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ABAP Development Tools for VS CodeABAP Development Tools for VS CodeA Devtoberfest 2026 session on ABAP Development Tools for VS Code: where the extension sits after the ABAP Workbench and ABAP Development Tools for Eclipse, the ADT language server both editors share, and what the releases since May 2026 cover. The demo installs the extension, creates a destination, opens, creates and activates objects, runs ATC and ABAP Unit, and names the object types, domains among them, for which a developer still goes to Eclipse or SAP GUI. It also opens the extension's settings to turn on the ADT MCP Server and shows the tools a chat can call, with the object search and source code search tools listed as planned.published 2026-09-28
Agent-led custom code migration: From planning to mass adaptationAgent-led custom code migration: From planning to mass adaptationThe Custom Code Migration Agent in SAP Joule for Developers, ABAP AI capabilities, applied to moving custom code from SAP ERP Central Component to SAP Cloud ERP Private: the abstract describes a toolchain that starts with planning in SAP Cloud ALM and ends in mass remediation by the agent, with newer custom code management features shown alongside. Which findings the agent remediates, and how far it goes without a developer, the abstract does not say. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Marco Matha and Olga Dolinskaja, written here from SAP's abstract; the recording is not yet published.
Agentic Loop with Joule for Developers and ADT MCP ServerAgentic Loop with Joule for Developers and ADT MCP ServerA Devtoberfest 2026 session from SAP's ABAP AI team that generates a RAP issue-tracker application by prompting a coding agent. It covers what SAP Joule for Developers, ABAP AI capabilities now ships as MCP tools and which assistants can reach an ABAP system's virtual filesystem, then does the setup twice: turning on the ADT MCP Server and pasting the Joule side-by-side tenant link in ABAP Development Tools for VS Code, and again in ABAP Development Tools for Eclipse, where the custom agent becomes custom instructions. The demo's subject is the guardrails around the loop — an agent.md of phases and human checkpoints, skill files cloned from a GitHub repository for naming, ATC compliance and UI annotations — run through GitHub Copilot until the generated objects are activated, unit-tested and in a transport.SAP Developers, published 2026-09-28
AI Assisted CAP DevelopmentAI Assisted CAP DevelopmentA Devtoberfest 2026 session (CAP-43) on building CAP applications with a coding agent, in two demos. The first asks the same question twice in a dev container, once with no MCP server configured and once with @cap-js/mcp-server registered: without it the agent answers CAP's semantic search with an outdated vector type and CQL, with its documentation search it writes the built-in vector embedding function and a working similarity query. The second installs the cap-developer plugin from capire/skills, from a Devtoberfest preview branch, and runs its guided-development skill stage by stage — domain model, sample data, services, constraints — each stage reviewed before the next.SAP Developers, published 2026-10-16
AI-assisted full stack development using model context protocol serversAI-assisted full stack development using model context protocol serversMCP servers in Visual Studio Code used to configure, query and change a full-stack application built with CAP, CDS and OData: the agent access to your code concern, a coding assistant reading and changing the project it works in. The abstract names no server, so neither @cap-js/mcp-server nor any other is attached, and it does not say which changes are made. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Sergio Guerrero, written here from SAP's abstract; the recording is not yet published.
AI-assisted SAP development with MCPAI-assisted SAP development with MCPA Devtoberfest 2026 session (UI-41) that traces AI-assisted SAP development from pasting code into a chat window to coding agents with built-in connectors, and sorts the MCP servers around SAP development into SAP's own, the community's and the hosted ones, where the agent cannot change what the server allows. Four demos follow: GitHub Copilot alone explaining an ABAP report from a Git repository, @ui5/mcp-server reading an OpenUI5 sample app and converting it to TypeScript, mcp-sap-docs grounding Terraform files for a BTP subaccount the presenter had not written before, and arc-1 with Copilot in Eclipse tracing why a title longer than 40 characters is rejected and proposing the DDIC-allowed length instead. It ends on a skill that migrates an SAP Gateway project on an ECC system to RAP on S/4HANA step by step, and on a rule Marian Zeis gives for servers written for internal use: keep them read-only, because what the agent is short of is context.published 2026-10-16
Beyond copilots: Agentic development with SAPUI5Beyond copilots: Agentic development with SAPUI5Devtoberfest 2026 session UI-12, from the SAPUI5 team, on the year of work behind UI5/plugins-coding-agents: what a model produces for UI5 without help — outdated concepts, framework versions a decade old, generic JavaScript rules, code that does not run — and the two ways they chose to close that gap, an MCP server in September 2025 and skills packaged as plugins once agents began reading them. Three plugins are demonstrated live in Claude Code: the everyday one scaffolds an Oktoberfest tents application in about four minutes, the TypeScript conversion plugin rewrites an existing JavaScript project and reconfigures its build with the types and the transpile task, and the modernisation plugin takes a ten-year-old application through staged migrations, applying UI5 Linter's automatic fixes where they cannot break the app and the model where they can, then running the tests. @ui5/mcp-server is still the path for the parts that need a server, and the plugins are installed from the Claude Code and GitHub Copilot marketplaces rather than a UI5-hosted one.SAP Developers, published 2026-09-25
Intelligent App Development at Scale: SAP Fiori Elements + ABAP Development Tools for VS CodeIntelligent App Development at Scale: SAP Fiori Elements + ABAP Development Tools for VS CodeA Devtoberfest 2026 session (UI-33) that builds a RAP service and the SAP Fiori elements app over it from one VS Code workspace, with a coding agent driving two of SAP's MCP servers. The ABAP Development Tools for VS Code edges hold on the demo itself: its virtual file system keeps the ABAP package beside the Fiori project, the ADT MCP Server inside it creates, changes and activates the ABAP objects, and a version not yet released publishes the service binding from the agent instead of by hand. The @sap-ux/fiori-mcp-server edge covers its generators and the three-step workflow it uses for changes — list the functionality available for the application, ask for its JSON schema, then execute it — and the agent guidance edge rests on the skills the Fiori team publishes beside it, on the session's account of what a skill adds that a server does not, and on the analytical chart demo where a skill orchestrates both servers in one task.SAP Developers, published 2026-10-09
Level up app development: ABAP Cloud model innovations and Joule solutionLevel up app development: ABAP Cloud model innovations and Joule solutionThe ABAP RESTful application programming model, in SAP's abstract, generates multi-node business objects and adds event-driven side effects, collaborative draft, background processing and analytical tables, with the SAP Joule for Developers, ABAP AI capabilities add-on used to speed development up. The generated business objects are the transactional model concern; the abstract names each feature and says nothing about how it is used. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Anne Keller, Carine Tchoutouo Djomo, Frank Jentsch and Marina Blank, written here from SAP's abstract; the recording is not yet published.
Migrate and modernize your custom code using RISE with SAP and agentic AIMigrate and modernize your custom code using RISE with SAP and agentic AIThe Custom Code Migration Agent in SAP Joule for Developers, ABAP AI capabilities, shown on the RISE with SAP path that moves custom extensions from SAP ERP Central Component to SAP Cloud ERP Private: the abstract says the agent adapts the code through MCP tools and the AI for ABAP features in the custom code tools, and that the adapted code is then reworked along the clean core approach, the concern ABAP Cloud readiness covers. Which MCP tools, and what the clean core step changes in the code, the abstract leaves open. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Hitesh Bindal, Ingo Braeuninger, Jonas Helin of GitHub, Olga Dolinskaja and Thomas Fiedler, written here from SAP's abstract; the recording is not yet published.
News from Custom Code Migration: ECC to SAP S/4HANA Powered by Agentic AINews from Custom Code Migration: ECC to SAP S/4HANA Powered by Agentic AIA Devtoberfest 2026 session (ABA-23) on what SAP has added to the ECC to SAP S/4HANA custom code migration tools, demonstrated across a live ECC and an S/4HANA system. The first half stays deterministic and explains static analysis in that process: the custom code migration app's scoping over ABAP test cockpit findings, an explain of a legacy report and of an S/4HANA simplification finding, and transferable quick fixes exported from the app and applied on the ECC system through the SAP GUI ATC transaction before conversion. The second half runs the S/4HANA custom code migration agent in ABAP Development Tools for Eclipse: GitHub Copilot drives the ADT MCP Server's ATC and quick-fix tools in a loop, SAP Joule for Developers, ABAP AI capabilities produces the AI code proposals behind it, and only the high-confidence ones are written into the code, the rest left as comments in one transport request.published 2026-09-28
OData to outcomes—Build AI-enabled SAP Fiori apps using SAP Fiori elementsOData to outcomes—Build AI-enabled SAP Fiori apps using SAP Fiori elementsA Fiori elements app built through SAP's MCP servers: the OData V4 service comes from the MCP server for RAP, which the atlas holds as the ADT MCP Server, or from @cap-js/mcp-server for CAP, and the UI from @sap-ux/fiori-mcp-server, with annotations and actions added before the app is tied to SAP's AI features. Agent access to your code on both the service and the UI side; SAP's abstract names the servers and the steps and says nothing about which AI features or which agent host. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Benedikt Schoelch, Sebastian Steinhauer, Sebastian Werner and Stefan Engelhardt, written here from SAP's abstract; the recording is not yet published.
Spec first: The disciplined way to develop ABAP with agentsSpec first: The disciplined way to develop ABAP with agentsSpec-driven ABAP development with a new AWS Toolkit for Eclipse plug-in powered by Kiro, in SAP's words, working inside ABAP Development Tools for Eclipse: SAP's abstract says it reads the codebase, helps with new features, explains legacy code, refactors and generates tests, for S/4HANA modernisation or a new business feature. It answers agent access to your code from inside Eclipse; the plug-in itself is not yet in the atlas, and the abstract does not say how it reaches the ABAP system. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Jon Friesen and Stephan Kremer, written here from SAP's abstract; the recording is not yet published.
Strategy for agent-led development in ABAPStrategy for agent-led development in ABAPSAP Joule for Developers, ABAP AI capabilities moving ABAP development in ADT from AI-assisted to agent-led, across greenfield work and the migration and modernisation of existing solutions: SAP's strategy session for its ABAP AI add-on. The abstract states the direction and names no feature or release date. A TechEd 2026 session (Tuesday 27 October, Berlin; also ST124V, virtual), presented by Alexander Rother and Sonja Lienard, written here from SAP's abstract; the recording is not yet published.
From confident to correct: AI search results you can actually trustFrom confident to correct: AI search results you can actually trustHow SAP LeanIX designs its AI search agents so that a result does not need checking in the UI: agents that adapt to each customer's own workspace model, with ambiguous queries and silent errors at scale as the two problems the talk takes on. The atlas holds no entry for SAP LeanIX itself; the SAP LeanIX MCP Server is the nearest entry, and the abstract names neither it nor any mechanism behind the agents, so the edge rests on the product name alone. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Aviral Vaid and Sai Krishna Subramanian, written here from SAP's abstract; the recording is not yet published.
MCP Gateway in Practice: Architecture, configuration, and hands-onMCP Gateway in Practice: Architecture, configuration, and hands-onA Devtoberfest 2026 integration-track session (INT-21) on the MCP gateway of SAP Integration Suite: curated enterprise APIs served to agents as MCP tools over JSON-RPC, behind the authentication, authorization and traffic policies an API artifact already carries, with the existing API layer left in place. The hands-on half composes S/4HANA plant, material-stock and supplier data with a non-SAP location-risk source into one business data graph, downloads its OpenAPI specification, creates an MCP server artifact with tools, prompts and a surge-protection policy over that endpoint, and publishes it as a product in Developer Hub of API Management, where an agent developer subscribes and gets OAuth credentials. An MCP client then asks for 15 brake pads and ranks plants by stock, location risk and distance from Walldorf, which is what the agent access to your systems edge rests on; the Q&A covers principal propagation to the backend, how errors reach the model, and which Integration Suite editions carry the gateway.SAP Developers
Model context protocol (MCP) unlocked: Enable governed access to AI agentsModel context protocol (MCP) unlocked: Enable governed access to AI agentsThe MCP Gateway in SAP Integration Suite: the place policy, security and analytics are applied to a curated set of MCP tools before an AI agent reaches enterprise tools and APIs through it, tool governance done in the integration layer and agent access to your systems routed through one gateway. The abstract names the gateway and its three functions and does not say how tools are curated, which policies exist or how the agent authenticates. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Bruno Renzo, Emily Mui, Markus Winter and Sunny Kapoor, written here from SAP's abstract; the recording is not yet published.
SAP Integration Suite as the foundation for enterprise agentic AISAP Integration Suite as the foundation for enterprise agentic AISAP Integration Suite as the way an agent reaches systems: SAP's abstract says it gives agents governed access to APIs, events, applications, trading partners and processes across SAP and third-party landscapes, with AI assistance in the design, deployment and operation of the integrations. That is agent access to your systems through middleware; the abstract names no protocol and no gateway. A TechEd 2026 session (Tuesday 27 October, Berlin; also ST104V, virtual), presented by Markus Winter and Udo Paltzer, written here from SAP's abstract; the recording is not yet published.
Speed up your cloud journey with agentic data management and configurationSpeed up your cloud journey with agentic data management and configurationThe Configuration Assistant for SAP Cloud ERP: an agent that validates insights from an organisation's data and maps toward a target business configuration, under the heading of agentic data management, with data preparation, transparency and governance as the stated aims. The atlas holds no entry for the Configuration Assistant and no concern for business configuration of an ERP, so the edge is to Agent access to your systems, the nearest concern, an agent working on a system's data and configuration; the abstract's configuration is not the per-environment application settings the atlas files under that word. The abstract states aims and no feature detail. A TechEd 2026 session (Wednesday 28 October, Berlin; the same abstract runs as the hands-on TM267), presented by Felix Peter and Helen Sontowski, written here from SAP's abstract; the recording is not yet published.
Transform your configuration of SAP S/4HANA Cloud with agentic AITransform your configuration of SAP S/4HANA Cloud with agentic AIThe Configuration Assistant for SAP Cloud ERP, hands-on: an agent that validates insights from an organisation's data and maps toward a target business configuration, under the heading of agentic data management, with data preparation, transparency and governance as the stated aims. The atlas holds no entry for the Configuration Assistant and no concern for business configuration of an ERP, so the edge is to Agent access to your systems, the nearest concern, an agent working on a system's data and configuration; the abstract's configuration is not the per-environment application settings the atlas files under that word. The abstract is the same text as TM100 and states aims and no exercise detail. A TechEd 2026 hands-on session (Thursday 29 October, Berlin), presented by Felix Peter, Joerg Rupprecht, Joerg Singler and Simone Mundt, written here from SAP's abstract; the recording is not yet published.
🟣 Enable Your AI application to Run on Multiple Models to Ensure Resilience and Compliance🟣 Enable Your AI application to Run on Multiple Models to Ensure Resilience and ComplianceDevtoberfest 2026 session AI-21. A cross product owner on the SAP AI Core team gives the reasons an AI application ends up on more than one model — a model down at the hyperscaler, a data centre that is not allowed to run it, a version being deprecated — and runs a joke app that answers from Gemini 2.5 Flash in EU10 and from Claude 4.5 Haiku in Asia-Pacific. The walk through AI Core's parts is where the edges hold: prompts kept as templates in the prompt registry, imported through the launchpad and the APIs or synced as YAML from a git repository (Prompt management); the evaluation service scoring one prompt across up to four models per run on built-in or model-as-judge metrics, and the prompt optimizer generating variants against one metric (Agent evals); and the orchestration service harmonising the providers behind one message format with a priority-sorted fallback list (LLM integration). The session also states where a metric has to be designed rather than picked: an exact-JSON match scores an email generator at zero, so the joke app's custom metric judges topic and family-appropriateness instead.SAP Developers, published 2026-10-01
AI Assisted CAP DevelopmentAI Assisted CAP DevelopmentA Devtoberfest 2026 session (CAP-43) on building CAP applications with a coding agent, in two demos. The first asks the same question twice in a dev container, once with no MCP server configured and once with @cap-js/mcp-server registered: without it the agent answers CAP's semantic search with an outdated vector type and CQL, with its documentation search it writes the built-in vector embedding function and a working similarity query. The second installs the cap-developer plugin from capire/skills, from a Devtoberfest preview branch, and runs its guided-development skill stage by stage — domain model, sample data, services, constraints — each stage reviewed before the next.SAP Developers, published 2026-10-16
Beyond copilots: Agentic development with SAPUI5Beyond copilots: Agentic development with SAPUI5Devtoberfest 2026 session UI-12, from the SAPUI5 team, on the year of work behind UI5/plugins-coding-agents: what a model produces for UI5 without help — outdated concepts, framework versions a decade old, generic JavaScript rules, code that does not run — and the two ways they chose to close that gap, an MCP server in September 2025 and skills packaged as plugins once agents began reading them. Three plugins are demonstrated live in Claude Code: the everyday one scaffolds an Oktoberfest tents application in about four minutes, the TypeScript conversion plugin rewrites an existing JavaScript project and reconfigures its build with the types and the transpile task, and the modernisation plugin takes a ten-year-old application through staged migrations, applying UI5 Linter's automatic fixes where they cannot break the app and the model where they can, then running the tests. @ui5/mcp-server is still the path for the parts that need a server, and the plugins are installed from the Claude Code and GitHub Copilot marketplaces rather than a UI5-hosted one.SAP Developers, published 2026-09-25
Bring "developers.sap.com" Into Your Dev Environment: SAP Developer Context for AI Coding AgentsBring "developers.sap.com" Into Your Dev Environment: SAP Developer Context for AI Coding AgentsDevtoberfest 2026 session FA-11: a tour of the rebuilt developers.sap.com by the team that runs it, from the administration screens behind the home page to the agent interfaces in front of it. The site is a CAP application on SAP HANA Cloud and SAP BTP, open-sourced in full, and the half of the session that places it here is how its content reaches an agent: every tutorial is also served as markdown, a coding agent is detected and given that version instead of the HTML, a well-known agent card advertises what the site offers, and SAP Developers MCP answers questions about tutorials, news and a reader's own completion history in Claude Code and Joule Desktop, over OAuth or a personal access token. Behind the answers sit two things working together: a knowledge graph in the HANA database over 1400 tutorials and 11,000 concepts, and SAP AI Core for the Joule interactions and the embeddings, with the agent harness written for the site rather than taken off a shelf. Where neither MCP nor A2A is available, the same content is published as skills.SAP Developers, published 2026-09-25
Bringing SAP themes to any web app with coding agentsBringing SAP themes to any web app with coding agentsA Devtoberfest 2026 session from SAP's UI theme designer team, in two halves. The first is how an SAP theme is built: seven reference tokens, the main tokens that carry the semantics, component tokens such as the emphasized button background, and derived tokens for states like hover — the inheritance chain that makes theming hard to follow by eye, and the reason a custom theme always derives from an SAP base theme. The second installs SAP/ui-theme-designer-plugins-for-coding-agents in Claude Code and has it apply SAP design tokens to a login screen built with a non-SAP component library, then make the page themeable from a theme root and a theme URL parameter; the design-tokens skill npm-installs the theming content to read current parameter values, and the help skill fetches the UI theme designer help pages at query time. The presenters state the skills are not limited to SAPUI5 and run in any coding agent that reads skills.SAP Developers, published 2026-09-25
Intelligent App Development at Scale: SAP Fiori Elements + ABAP Development Tools for VS CodeIntelligent App Development at Scale: SAP Fiori Elements + ABAP Development Tools for VS CodeA Devtoberfest 2026 session (UI-33) that builds a RAP service and the SAP Fiori elements app over it from one VS Code workspace, with a coding agent driving two of SAP's MCP servers. The ABAP Development Tools for VS Code edges hold on the demo itself: its virtual file system keeps the ABAP package beside the Fiori project, the ADT MCP Server inside it creates, changes and activates the ABAP objects, and a version not yet released publishes the service binding from the agent instead of by hand. The @sap-ux/fiori-mcp-server edge covers its generators and the three-step workflow it uses for changes — list the functionality available for the application, ask for its JSON schema, then execute it — and the agent guidance edge rests on the skills the Fiori team publishes beside it, on the session's account of what a skill adds that a server does not, and on the analytical chart demo where a skill orchestrates both servers in one task.SAP Developers, published 2026-10-09
Real Pro-Code Development with Joule StudioReal Pro-Code Development with Joule StudioA Devtoberfest 2026 AI-track session that runs one agent build across both of Joule Studio's paths. Playing a procurement manager, one presenter states the intent in the browser, answers the clarifying questions, watches the fit-gap analysis name the S/4HANA APIs the use case needs, and pushes the intent and requirements document to GitHub; the other clones it and carries on in a terminal, logging in with the jl command line against her landscape URL and running its init command to fetch Joule Studio's skills for OpenCode. From there the coding agent writes the specification, the discovered API specifications, the MCP translation and the agent's Python file with its model configuration and evaluation scenarios, which is the edge to Agent tooling; the skills themselves, which SAP says not to edit but which a developer may add to, are the edge to Agent guidance.SAP Developers, published 2026-10-01
Token Efficiency – Your Guide To Smart AI DevelopmentToken Efficiency – Your Guide To Smart AI DevelopmentA Devtoberfest 2026 session from two engineers on SAP's business AI platform team on where a coding agent's tokens go: the read-decide-act loop behind one request, what the context command shows is occupying the window — 22,700 tokens of tool definitions against 1,800 of project instructions in their example — and the habits of compacting with a hint, clearing between tasks, choosing model and reasoning effort per job, and handing a large investigation to a sub-agent so only its summary comes back. It reaches agent guidance through the part on skills: a skill holds the reusable instructions for one kind of work and is disclosed progressively, a short description in the window and the detailed file read when it is relevant, rather than every occasional procedure sitting in the always-loaded project instructions. The demo runs on Claude Code against a generated warehouse-management project, with a custom status line showing context, session cost and a self-set budget.SAP Developers, published 2026-10-08
Unlocking Tabular Foundation Models: From Experimentation to ProductionUnlocking Tabular Foundation Models: From Experimentation to ProductionA Devtoberfest 2026 session (AI-41) on taking tabular prediction from a playground to a deployment. It sets tabular foundation models against a model trained per use case and against language models reading rows as text, explains in-context learning as examples plus the rows whose target column is missing, and tries SAP RPT 1.6 on a train-delay dataset in the RPT playground, including the column and row importance it returns with the prediction. The same prediction is then rebuilt on SAP AI Core, where the tabular orchestration service plays the part the orchestration service plays for language models: a data destination, a table artifact with its CSN schema and a scenario configuration registered once at design time, after which a predict call passes only the query rows, the scenario configuration and a context-selection strategy. The last demo runs those same calls in natural language through the aicore-skills plugin in a coding agent, and one of them only resolves once the agent is told which scenario configuration to use.SAP Developers, published 2026-10-15
What's in Daniel Hutzel's brain?What's in Daniel Hutzel's brain?A Devtoberfest 2026 session in the building-apps track, in which Daniel Hutzel and DJ Adams work through what the CAP team is building for agents. A bookshop gets an MCP endpoint beside its OData one from a single annotation, with the plugin writing the coding agent's configuration itself; in the xt-travels sample five services that know nothing about each other are served over MCP and an agent does the orchestration the hand-built UI and its value helps used to do. Hutzel then annotates a service as an agent so the ReAct loop and the choice of model move into the CAP service, and finally drops MCP for a skill that teaches the agent CQL instead, which is where the edges to Serve your application over MCP, Agent tooling and Agent guidance come from. The mechanism under all of it, a plugin file in the package root and event handlers that can be added to any CAP service, is the edge to Plugin authoring.published 2026-10-02
Achieve Agentic Enterprise Automation with SAP Integration Suite and Joule StudioAchieve Agentic Enterprise Automation with SAP Integration Suite and Joule StudioA Devtoberfest 2026 integration-track session (INT-22), the second of that week's integration sessions, given by an SAP product expert for process automation and integration together with the product manager for Joule Studio, who walks the audience through it. The opening states the subject: process management, automation and orchestration unified into one combined approach, which the presenters put forward as the foundation for building custom AI agents.SAP Developers, published 2026-09-30
Agent-led test management: Hands-on lab with Joule in SAP Cloud ALMAgent-led test management: Hands-on lab with Joule in SAP Cloud ALMThe Test Management Assistant, a Joule capability in SAP Cloud ALM, worked through on project scenarios: scoping requirements, detecting coverage gaps and generating test cases with AI. The edge is to SAP Joule, which the assistant runs on; SAP Cloud ALM has no entry here, and the atlas's testing concern, proving a service's model and handlers, is not this session's test management. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Christina Pickhardt, Daniel Lorenz, Niclas Weidner and Tobias Keller, written here from SAP's abstract; the recording is not yet published.
Agentic memory: Knowledge graph engine and recall in SAP HANA CloudAgentic memory: Knowledge graph engine and recall in SAP HANA CloudThe knowledge graph engine in SAP HANA Cloud as an agent's memory: what the engine, the graph side of graph, spatial and document data, does in an agentic workflow, how an agent keeps what it learns there, the state agent tooling holds between turns, and the SAP AI Core integration through which the database calls LLMs and tabular foundation models such as SAP-RPT-1. The abstract names the engine, the memory role and the AI Core link and does not say how the memory is written or read. DA263 on Wednesday 28 October is a two-hour hands-on on the same engine with a different cast. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Markus Fath and Shraddha Shetty, written here from SAP's abstract; the recording is not yet published.
AI-accelerated RISE with SAP migration with the system transition workbenchAI-accelerated RISE with SAP migration with the system transition workbenchSAP Joule for Consultants and the RISE with SAP system transition workbench in a move to SAP S/4HANA Cloud Private Edition: readiness assessments, migration workflows and the SAP tools involved. The edge is to SAP Joule, of which Joule for Consultants is a part; the system transition workbench has no entry here, and Platform migration covers applications leaving older BTP platforms, not an ERP system's move. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Daniel Funkert, Kristin Aleksandrova, Mirja Kempin and Moritz Gysler, written here from SAP's abstract; the recording is not yet published.
AI-enhanced analytics with SAP Business AI PlatformAI-enhanced analytics with SAP Business AI PlatformSAP Business Data Cloud data products joined to an ontology, a semantic layer the abstract says is supported by the Model Context Protocol, and read from Joule Work (SAP Joule) and SAP Analytics Cloud: that is the architecture SAP's abstract states for its AI-enabled analytics. The abstract names the parts and not how the semantic layer is modelled or what an analytics developer builds against. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Hacen Benkhedah, Joaquin Recio Huertas, Matilda Hyka and Oliver Huth, written here from SAP's abstract; the recording is not yet published.
Be the First to Understand Joule Work's Agentic ThinkingBe the First to Understand Joule Work's Agentic ThinkingA Devtoberfest 2026 session on the agent harness behind agentic thinking in Joule Work: generic operating-system tools in a gVisor-isolated sandbox instead of hand-wired domain functions, a react loop, a warm pool of sandboxes torn down after each task, tenant-separated skill loading, and placeholder tokens the agent never sees swapped for real credentials at the egress path. A skill is a folder with a SKILL.md carrying metadata and instructions, and where it reaches a system, an SAP connectivity JSON that declares each connector by ORD ID with its guardrails — GET allowed by default, POST, PUT, PATCH and DELETE requiring human approval, everything else blocked. The demo uploads a cost-centre skill through the skills view, then has agentic thinking delegate over A2A through Agent Gateway to a custom agent built in Joule Studio, whose MCP tools read cost centres from an S/4HANA Cloud system, and ends by turning the result into a PDF; the Joule Studio trace is what shows the tool call actually happened.SAP Developers, published 2026-10-15
Build your first agent with Joule Studio in a pro-code wayBuild your first agent with Joule Studio in a pro-code wayThe command line interface of Joule Studio, which the atlas holds as @sap/joule-work-dev-cli-early-adopters, carries an agent from a structured intent through generated product requirements documentation and wired APIs to a deployment on Joule Studio's SAP-managed runtime, in one guided flow. SAP's abstract names the stages of that pipeline and promises working code at the end; what the generated requirements and APIs look like is not described. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Charan Ravikumar, Evgenii Skrebtcov, Maria Kondratyeva and Simon Endres, written here from SAP's abstract; the recording is not yet published.
Building agentic applications with SAP HANA CloudBuilding agentic applications with SAP HANA CloudA CAP application extended with semantic search and agent features on top of SAP HANA Cloud's vector engine and SAP AI Core, built in a hands-on workshop. The abstract names the parts, CAP, the vector engine and AI Core, and the two additions: semantic search, the retrieval half of retrieval-augmented generation, and LLM-supported agent capabilities inside the application, which is agent tooling. Which embedding model, which CAP runtime and how the agent calls its tools are not stated. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Hui Li, Ritty Joseph, Shraddha Shetty and Tanuja Jadhav, written here from SAP's abstract; the recording is not yet published.
Building Agentic Workflows with n8n in Joule StudioBuilding Agentic Workflows with n8n in Joule StudioA Devtoberfest 2026 session, JS-31, on SAP-managed n8n inside Joule Studio, shown as a labs preview on a blocked-invoice scenario: a solution made of assets, an intent refined by the web agent into requirements and then a specification, and the generated workflow opened in the n8n editor that Joule Studio connects to its own n8n tenant, with the generated files committed through GitHub. The nodes carry the other edges — the human-in-the-loop node is built on SAP Task Center, and SAP AI Core is where model providers are configured centrally instead of per developer. It ends in Joule chat, where the approval task the workflow created is listed, opened and completed.SAP Developers, published 2026-10-08
Building Code-Based AI Agents on the BAIPBuilding Code-Based AI Agents on the BAIPA Devtoberfest 2026 session on writing the agent yourself rather than configuring one, which is the agent tooling edge: an agent is a model with tools, skills, memory and context around it, and the session reads the code of one built in CAP as a LangGraph state graph, with an agent node that calls the model, a tools node holding the MCP clients, and the edge between them looping until no tool is needed. It then shows the shorter route, a CDS service annotated for the agent protocol with its instructions and skills in an agent.md file. SAP AI Core carries both, with the CAP service in front of it as middleware so the credentials never reach the browser, and that is what cap-agent-ui5-webui is demonstrated against: added as a dependency, it gives the annotated service a UI5 chat interface that can be deployed rather than only previewed. A Python multi-agent application on Cloud Foundry, where an orchestrator delegates to per-stack specialists so no single model sees every tool, closes the session.published 2026-10-09
Building custom Joule Agents with SAP Knowledge GraphBuilding custom Joule Agents with SAP Knowledge GraphCustom Joule Agents built in a hands-on with SAP Knowledge Graph and Joule Studio: discovering APIs from a user's intent, grounding an agent's answers in business context, and integrating data products for SAP Business Data Cloud. The agents are SAP Joule's; the Knowledge Graph is not an atlas entry, and the abstract does not say which Joule Studio edition the exercises use. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Jan Portisch, Lucas Kiesow, Pavithra G K and Rafael Martin, written here from SAP's abstract; no recording is announced.
Building enterprise agent extensions with the Joule Studio solutionBuilding enterprise agent extensions with the Joule Studio solutionExtending SAP's standard agents with third-party integrations and business actions in Joule Studio: agents that run a process across systems, call an external service, put an approval step in the middle and bring the result back into the business context, which is what SAP Joule's agents do and what Joule Studio, classic edition is in the atlas. The abstract names Joule Studio without saying which edition the exercise uses, and lists outcomes rather than the steps built. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Charan Ravikumar, Jacob Hornberger, Maria Kondratyeva and Michael Zadikowitsch, written here from SAP's abstract; the recording is not yet published.
CAP: The Road Ahead - Simplicity in an AI EraCAP: The Road Ahead - Simplicity in an AI EraDevtoberfest 2026 session CAP10, from the head of SAP's Cloud Application Programming Model: forty minutes of live building rather than slides, on the argument that the cheapest code in an AI project is code nobody has to generate. Claude Code builds an invoice-matching workspace from cds init onwards, and each step is one the framework answers rather than the agent: a 42-line domain model that @sap/cds serves as OData and Fiori elements with a status flow, data privacy and change-tracking annotations that produce audit log entries in the console and would reach the SAP Audit Log service once deployed, an imported S/4HANA supplier data product, and semantic matching from a local embedding model after @cap-js/ai is added. The last three steps are annotations: @mcp beside @odata turns the service into an MCP server that a second Claude session queries through @cap-js/mcp, an agent annotation adds the A2A protocol with an agent card and an audit log entry for the agent task, and a skill file gives the agent the matching policy.SAP Developers, published 2026-09-25
Combining AI Agents with the power of SAP HANA embedded ML (part 1)Combining AI Agents with the power of SAP HANA embedded ML (part 1)Devtoberfest 2026 session DAT-12, the first of two parts, in which Vitaliy Rudnytskiy does a data scientist's work against the embedded machine learning of SAP HANA Cloud by talking to an agent. The session first takes an agent apart into its LLM, its tools, its memory and the loop between them, then stacks the Predictive Analysis Library under the hana-ml Python wrapper and that under the HANA AI toolkit, whose tools an agent calls from plain English in a notebook to preview a sales refunds table, split it into train and predict tables, run a time-series check and train an AutoML forecast, keeping what it decided in Markdown memory files. That is the agent tooling edge; the same toolkit is then started as an MCP server over stdio and over streamable HTTP and reached from a coding agent and from Joule Work's desktop, which is where the live demo partly fails and the failure is shown.published 2026-09-22
Connecting AI agents to the ABAP RESTful application programming modelConnecting AI agents to the ABAP RESTful application programming modelJoule Studio, classic edition connects Joule Agents to applications built with the ABAP RESTful application programming model through actions and skills, calling the OData services those applications expose their business objects through: the tools an agent may call, which is the agent tooling concern seen from the ABAP side. The abstract promises alternative integration patterns and does not name them. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Leon Karlau, written here from SAP's abstract; the recording is not yet published.
Deploy, review, break, fix: Govern cloud transports with agility and AIDeploy, review, break, fix: Govern cloud transports with agility and AIFive BTP services in one delivery chain, as the abstract lays it out: a transport is triggered in SAP Content Agent Service, tested in SAP Cloud Transport Management, its failure is raised by SAP Alert Notification service for SAP BTP and remediated by a SAP Joule agent with SAP Automation Pilot, and SAP Cloud Logging keeps the history for root-cause analysis. The chain from alert to remediation is the operations automation concern; what the Joule agent decides on its own is not in the abstract. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Biser Simeonov, Daniel Funkert, Sven Rullmann and Thorsten Sandfuchs, written here from SAP's abstract; the recording is not yet published.
Discover fast-track implementation of SAP Cloud ERP with AIDiscover fast-track implementation of SAP Cloud ERP with AISAP's implementation practice for SAP S/4HANA Cloud Public Edition and the AI-driven tooling SAP says is changing stages of a project, with faster and more predictable deployments, less manual effort and lower risk as the stated outcomes. The abstract names the product, an external here, and no tool; the edge is to SAP Joule because SAP's AI tooling for implementation in the sibling sessions TM109, TM263 and TM265 is Joule for Consultants, and whether this session shows it is not stated. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Anurag Barua and Khaled MUSILHY, written here from SAP's abstract; the recording is not yet published.
Discover how SAP Joule for Consultants transforms cloud implementationsDiscover how SAP Joule for Consultants transforms cloud implementationsA customer's use of SAP Joule for Consultants in a cloud transformation: grounding project data, running fit-to-standard workshops faster and keeping teams aligned, followed by the technical architecture behind those capabilities and an early road map preview on feasibility for developers and enterprise architects. The edge is to SAP Joule, of which Joule for Consultants is the offering for consultants and has no entry of its own here; the abstract leaves the customer as a placeholder and the architecture to the session. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Philipp Kandziora and Yi Hsuan Lin, written here from SAP's abstract; the recording is not yet published.
Experience core foundational capabilities of SAP Cloud ERPExperience core foundational capabilities of SAP Cloud ERPGuided exercises in SAP S/4HANA Cloud Public Edition, which SAP calls the execution backbone of the Autonomous Enterprise: validating AI capabilities against master data for industry and domain needs, generating AI-driven KPIs and reporting summaries. The product is an external here and the abstract names no AI feature by name; the edge is to SAP Joule, SAP's AI layer across its applications and the one entry the AI capabilities of SAP Cloud ERP attach to, which the abstract itself does not name. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Akshat Kharial, Ankush Thareja and Nises Soni, written here from SAP's abstract; the recording is not yet published.
From Intent to Arcade: Building Joule*Bert with Joule Studio and AI-Assisted Pro CodeFrom Intent to Arcade: Building Joule*Bert with Joule Studio and AI-Assisted Pro CodeA Devtoberfest 2026 AI-track session that takes a Q*bert-style arcade game, written as an Easter egg for colleagues, through every phase Joule Studio runs: intent analysis with its clarifying questions, a product requirements document, a specification with its task list, generated code, generated tests and deployment. The knowledge-graph lookup reports that the game maps to no enterprise process and the flow adjusts, and the presenter edits the requirements by hand when the first version declares sound out of scope. He then pushes the project to GitHub, clones it and initialises the jl command line so that Joule Studio's MCP servers are wired into the coding agent in VS Code, where mobile arrow keys were added afterwards; applications could not yet be deployed to the Joule Studio runtime, so this one runs on Kyma.SAP Developers, published 2026-10-01
From intent to extension: Joule and the future of solution extensibilityFrom intent to extension: Joule and the future of solution extensibilityHow Joule turns natural-language intent into extensions across SAP Autonomous Suite: intent-based agent extensions, enriching the agents SAP delivers, packaging options for partners and what SAP calls a harmonised extensibility experience. The edges are to SAP Joule, which does the translating, and to Extensibility, the concern; the abstract names the directions and no feature that ships today. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Amitha Kamath, Oren Shatil and Richard Kuba, written here from SAP's abstract; the recording is not yet published.
Generate agentic workflows using SAP-managed n8n in Joule StudioGenerate agentic workflows using SAP-managed n8n in Joule StudioSAP-managed n8n inside Joule Studio generates a workflow from a business intent a developer states, and the workflow is then tested and deployed, consuming line-of-business application APIs, events and agents in SAP Business AI Platform: process automation with the workflow generated from intent, and agent tooling where the workflow calls agents. The generated workflow sends notifications to the Joule Work mobile app of SAP Joule, to Microsoft Teams or to Slack. SAP's abstract names the pieces and not how the generation or the n8n hosting works. A two-hour hands-on TechEd 2026 session (Tuesday 27 October, Berlin), presented by Rama Sulakshani Murari, Rumen Dimitrov, Seshadri Sreenivas Ramanarayanan and Venugopal Chembrakalathil, written here from SAP's abstract; the recording is not yet published.
Get to know our AI-enhanced mobile apps across the Autonomous EnterpriseGet to know our AI-enhanced mobile apps across the Autonomous EnterpriseA demo of the Joule Work mobile app, part of SAP Joule, and selected SAP mobile apps, showing the mobile AI features meant for using SAP Autonomous Suite on the go, followed by the mobile AI patterns and how to build your own Mobile apps with SAP Business AI Platform. The abstract names the apps and the patterns and states no feature or tool, so what building your own involves is not said. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Sandeep Tetali and Thilo Berndt, written here from SAP's abstract; the recording is not yet published.
How to implement business AI capabilities in ABAP CloudHow to implement business AI capabilities in ABAP CloudA Devtoberfest 2026 session (ABA-32) on embedding AI in an ABAP Cloud application and on making SAP Joule aware of what that application can do. The first demo implements two features of a RAP travel app with the ABAP AI SDK: a determination on an uploaded receipt that sends the image together with the allowed categories and transaction types to a model reached through an intelligent scenario, then writes the extracted description, category, currency and amount back to the expense entity; and a recommendation function, triggered by a side effect on the trip title, that proposes a trip type with a score the Fiori UI sorts the proposals by and leaves the business user to accept — which is LLM integration from ABAP code. The second demo builds a capability for SAP Joule in the Joule Studio code editor in VS Code, with a scenario that extracts a trip title from the user's intent and calls an OData service in the ABAP backend through a BTP destination, deploys it and asks the Joule test UI for the trip's details; the session states that agents reach ABAP only over governed remote APIs — OData, SQL and MCP — and that automatic grounding of custom OData services in the knowledge graph is upcoming rather than available.published 2026-10-05
Inside Joule Studio runtime: Agent deployment and integrationsInside Joule Studio runtime: Agent deployment and integrationsJoule Studio runtime from the inside: the tools and services SAP manages to deploy, integrate, run, extend and operate agents at scale, and the integrations through the agent gateway and SAP S/4HANA Cloud Private Edition. The edge is to SAP Joule, whose agents the runtime runs; the atlas reaches that runtime through @sap/joule-work-dev-cli-early-adopters, which deploys a solution to it, and the abstract names neither the CLI nor a service by name. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Andre Lamego and Jens Huesken, written here from SAP's abstract; the recording is not yet published.
Joule and related AI offerings from SAP: One platform, many systemsJoule and related AI offerings from SAP: One platform, many systemsSAP Joule run across dozens of SAP systems: the SAP for Me portal, orchestration across systems, configuration and credential management, monitoring and tenant isolation are the topics SAP's abstract lists. It stays on the operating side and says nothing about building on Joule. A TechEd 2026 session (Wednesday 28 October, Berlin; also JW301V, virtual), presented by Lukas Lochner, Marvin Klaus and Mathias Rup, written here from SAP's abstract; the recording is not yet published.
Joule and SAP Knowledge Graph: Context-aware AI across SAP solutionsJoule and SAP Knowledge Graph: Context-aware AI across SAP solutionsThe catalogue carries RA107's abstract under this title, and what it describes is SAP AI Core as the management and orchestration layer of an AI architecture: extending Joule Agents in SAP Joule, the model library in Joule Studio for contextual reasoning, connecting data products from SAP Business Data Cloud, and embedding AI in SAP S/4HANA. The SAP Knowledge Graph the title names does not appear in that text, so the edges rest on the abstract as published, and whether the session follows the title or the abstract is not known until it is recorded. A TechEd 2026 session (Wednesday 28 October, Berlin; also RA110V, virtual), presented by Jan Portisch and Pavithra G K, written here from SAP's abstract; the recording is not yet published.
Joule without walls: From personal skills to enterprise interoperabilityJoule without walls: From personal skills to enterprise interoperabilitySAP Joule connects outward over two protocols, A2A and MCP, which SAP's abstract names as the foundation of its open ecosystem, with Joule Assistants as composable agents and extensibility built in. The session draws the line between a personal extension of Joule and one that needs enterprise governance; the abstract does not say where that line falls. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Mathis Boerner and Thomas Mueller, written here from SAP's abstract; the recording is not yet published.
Knowledge graph and agent memory: Build an agent that remembersKnowledge graph and agent memory: Build an agent that remembersThe knowledge graph engine in SAP HANA Cloud as an agent's memory: what the engine, the graph side of graph, spatial and document data, does in an agentic workflow, how an agent keeps what it learns there, the state agent tooling holds between turns, and the SAP AI Core integration through which the database calls LLMs and tabular foundation models such as SAP-RPT-1. The abstract names the engine, the memory role and the AI Core link and does not say how the memory is written or read. DA205 on Tuesday 27 October is the 45-minute talk on the same engine, with a near-identical abstract and a different cast. A two-hour hands-on TechEd 2026 session (Wednesday 28 October, Berlin), presented by Christoph Morgen, Jan Zwickel, Markus Fath and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
Meet Joule Studio and Build your First AI AgentMeet Joule Studio and Build your First AI AgentA Devtoberfest 2026 session from the product manager of Joule Studio, walking one agent through the whole path the tool defines: an intent, the problem statement and goals a coding agent derives from it, the business context it takes from the SAP knowledge graph, and the solution type it proposes with a stated intent fit. The demo is a collections agent that drafts dunning emails: the product requirements document names the metrics and the human-in-the-loop review, the technical specification lists the artifacts to build — the MCP tools among them — and the build is followed by a business test run against business partner 10001, technical unit tests, and deployment to the managed runtime, where the agent and its MCP server appear as deployed assets. Two points shape how it is used rather than what it produces: every asset is a file, editable in the web editor or in the code view and pushable to git, and the same solution can be built from local pro-code tools; n8n workflows are stated as delivered out of the box inside the studio.SAP Developers, published 2026-09-24
Real Pro-Code Development with Joule StudioReal Pro-Code Development with Joule StudioA Devtoberfest 2026 AI-track session that runs one agent build across both of Joule Studio's paths. Playing a procurement manager, one presenter states the intent in the browser, answers the clarifying questions, watches the fit-gap analysis name the S/4HANA APIs the use case needs, and pushes the intent and requirements document to GitHub; the other clones it and carries on in a terminal, logging in with the jl command line against her landscape URL and running its init command to fetch Joule Studio's skills for OpenCode. From there the coding agent writes the specification, the discovered API specifications, the MCP translation and the agent's Python file with its model configuration and evaluation scenarios, which is the edge to Agent tooling; the skills themselves, which SAP says not to edit but which a developer may add to, are the edge to Agent guidance.SAP Developers, published 2026-10-01
SAP BDC and AI: A Perfect MatchSAP BDC and AI: A Perfect MatchA Devtoberfest 2026 data-track session (DAT-22) in which Business Data Cloud's CTO sets out how SAP Business Data Cloud feeds SAP's business AI platform: data products whose primary persistence is an object store and whose semantics are kept with them, the one domain model that links a supplier in Ariba to a supplier in S/4HANA, and the SAP knowledge graph, a triple store running in SAP HANA Cloud and queried with SPARQL, that SAP Joule consults before answering. The live demo asks Joule for the available data products and the top ten open purchase orders, with the data product query agent compiling SQL over virtual tables and a space rendering a dashboard, which is the cataloguing side of this: a central registry, the Unified Customer Landscape, that every activated data product is registered in. The Q&A covers where the knowledge graph lives and what a customer may extend, base policies that turn into filter conditions on an agent's queries, and Joule Studio as the place to build your own agents and data products.SAP Developers, published 2026-09-29
SAP BDC in Business AI Platform: Contextualize and ReasonSAP BDC in Business AI Platform: Contextualize and ReasonA Devtoberfest 2026 session (DAT-31) that places SAP Business Data Cloud as the contextualise-and-reason pillar of the SAP Business AI Platform, between the build pillar of Joule Studio and Integration Suite and the govern pillar of AI Agent Hub. It covers data products described with open resource discovery and core schema notation metadata, a data product creation agent that assembles a derived data product for overdue billing documents from the billing document and customer products and shows its lineage and fields; the data products a line-of-business application brings being readable by Joule without a BDC subscription; and the SAP-managed knowledge graph that maps business entities and their relationships for agents, held as graph data in the SAP HANA Cloud knowledge graph engine as RDF triples queried with SPARQL. The closing demo has SAP Joule answer head-count and purchase-order questions, with the generated SQL passed through a data product query that adds the restriction policy defined for that user in cloud identity services, which is why the session stands for cataloguing and lineage as much as for the products it names.SAP Developers, published 2026-10-06
SAP Joule for Consultants: Unified knowledge for requirements and designsSAP Joule for Consultants: Unified knowledge for requirements and designsFit-to-standard analysis as a consultant on a cloud transformation project: connecting an organisation's data to SAP Joule for Consultants through SAP AI Core, getting answers from SAP knowledge and that content, then building an expert, loading project files and running guided prompts. The edges are to SAP Joule, of which Joule for Consultants is a part, and to SAP AI Core, named as the connection path; how the data is grounded is left to the session. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Anantharaman Ravi, Natalie Han, Sachin Kaura and Yi Hsuan Lin, written here from SAP's abstract; the recording is not yet published.
SAP’s compositional design system: Craft enterprise UIs with AI on the flySAP’s compositional design system: Craft enterprise UIs with AI on the flySAP's compositional design system is the engine behind the generated interface in Joule Work, the front of SAP Joule: SAP's abstract says AI assembles the UI at runtime from primitives and composites under a body of design knowledge, inside a brand-safe design system, and that the session covers the architecture that keeps the result consistent. A third shape of Generative UI beside the two the capability describes, since here the model composes the interface at runtime. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Philip Miseldine and Sophia Levens, written here from SAP's abstract; the recording is not yet published.
The road map for SAP Joule for Consultants—your go-to SAP consulting toolThe road map for SAP Joule for Consultants—your go-to SAP consulting toolSAP's road map for SAP Joule for Consultants, which the abstract describes as becoming the tool for SAP software projects: landscape awareness and secure system connectivity, so that Joule understands an organisation's SAP environments and gives project teams more contextual guidance. The atlas holds no entry for Joule for Consultants, so the piece enters on SAP Joule, the product it is an edition of; the abstract states outcomes and no feature or date. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Natalie Han and Sachin Kaura, written here from SAP's abstract; the recording is not yet published.
Transform business data into AI-supported insightsTransform business data into AI-supported insightsBusiness metrics turned into insights, narratives and recommendations by SAP Joule's agents, with People Intelligence, the SAP Snowflake solution extension for SAP Business Data Cloud and SAP Analytics Cloud connected in SAP Business Data Cloud. The abstract names what is connected and what comes out, and does not say what the exercise builds or where the Snowflake extension sits in it; People Intelligence and the extension are not atlas entries. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Babacar Toure, Maximilian Paul Gander, Neetha Pucknat and San Tran, written here from SAP's abstract; the recording is not yet published.
What's in Daniel Hutzel's brain?What's in Daniel Hutzel's brain?A Devtoberfest 2026 session in the building-apps track, in which Daniel Hutzel and DJ Adams work through what the CAP team is building for agents. A bookshop gets an MCP endpoint beside its OData one from a single annotation, with the plugin writing the coding agent's configuration itself; in the xt-travels sample five services that know nothing about each other are served over MCP and an agent does the orchestration the hand-built UI and its value helps used to do. Hutzel then annotates a service as an agent so the ReAct loop and the choice of model move into the CAP service, and finally drops MCP for a skill that teaches the agent CQL instead, which is where the edges to Serve your application over MCP, Agent tooling and Agent guidance come from. The mechanism under all of it, a plugin file in the package root and event handlers that can be added to any CAP service, is the edge to Plugin authoring.published 2026-10-02
What’s next for agentic analytics and planning in SAP Business Data CloudWhat’s next for agentic analytics and planning in SAP Business Data CloudWhat is next for agentic analytics and planning in SAP Business Data Cloud: SAP Joule's agents automating insight delivery, analysis, narrative generation and modelling tasks. A road map session; the abstract names the four kinds of task and no agent or date. A TechEd 2026 session (Tuesday 27 October, Berlin; also DA806V, virtual), presented by Kristian Ruemmelin, written here from SAP's abstract; the recording is not yet published.
What’s next for the core platform capabilities of SAP Business AI PlatformWhat’s next for the core platform capabilities of SAP Business AI PlatformA preview of the operations layer beneath SAP Business AI Platform: selected road map highlights across Joule Studio runtime, Cloud Identity Services and SAP Cloud Logging, on how enterprise AI is governed and run. The edges are to the two named services and to SAP Joule, whose agents the Joule Studio runtime runs; the abstract names the three areas and no highlight. A TechEd 2026 session (Tuesday 27 October, Berlin; also XP825V, virtual), presented by Andre Lamego and Jens Huesken, written here from SAP's abstract; the recording is not yet published.
Zero token architecture for Joule AgentsZero token architecture for Joule AgentsA pattern for SAP Joule's agents in which an agent maps the solution path once, solves the problem, generates reusable code or configuration and validates it, and later requests reuse that output, so discovery is done by the model and execution is repeatable. The abstract states the pattern as an idea and names no Joule component and no case it was tried on. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by EDGAR ADRIAN MARTINEZ ARCE, written here from SAP's abstract; the recording is not yet published.
🔴 Your Agent Wants to Call SAP. Now What?🔴 Your Agent Wants to Call SAP. Now What?Devtoberfest 2026 session INT-23, on what belongs between an agent and an SAP system. A solution advisor and an enterprise architect point Joule Desktop extensions at MCP servers built on API Management inside SAP Integration Suite, and ask it for business partners, orders and line items from an S/4HANA demo system; asked for the ten largest customers it answers from a sample of 200 orders rather than reading the whole table. They then open the API proxy behind it, where a spike arrest policy caps the backend at ten calls per second and the MCP server is configured to expose only the GET resources of the business-partner API so that an agent cannot create one, which is where the edges to Serve your application over MCP and Rate limiting hold. For totals across all sales orders they send the agent to SAP Business Data Cloud instead of the transactional system, since it aggregates and is read-only, and back through Integration Suite for writes such as journal entries.SAP Developers, published 2026-09-30
🟣 AI Eating Brains! How I Fed Mine to Joule Work Desktop🟣 AI Eating Brains! How I Fed Mine to Joule Work DesktopDevtoberfest 2026 session AI-22. Mathias Kemeter connects his Obsidian note vault to Joule Work Desktop with VaultGate, a local HTTP MCP server he wrote in his spare time because the desktop's sandbox accepts HTTP MCP servers and not stdio ones, and because he wanted the vault reached through Obsidian's own command line rather than by direct file access. The demo builds a Space of management tasks from notes and mailbox together, has the assistant pick up a conventions file in the vault without being told where the reporting rules are, finds a conflict the notes never name by semantic search over local embeddings, and appends a task to a sprint note behind a write confirmation, which is where the edges to Joule Work and Agent workspaces hold. The second half is about the guardrails he had AI choose for the project it then had to live inside: tests and coverage, type safety, static checks, dependency and secret scanning, blocking on commit, on push and in CI.published 2026-10-01
Be the First to Understand Joule Work's Agentic ThinkingBe the First to Understand Joule Work's Agentic ThinkingA Devtoberfest 2026 session on the agent harness behind agentic thinking in Joule Work: generic operating-system tools in a gVisor-isolated sandbox instead of hand-wired domain functions, a react loop, a warm pool of sandboxes torn down after each task, tenant-separated skill loading, and placeholder tokens the agent never sees swapped for real credentials at the egress path. A skill is a folder with a SKILL.md carrying metadata and instructions, and where it reaches a system, an SAP connectivity JSON that declares each connector by ORD ID with its guardrails — GET allowed by default, POST, PUT, PATCH and DELETE requiring human approval, everything else blocked. The demo uploads a cost-centre skill through the skills view, then has agentic thinking delegate over A2A through Agent Gateway to a custom agent built in Joule Studio, whose MCP tools read cost centres from an S/4HANA Cloud system, and ends by turning the result into a PDF; the Joule Studio trace is what shows the tool call actually happened.SAP Developers, published 2026-10-15
Supercharge Joule Desktop: Connect Any SAP API in Minutes with MCP GatewaySupercharge Joule Desktop: Connect Any SAP API in Minutes with MCP GatewayDevtoberfest 2026 session INT-13, in which an SAP solution advisor connects a live S/4HANA system to the desktop experience of Joule Work through the MCP gateway in SAP Integration Suite. One OpenAPI specification covering business partners, sales orders, material stock, billing and purchase requisitions is uploaded as an MCP server artifact, deployed to integration cell with XSUAA inbound authentication, and registered as an MCP connector; the destination behind it is then switched from basic authentication to principal propagation, and the Cloud Connector monitor shows the same question arriving as the presenter's own user. That demonstration is the serve your application over MCP edge, and the second half is Joule Work itself: a Markdown skill that fixes the steps and format of a customer briefing, and a Space the skill rebuilds with each run.SAP Developers, published 2026-09-23
Behind the Autonomous Enterprise: SAP Knowledge Graph and SAP Domain ModelsBehind the Autonomous Enterprise: SAP Knowledge Graph and SAP Domain ModelsThe strategy behind SAP Business AI's intelligence layer: SAP Knowledge Graph for enterprise context, SAP Domain Models for SAP-specific expertise and tabular AI for predictions, unified on SAP AI Core with SAP Document AI. Knowledge Graph and Domain Models are not atlas entries, so the edges rest on the two products the abstract names as the infrastructure and on Predictive models for the tabular AI; nothing is stated about what any of them does in the layer. A TechEd 2026 session (Tuesday 27 October, Berlin; also ST103V, virtual), presented by Jan Portisch and Richard Grandpierre, written here from SAP's abstract; the recording is not yet published.
Hands on SAP Document AI: Next-generation intelligent document processingHands on SAP Document AI: Next-generation intelligent document processingSAP Document AI configured and run by hand: schema design, splitting and classifying documents, enriching the extracted data and custom prompting are the exercises SAP's abstract names. Document extraction from the configuring side, with the schema the participant's own; which document types or models the exercises use is not stated. A TechEd 2026 hands-on session (Thursday 29 October, Berlin), presented by Christoph Lenschow, Tobias Weller and Tomasz Janasz, written here from SAP's abstract; no recording is announced.
How SAP Document AI brings agentic intelligence to business documentsHow SAP Document AI brings agentic intelligence to business documentsSAP Document AI as SAP's abstract now describes it: composable, agent-ready skills for schemaless extraction, classification and summarisation of business documents, so Joule Agents can read and act on unstructured content, plus new document foundation models and agentic validation in its workflow engine. That widens document extraction past the fixed-schema fields the atlas entry records; the abstract names the features and not their release state. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Dheeraj Diwan, Soeren Leibach and Tomasz Janasz, written here from SAP's abstract; the recording is not yet published.
How to Use n8n for Agentic Integrations and Cool InsightsHow to Use n8n for Agentic Integrations and Cool InsightsA Devtoberfest 2026 session on one use case built with n8n, the workflow automation tool SAP announced a partnership with in May 2026: judging the attachments of an automotive warranty claim. A Fiori upload table carries named evidence rows — this line is the invoice, this one the quote — and each uploaded file goes as base64 to an n8n webhook together with the claim context: the position and diagnosis codes, the parts, the amounts and the conversation with the dealer. The flow splits PDF from image, tries text extraction before falling back to a vision prompt, and calls Anthropic's Sonnet with a prompt that names the role, the input, the scoring rules and the response shape; the demo shows a matching invoice scoring 95%, an unrelated dent-removal invoice scoring 5% with the mismatches listed, and a photograph of a rusted suspension arm accepted while an engine bay is rejected against the same claim. The second half is the n8n editor itself — nodes, credentials, the test trace with each node's input and output — and the closing advice is human-in-the-loop flows at the edges of a process rather than automatic adjudication inside it.SAP Developers, published 2026-09-25
Use Free Tier to Create a Service Instance for SAP Document AIUse Free Tier to Create a Service Instance for SAP Document AIFour steps in the SAP BTP cockpit that end with a service key for SAP Document AI: open the cockpit, check the subaccount's entitlements and add the service on the free tier plan if it is not listed, create the instance, then create the key. It names the plans to use in production instead, blocks_of_100, embedded_edition and premium_edition, and stops at the credentials, before any document is uploaded.
Use Free Tier to Subscribe to SAP Document AI Basic UIUse Free Tier to Subscribe to SAP Document AI Basic UIEight steps from an entitled subaccount to the SAP Document AI basic UI open in a browser, and most of them are identity work rather than document work: getting a tenant for Cloud Identity Services, which the basic UI requires, activating the account and establishing trust with the subaccount, then subscribing, creating a user and assigning the Document_Information_Extraction_UI_Templates_Admin role collection. Using the UI to read a document is the subject of Use Machine Learning to Extract Information from Documents with the SAP Document AI Basic UI, which this tutorial names as what to read next.
SAP’s compositional design system: Craft enterprise UIs with AI on the flySAP’s compositional design system: Craft enterprise UIs with AI on the flySAP's compositional design system is the engine behind the generated interface in Joule Work, the front of SAP Joule: SAP's abstract says AI assembles the UI at runtime from primitives and composites under a body of design knowledge, inside a brand-safe design system, and that the session covers the architecture that keeps the result consistent. A third shape of Generative UI beside the two the capability describes, since here the model composes the interface at runtime. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Philip Miseldine and Sophia Levens, written here from SAP's abstract; the recording is not yet published.
🟣 Bring AI into Your ABAP Applications with ISLM: Build, Integrate, and Consume AI Natively🟣 Bring AI into Your ABAP Applications with ISLM: Build, Integrate, and Consume AI NativelyDevtoberfest 2026 session AI-11, from the product manager and product owner of Intelligent Scenario Lifecycle Management: ISLM as the place an AI use case is registered, deployed and operated inside an SAP S/4HANA system, and what has been added to it for generative AI. The demo builds a custom scenario end to end — an intelligent scenario of type generative AI, a connection to SAP AI Core, a GPT-5 mini model, an orchestration flow template that configures data masking, input and output filtering and translation into the user's logged-in language, then prompts with a grounding query over five companies' return-policy documents — and consumes it from an ABAP report through the ABAP AI SDK, which calls the orchestration API and returns the summary as JSON. Two newer pieces follow: SAP RPT, the relational pre-trained transformer for tabular prediction, called with context rows and query rows and answering with a confidence value and no training step; and system-triggered agents, where an application job in the ABAP system starts a billing-creation agent that reaches S/4HANA OData APIs as tools through the agent gateway with principal propagation. The closing availability matrix states the generative AI capabilities for on-premise and private cloud from the 2021 release, with SAP notes to implement on lower ones.SAP Developers, published 2026-09-24
🟣 Enable Your AI application to Run on Multiple Models to Ensure Resilience and Compliance🟣 Enable Your AI application to Run on Multiple Models to Ensure Resilience and ComplianceDevtoberfest 2026 session AI-21. A cross product owner on the SAP AI Core team gives the reasons an AI application ends up on more than one model — a model down at the hyperscaler, a data centre that is not allowed to run it, a version being deprecated — and runs a joke app that answers from Gemini 2.5 Flash in EU10 and from Claude 4.5 Haiku in Asia-Pacific. The walk through AI Core's parts is where the edges hold: prompts kept as templates in the prompt registry, imported through the launchpad and the APIs or synced as YAML from a git repository (Prompt management); the evaluation service scoring one prompt across up to four models per run on built-in or model-as-judge metrics, and the prompt optimizer generating variants against one metric (Agent evals); and the orchestration service harmonising the providers behind one message format with a priority-sorted fallback list (LLM integration). The session also states where a metric has to be designed rather than picked: an exact-JSON match scores an email generator at zero, so the joke app's custom metric judges topic and family-appropriateness instead.SAP Developers, published 2026-10-01
ABAP AI SDK powered by ISLM - How to implement your own AI use cases in ABAPABAP AI SDK powered by ISLM - How to implement your own AI use cases in ABAPA Devtoberfest 2026 ABAP-track session (ABA-44) on the ABAP AI SDK: an intelligent scenario development object holds the model and its version, so the ABAP code asks for an API, sends a prompt and reads the completion with its token counts and finish reason, and swapping the model is a change to that object rather than to the code. Four demos go through the ABAP line by line — a bare completion, a system prompt with the temperature set to 0.2, tool calls where the model asks for order details and the result goes back into the message container, and a JSON response schema that returns category, severity and goodwill as fields a program can act on — and a fifth replaces the API with the SDK's own mocks so unit tests run with no network call, which is what the LLM integration edge on the ABAP door rests on. The closing availability matrix separates base scenarios, available across SAP S/4HANA on-premise, private edition, public cloud and the SAP BTP ABAP environment, from the orchestration service and SAP RPT, shown for on-premise and private cloud with transport-based correction instructions back to release 2022 and not yet for the public cloud editions.SAP Developers
Agentic CAP: Build MCP servers and enterprise AI agentsAgentic CAP: Build MCP servers and enterprise AI agentsCAP applications become AI agents over the Model Context Protocol and the Agent2Agent protocol, which is the serve your application over MCP concern, and SAP AI Core is the LLM integration through which AI is embedded in a CAP app, with recommendations from the SAP-RPT-1 model as the abstract's example. The abstract names the two protocols and the one model and does not say which packages carry them. A two-hour TechEd 2026 session in a hands-on room (Tuesday 27 October, Berlin), presented by Daniel Hutzel, Daniel Schlachter, Marc Huber and Sami Lechner, written here from SAP's abstract; the recording is not yet published.
Agentic memory: Knowledge graph engine and recall in SAP HANA CloudAgentic memory: Knowledge graph engine and recall in SAP HANA CloudThe knowledge graph engine in SAP HANA Cloud as an agent's memory: what the engine, the graph side of graph, spatial and document data, does in an agentic workflow, how an agent keeps what it learns there, the state agent tooling holds between turns, and the SAP AI Core integration through which the database calls LLMs and tabular foundation models such as SAP-RPT-1. The abstract names the engine, the memory role and the AI Core link and does not say how the memory is written or read. DA263 on Wednesday 28 October is a two-hour hands-on on the same engine with a different cast. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Markus Fath and Shraddha Shetty, written here from SAP's abstract; the recording is not yet published.
AI-enabled administration: Automating log analysis with generative AI hubAI-enabled administration: Automating log analysis with generative AI hubA log analysis tool for incident work, built in SAP Business Application Studio with the generative AI hub feature, which SAP AI Core ships as its LLM integration by its own documentation: it automates root-cause analysis over system errors and masks sensitive data. SAP's abstract states the tool's jobs and not how the hub is called, what the masking covers or which model answers. A TechEd 2026 session (Wednesday 28 October, Berlin), with no speaker listed in the catalogue at the time of writing, written here from SAP's abstract; the recording is not yet published.
Behind the Autonomous Enterprise: SAP Knowledge Graph and SAP Domain ModelsBehind the Autonomous Enterprise: SAP Knowledge Graph and SAP Domain ModelsThe strategy behind SAP Business AI's intelligence layer: SAP Knowledge Graph for enterprise context, SAP Domain Models for SAP-specific expertise and tabular AI for predictions, unified on SAP AI Core with SAP Document AI. Knowledge Graph and Domain Models are not atlas entries, so the edges rest on the two products the abstract names as the infrastructure and on Predictive models for the tabular AI; nothing is stated about what any of them does in the layer. A TechEd 2026 session (Tuesday 27 October, Berlin; also ST103V, virtual), presented by Jan Portisch and Richard Grandpierre, written here from SAP's abstract; the recording is not yet published.
Bring "developers.sap.com" Into Your Dev Environment: SAP Developer Context for AI Coding AgentsBring "developers.sap.com" Into Your Dev Environment: SAP Developer Context for AI Coding AgentsDevtoberfest 2026 session FA-11: a tour of the rebuilt developers.sap.com by the team that runs it, from the administration screens behind the home page to the agent interfaces in front of it. The site is a CAP application on SAP HANA Cloud and SAP BTP, open-sourced in full, and the half of the session that places it here is how its content reaches an agent: every tutorial is also served as markdown, a coding agent is detected and given that version instead of the HTML, a well-known agent card advertises what the site offers, and SAP Developers MCP answers questions about tutorials, news and a reader's own completion history in Claude Code and Joule Desktop, over OAuth or a personal access token. Behind the answers sit two things working together: a knowledge graph in the HANA database over 1400 tutorials and 11,000 concepts, and SAP AI Core for the Joule interactions and the embeddings, with the agent harness written for the site rather than taken off a shelf. Where neither MCP nor A2A is available, the same content is published as skills.SAP Developers, published 2026-09-25
Build AI agents and applications natively on SAP HANA CloudBuild AI agents and applications natively on SAP HANA CloudSAP HANA Cloud as the base for agentic applications on SAP Business AI Platform: the session goes through CAP, the SAP HANA Cloud vector engine and SAP AI Core, with architecture patterns and lessons learned from building AI-supported applications. SAP's abstract names the three parts of that stack and the vector engine as the database's feature in it, and describes none of the patterns. A TechEd 2026 session (Wednesday 28 October, Berlin; also DA113V, virtual), presented by Christoph Morgen and Shraddha Shetty, written here from SAP's abstract; the recording is not yet published.
Build business differentiation with SAP AI CoreBuild business differentiation with SAP AI CoreSAP AI Core as the orchestration layer for enterprise AI, worked through with SAP's engineers: extend Joule Agents with models from its library, ground them in SAP Business Data Cloud products, embed them in SAP S/4HANA flows, then govern, scale and monitor them from prototype to production. The abstract says what the layer does for an agent and not which services carry each step. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by David Knaack, Franziska Dobrigkeit, Hadi Hares and Jonas Israel, written here from SAP's abstract; the recording is not yet published.
Building agentic applications with SAP HANA CloudBuilding agentic applications with SAP HANA CloudA CAP application extended with semantic search and agent features on top of SAP HANA Cloud's vector engine and SAP AI Core, built in a hands-on workshop. The abstract names the parts, CAP, the vector engine and AI Core, and the two additions: semantic search, the retrieval half of retrieval-augmented generation, and LLM-supported agent capabilities inside the application, which is agent tooling. Which embedding model, which CAP runtime and how the agent calls its tools are not stated. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Hui Li, Ritty Joseph, Shraddha Shetty and Tanuja Jadhav, written here from SAP's abstract; the recording is not yet published.
Building Agentic Workflows with n8n in Joule StudioBuilding Agentic Workflows with n8n in Joule StudioA Devtoberfest 2026 session, JS-31, on SAP-managed n8n inside Joule Studio, shown as a labs preview on a blocked-invoice scenario: a solution made of assets, an intent refined by the web agent into requirements and then a specification, and the generated workflow opened in the n8n editor that Joule Studio connects to its own n8n tenant, with the generated files committed through GitHub. The nodes carry the other edges — the human-in-the-loop node is built on SAP Task Center, and SAP AI Core is where model providers are configured centrally instead of per developer. It ends in Joule chat, where the approval task the workflow created is listed, opened and completed.SAP Developers, published 2026-10-08
Building Code-Based AI Agents on the BAIPBuilding Code-Based AI Agents on the BAIPA Devtoberfest 2026 session on writing the agent yourself rather than configuring one, which is the agent tooling edge: an agent is a model with tools, skills, memory and context around it, and the session reads the code of one built in CAP as a LangGraph state graph, with an agent node that calls the model, a tools node holding the MCP clients, and the edge between them looping until no tool is needed. It then shows the shorter route, a CDS service annotated for the agent protocol with its instructions and skills in an agent.md file. SAP AI Core carries both, with the CAP service in front of it as middleware so the credentials never reach the browser, and that is what cap-agent-ui5-webui is demonstrated against: added as a dependency, it gives the annotated service a UI5 chat interface that can be deployed rather than only previewed. A Python multi-agent application on Cloud Foundry, where an orchestrator delegates to per-stack specialists so no single model sees every tool, closes the session.published 2026-10-09
CAP: The Road Ahead - Simplicity in an AI EraCAP: The Road Ahead - Simplicity in an AI EraDevtoberfest 2026 session CAP10, from the head of SAP's Cloud Application Programming Model: forty minutes of live building rather than slides, on the argument that the cheapest code in an AI project is code nobody has to generate. Claude Code builds an invoice-matching workspace from cds init onwards, and each step is one the framework answers rather than the agent: a 42-line domain model that @sap/cds serves as OData and Fiori elements with a status flow, data privacy and change-tracking annotations that produce audit log entries in the console and would reach the SAP Audit Log service once deployed, an imported S/4HANA supplier data product, and semantic matching from a local embedding model after @cap-js/ai is added. The last three steps are annotations: @mcp beside @odata turns the service into an MCP server that a second Claude session queries through @cap-js/mcp, an agent annotation adds the A2A protocol with an agent card and an audit log entry for the agent task, and a skill file gives the agent the matching policy.SAP Developers, published 2026-09-25
Enriching AI models with SAP AI Core in SAP Business Data CloudEnriching AI models with SAP AI Core in SAP Business Data CloudThe integration between SAP Business Data Cloud and SAP AI Core, through which data products with their semantics feed AI models for benchmarking, custom AI development and agentic analytics and applications. The abstract names the two products and the three uses and states nothing about how the data reaches AI Core or what the integration consists of. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by San Tran and Sandy Tran, written here from SAP's abstract; the recording is not yet published.
How to implement business AI capabilities in ABAP CloudHow to implement business AI capabilities in ABAP CloudA Devtoberfest 2026 session (ABA-32) on embedding AI in an ABAP Cloud application and on making SAP Joule aware of what that application can do. The first demo implements two features of a RAP travel app with the ABAP AI SDK: a determination on an uploaded receipt that sends the image together with the allowed categories and transaction types to a model reached through an intelligent scenario, then writes the extracted description, category, currency and amount back to the expense entity; and a recommendation function, triggered by a side effect on the trip title, that proposes a trip type with a score the Fiori UI sorts the proposals by and leaves the business user to accept — which is LLM integration from ABAP code. The second demo builds a capability for SAP Joule in the Joule Studio code editor in VS Code, with a scenario that extracts a trip title from the user's intent and calls an OData service in the ABAP backend through a BTP destination, deploys it and asks the Joule test UI for the trip's details; the session states that agents reach ABAP only over governed remote APIs — OData, SQL and MCP — and that automatic grounding of custom OData services in the knowledge graph is upcoming rather than available.published 2026-10-05
Joule and SAP Knowledge Graph: Context-aware AI across SAP solutionsJoule and SAP Knowledge Graph: Context-aware AI across SAP solutionsThe catalogue carries RA107's abstract under this title, and what it describes is SAP AI Core as the management and orchestration layer of an AI architecture: extending Joule Agents in SAP Joule, the model library in Joule Studio for contextual reasoning, connecting data products from SAP Business Data Cloud, and embedding AI in SAP S/4HANA. The SAP Knowledge Graph the title names does not appear in that text, so the edges rest on the abstract as published, and whether the session follows the title or the abstract is not known until it is recorded. A TechEd 2026 session (Wednesday 28 October, Berlin; also RA110V, virtual), presented by Jan Portisch and Pavithra G K, written here from SAP's abstract; the recording is not yet published.
Knowledge graph and agent memory: Build an agent that remembersKnowledge graph and agent memory: Build an agent that remembersThe knowledge graph engine in SAP HANA Cloud as an agent's memory: what the engine, the graph side of graph, spatial and document data, does in an agentic workflow, how an agent keeps what it learns there, the state agent tooling holds between turns, and the SAP AI Core integration through which the database calls LLMs and tabular foundation models such as SAP-RPT-1. The abstract names the engine, the memory role and the AI Core link and does not say how the memory is written or read. DA205 on Tuesday 27 October is the 45-minute talk on the same engine, with a near-identical abstract and a different cast. A two-hour hands-on TechEd 2026 session (Wednesday 28 October, Berlin), presented by Christoph Morgen, Jan Zwickel, Markus Fath and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
SAP AI Core deep dive: Models, agents, and business context at scaleSAP AI Core deep dive: Models, agents, and business context at scaleSAP AI Core read as the management and orchestration layer of an AI architecture, beyond the model runtime: SAP's abstract lists extending Joule Agents, the model library in Joule Studio for contextual reasoning, connecting data products from SAP Business Data Cloud, and embedding AI in SAP S/4HANA. It names the connections and not the APIs behind them. A TechEd 2026 session (Tuesday 27 October, Berlin; also RA107V, virtual), presented by Franziska Dobrigkeit and Hadi Hares, written here from SAP's abstract; the recording is not yet published.
SAP Joule for Consultants: Unified knowledge for requirements and designsSAP Joule for Consultants: Unified knowledge for requirements and designsFit-to-standard analysis as a consultant on a cloud transformation project: connecting an organisation's data to SAP Joule for Consultants through SAP AI Core, getting answers from SAP knowledge and that content, then building an expert, loading project files and running guided prompts. The edges are to SAP Joule, of which Joule for Consultants is a part, and to SAP AI Core, named as the connection path; how the data is grounded is left to the session. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Anantharaman Ravi, Natalie Han, Sachin Kaura and Yi Hsuan Lin, written here from SAP's abstract; the recording is not yet published.
SAP-RPT and TabPFN: Get started with tabular foundation modelsSAP-RPT and TabPFN: Get started with tabular foundation modelsTabular foundation models, SAP-RPT and TabPFN, in a hands-on with SAP and Prior Labs: the model families first, then predictions run through SAP AI Core with a workflow built on tabular orchestration and connected to the participant's own data for real-time predictions. A predictive models session with the models as the subject; the abstract does not name the SDK or API the workflow is built with. A TechEd 2026 hands-on session (Thursday 29 October, Berlin), presented by Eliott Kalfon, Janick Zaehringer-Frasch, Johannes Hoehne, Katharina Schell, Nilay Mehta and Sherene Tan, written here from SAP's abstract; no recording is announced.
Ship your own sandboxed AI operations agent to Kyma in two hoursShip your own sandboxed AI operations agent to Kyma in two hoursAn operations agent built and then broken on purpose: the abstract has participants deploy a reasoning agent to SAP BTP, Kyma runtime, connect it to SAP AI Core, give it observability over the runtime and cause a failure for it to diagnose, the operations automation concern with an agent doing the diagnosis. Patterns for cost control and monitoring are promised at the end; the agent framework and how the sandbox is drawn are not named. A TechEd 2026 session (Tuesday 27 October, Berlin, two hours), presented by Christian Lechner, Piotr Tesny, Thorsten Sandfuchs and Vipin VijayKumar, written here from SAP's abstract; the recording is not yet published.
Stop guessing, start counting: How generative AI fixed an inventory messStop guessing, start counting: How generative AI fixed an inventory messAn inventory-counting application a business built on SAP Business AI Platform with SAP HANA Cloud and generative AI, to replace recount lists kept by gut feel across SAP ERP Central Component, SAP S/4HANA and Microsoft Excel; the talk promises the app, its architecture and what went wrong. The generative AI part is LLM integration from application code; the abstract names HANA Cloud and generative AI as the two building blocks and says nothing about how either is used. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Ranjeet Kumar, written here from SAP's abstract; the recording is not yet published.
Unlocking Tabular Foundation Models: From Experimentation to ProductionUnlocking Tabular Foundation Models: From Experimentation to ProductionA Devtoberfest 2026 session (AI-41) on taking tabular prediction from a playground to a deployment. It sets tabular foundation models against a model trained per use case and against language models reading rows as text, explains in-context learning as examples plus the rows whose target column is missing, and tries SAP RPT 1.6 on a train-delay dataset in the RPT playground, including the column and row importance it returns with the prediction. The same prediction is then rebuilt on SAP AI Core, where the tabular orchestration service plays the part the orchestration service plays for language models: a data destination, a table artifact with its CSN schema and a scenario configuration registered once at design time, after which a predict call passes only the query rows, the scenario configuration and a context-selection strategy. The last demo runs those same calls in natural language through the aicore-skills plugin in a coding agent, and one of them only resolves once the agent is told which scenario configuration to use.SAP Developers, published 2026-10-15
Behind the Autonomous Enterprise: SAP Knowledge Graph and SAP Domain ModelsBehind the Autonomous Enterprise: SAP Knowledge Graph and SAP Domain ModelsThe strategy behind SAP Business AI's intelligence layer: SAP Knowledge Graph for enterprise context, SAP Domain Models for SAP-specific expertise and tabular AI for predictions, unified on SAP AI Core with SAP Document AI. Knowledge Graph and Domain Models are not atlas entries, so the edges rest on the two products the abstract names as the infrastructure and on Predictive models for the tabular AI; nothing is stated about what any of them does in the layer. A TechEd 2026 session (Tuesday 27 October, Berlin; also ST103V, virtual), presented by Jan Portisch and Richard Grandpierre, written here from SAP's abstract; the recording is not yet published.
Get hands on with tabular AI and forecasting models in SAP HANA CloudGet hands on with tabular AI and forecasting models in SAP HANA CloudPrediction and forecasting as predictive models inside SAP HANA Cloud, worked through hands-on: tabular AI models such as SAP-RPT-1 for on-the-fly predictions, time series foundation models for ad hoc forecasts, and the AutoML in the predictive analysis library. The abstract names the model kinds and the library and does not say how a model is called from SQL or from an application. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Christoph Morgen, Markus Fath, Ritty Joseph and Tanuja Jadhav, written here from SAP's abstract; the recording is not yet published.
How We Make Tabular Predictions in 2026 with TabPFNHow We Make Tabular Predictions in 2026 with TabPFNA Devtoberfest 2026 session, AI-32, on why a table needs a model of its own: a language model reasons its way to a plausible number, while a tabular foundation model takes the table as context in one forward pass and learns from its features statistically. That is predictive models from both ends — a scikit-learn-shaped fit and predict in a notebook over a heart-disease data set, predicted class probabilities and SHAP values for which features drove the outcome, then the same model reached as an MCP tool by a coding agent that is asked which current customers are most likely to churn. The presenter is from the lab that publishes TabPFN; the Q&A puts it beside SAP's own tabular foundation model, which she says she has not used.SAP Developers, published 2026-10-08
SAP-RPT and TabPFN: Get started with tabular foundation modelsSAP-RPT and TabPFN: Get started with tabular foundation modelsTabular foundation models, SAP-RPT and TabPFN, in a hands-on with SAP and Prior Labs: the model families first, then predictions run through SAP AI Core with a workflow built on tabular orchestration and connected to the participant's own data for real-time predictions. A predictive models session with the models as the subject; the abstract does not name the SDK or API the workflow is built with. A TechEd 2026 hands-on session (Thursday 29 October, Berlin), presented by Eliott Kalfon, Janick Zaehringer-Frasch, Johannes Hoehne, Katharina Schell, Nilay Mehta and Sherene Tan, written here from SAP's abstract; no recording is announced.
Unlock predictive and generative AI with your data in SAP HANA CloudUnlock predictive and generative AI with your data in SAP HANA CloudThe AI features SAP lists for SAP HANA Cloud: the function libraries for tabular prediction and forecasting, where predictive models run inside the database, the vector engine, the knowledge graph engine, which is graph, spatial and document data put to generative use, and SQL to LLM calls. The abstract names the engines and the use cases they are meant for and gives no detail of any one of them. A TechEd 2026 session (Tuesday 27 October, Berlin; also DA204V, virtual), presented by Christoph Morgen and Javier Martin, written here from SAP's abstract; the recording is not yet published.
Unlocking Tabular Foundation Models: From Experimentation to ProductionUnlocking Tabular Foundation Models: From Experimentation to ProductionA Devtoberfest 2026 session (AI-41) on taking tabular prediction from a playground to a deployment. It sets tabular foundation models against a model trained per use case and against language models reading rows as text, explains in-context learning as examples plus the rows whose target column is missing, and tries SAP RPT 1.6 on a train-delay dataset in the RPT playground, including the column and row importance it returns with the prediction. The same prediction is then rebuilt on SAP AI Core, where the tabular orchestration service plays the part the orchestration service plays for language models: a data destination, a table artifact with its CSN schema and a scenario configuration registered once at design time, after which a predict call passes only the query rows, the scenario configuration and a context-selection strategy. The last demo runs those same calls in natural language through the aicore-skills plugin in a coding agent, and one of them only resolves once the agent is told which scenario configuration to use.SAP Developers, published 2026-10-15
🟣 Enable Your AI application to Run on Multiple Models to Ensure Resilience and Compliance🟣 Enable Your AI application to Run on Multiple Models to Ensure Resilience and ComplianceDevtoberfest 2026 session AI-21. A cross product owner on the SAP AI Core team gives the reasons an AI application ends up on more than one model — a model down at the hyperscaler, a data centre that is not allowed to run it, a version being deprecated — and runs a joke app that answers from Gemini 2.5 Flash in EU10 and from Claude 4.5 Haiku in Asia-Pacific. The walk through AI Core's parts is where the edges hold: prompts kept as templates in the prompt registry, imported through the launchpad and the APIs or synced as YAML from a git repository (Prompt management); the evaluation service scoring one prompt across up to four models per run on built-in or model-as-judge metrics, and the prompt optimizer generating variants against one metric (Agent evals); and the orchestration service harmonising the providers behind one message format with a priority-sorted fallback list (LLM integration). The session also states where a metric has to be designed rather than picked: an exact-JSON match scores an email generator at zero, so the joke app's custom metric judges topic and family-appropriateness instead.SAP Developers, published 2026-10-01
🟣 Bring AI into Your ABAP Applications with ISLM: Build, Integrate, and Consume AI Natively🟣 Bring AI into Your ABAP Applications with ISLM: Build, Integrate, and Consume AI NativelyDevtoberfest 2026 session AI-11, from the product manager and product owner of Intelligent Scenario Lifecycle Management: ISLM as the place an AI use case is registered, deployed and operated inside an SAP S/4HANA system, and what has been added to it for generative AI. The demo builds a custom scenario end to end — an intelligent scenario of type generative AI, a connection to SAP AI Core, a GPT-5 mini model, an orchestration flow template that configures data masking, input and output filtering and translation into the user's logged-in language, then prompts with a grounding query over five companies' return-policy documents — and consumes it from an ABAP report through the ABAP AI SDK, which calls the orchestration API and returns the summary as JSON. Two newer pieces follow: SAP RPT, the relational pre-trained transformer for tabular prediction, called with context rows and query rows and answering with a confidence value and no training step; and system-triggered agents, where an application job in the ABAP system starts a billing-creation agent that reaches S/4HANA OData APIs as tools through the agent gateway with principal propagation. The closing availability matrix states the generative AI capabilities for on-premise and private cloud from the 2021 release, with SAP notes to implement on lower ones.SAP Developers, published 2026-09-24
Building agentic applications with SAP HANA CloudBuilding agentic applications with SAP HANA CloudA CAP application extended with semantic search and agent features on top of SAP HANA Cloud's vector engine and SAP AI Core, built in a hands-on workshop. The abstract names the parts, CAP, the vector engine and AI Core, and the two additions: semantic search, the retrieval half of retrieval-augmented generation, and LLM-supported agent capabilities inside the application, which is agent tooling. Which embedding model, which CAP runtime and how the agent calls its tools are not stated. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Hui Li, Ritty Joseph, Shraddha Shetty and Tanuja Jadhav, written here from SAP's abstract; the recording is not yet published.
Conversational search for the Cloud Integration capabilityConversational search for the Cloud Integration capabilityCloud Integration content becomes searchable in natural language through three architectures SAP's abstract names: MCP servers, retrieval-augmented generation and knowledge graphs, set against the work of analysing and governing a growing SAP Integration Suite tenant. The abstract names the three and does not say which is built or how they compare. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Vadim Klimov, written here from SAP's abstract; the recording is not yet published.
Building trusted applications on SAP Business AI Platform by designBuilding trusted applications on SAP Business AI Platform by designBuilding cloud applications on SAP Business AI Platform with security and compliance built in: the identity, connectivity, governance and security services SAP groups under the platform, secure-by-design development, and authorisation and access controls for AI agents. The edges are to Authorization and to Tool governance, the concern of what an agent may call with which authorisations; the abstract names the service categories and no service by name. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Christian Cohrs and Regine Schimmer, written here from SAP's abstract; the recording is not yet published.
From APIs to Agent Tools: How MCP Gateway changes what Integration meansFrom APIs to Agent Tools: How MCP Gateway changes what Integration meansThe opening session of the Devtoberfest 2026 integration track, in which two product managers for SAP Integration Suite set out why the suite puts an MCP gateway between agents and backend systems, and then build one. The demo turns an HTTP endpoint and its OpenAPI specification into MCP tools on the integration cell runtime, does the same on top of an existing API-centric integration, and shows the policies tab where authentication through an external provider, quotas, spike arrest and IP filtering sit, plus the trace of the JSON-RPC calls in monitoring and the agent they are earmarked against in analytics. That is where the serve your application over MCP and tool governance edges hold; RFCs and BAPIs as sources are stated as supported, and MCP federation, custom domains and edge integration cell as roadmap.SAP Developers, published 2026-09-23
Govern AI-supported actions across enterprise systemsGovern AI-supported actions across enterprise systemsGoverning what an AI agent may do once it takes business actions across enterprise systems, which is the Tool governance concern, with SAP Integration Suite as the place it is enforced. The abstract lists the mechanisms, scoped APIs, event-driven workflows, runtime policy enforcement, exception handling and observability across SAP and third-party systems, and names no Integration Suite feature behind any of them. A TechEd 2026 session (Tuesday 27 October, Berlin; also IN200V, virtual), presented by Finny Babu and Piyush Gakhar, written here from SAP's abstract; the recording is not yet published.
Intelligent, governed, and agentic integrations with SAP Integration SuiteIntelligent, governed, and agentic integrations with SAP Integration SuiteSAP Integration Suite positioned as the control plane that connects and governs agentic workflows across SAP and third-party systems, set against the abstract's claim that exposing back ends directly to AI brings security, compliance and cost risks. That governing role is the Tool governance concern; the abstract promises recent innovations and names none. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Finny Babu and Piyush Gakhar, written here from SAP's abstract; the recording is not yet published.
Model context protocol (MCP) unlocked: Enable governed access to AI agentsModel context protocol (MCP) unlocked: Enable governed access to AI agentsThe MCP Gateway in SAP Integration Suite: the place policy, security and analytics are applied to a curated set of MCP tools before an AI agent reaches enterprise tools and APIs through it, tool governance done in the integration layer and agent access to your systems routed through one gateway. The abstract names the gateway and its three functions and does not say how tools are curated, which policies exist or how the agent authenticates. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Bruno Renzo, Emily Mui, Markus Winter and Sunny Kapoor, written here from SAP's abstract; the recording is not yet published.
OData entity as a governed query surface for agents, not a toolOData entity as a governed query surface for agents, not a toolAn OData entity, generated from the annotations a service already carries, as the surface an agent queries over SAP data: filterable, selectable and sortable fields, authorisation injected on the server side, and a bound query cost, instead of the entity as a tool. SAP's abstract sets this against the MCP gateway in SAP Integration Suite, where exposing an API is the easy part and getting an agent to pick the right one is not, which is the tool governance concern read through OData. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Aleksandr Ivanov and Evgenii Shirokikh, written here from SAP's abstract; the recording is not yet published.
Powering Enterprise-Ready Agentic AI with SAP Integration SuitePowering Enterprise-Ready Agentic AI with SAP Integration SuiteA Devtoberfest 2026 session (INT-31) from SAP Integration Suite product management on the MCP gateway. The demo creates an MCP server in a design package from an API already deployed on the tenant, exposes two of its 300-odd resources as tools, attaches authentication and quota policies on a policies tab, and publishes the deployed endpoint as an AI product in Developer Hub of API Management, where an agent subscribes and receives a token, URL, key and secret; the calls then show up in monitoring, in message processing logs and in the analytics dashboard, which is the MCP exposure and the tool governance the edges rest on. Three AI features inside Cloud Integration follow: a content migration agent that converts a PI/PO Java mapping into a Groovy script and generates a second integration flow for its lookup, memory profiling during a flow simulation, and root-cause analysis on a failed message processing log.SAP Developers, published 2026-10-07