects and reconciliation
  12. Reporting and analytics architecture: what lives where in an SAP landscape
  13. Non-functional design: volumes, performance, availability and audit
  14. One exception, traced across the enterprise
  15. How SAP systems talk: integration styles and when to use each
  16. The integration platform and clean core
  17. The integration lead's toolkit: inventory, specs, testing and cutover
  18. Calling AI from SAP Integration Suite
  19. Writing a solution design document for an AI use case
  20. The solution architect on an SAP program

From SAP specialist to FDE

Module experts (PM, MM, SD, FI and others) and ABAP developers

Start from the module you know: see the rest of the enterprise, pick up Python and AI, and finish with a working agent on SAP processes.

Deep layer · 20 topics · 20 live · about 9 h of reading so far

  1. What an SAP forward deployed engineer does Foundational
  2. Set up your computer for this course
  3. Python and APIs for AI engineers
  4. Calling your first SAP API
  5. How an SAP enterprise is wired: organizational structure Foundational
  6. Document flow and how logistics becomes finance
  7. Order-to-cash, end to end Foundational
  8. Procure-to-pay, end to end Foundational
  9. Plan-to-produce, end to end Foundational
  10. Maintain-to-settle: plant maintenance and assets Foundational
  11. One exception, traced across the enterprise
  12. Machine learning in plain terms Foundational
  13. Choosing and calling LLMs
  14. Prompt and context engineering
  15. RAG fundamentals: the architecture end to end
  16. Agents from first principles
  17. One order-exception agent, built three ways
  18. Coding agents for SAP developers
  19. Discovery: interviewing the customer Foundational
  20. Capstone: an enterprise exception management platform

Full FDE track

Aspiring forward deployed engineers

Take the whole curriculum in order, both layers, then the portfolio projects. These are the milestone topics: the points where each unit's skill comes together.

Deep layer · 20 topics · 20 live · about 13 h of reading so far

  1. What an SAP forward deployed engineer does
  2. One exception, traced across the enterprise
  3. Machine learning in plain terms
  4. Embeddings and semantic similarity
  5. How LLMs generate text, and what that means for enterprise use
  6. SAP Generative AI Hub and the orchestration service
  7. How SAP systems talk: integration styles and when to use each
  8. RAG fundamentals: the architecture end to end
  9. Building an evaluation harness
  10. Evaluating in production: shadow mode, A/B tests and user feedback
  11. One order-exception agent, built three ways
  12. Running AI on SAP BTP in production
  13. Shipping AI changes safely: CI/CD for prompts, models and agents
  14. Agent permissions and SAP authorizations
  15. AI gateways: governing model and agent traffic
  16. Buy vs. build for SAP AI
  17. An agent that calls a RAP service
  18. Discovery: interviewing the customer
  19. Capstone: an enterprise exception management platform
  20. Your FDE portfolio and career path

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