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S/4HANA Custom Development - What happens in case of errors in BAPIs or RAP BOs?S/4HANA Custom Development - What happens in case of errors in BAPIs or RAP BOs?A Devtoberfest 2026 session on what a custom S/4HANA process does when a BAPI or a RAP business object fails. It is framed from project work rather than product development, with the same issues and challenges turning up on project after project, and it offers the ABAP Processing Center, ABAP-PRC, as what fills the gap it names in modern ABAP development. The edges rest on the opening, which states the session's subject as errors in S/4HANA custom development, read as error handling on the ABAP door, and names that framework.SAP Developers, published 2026-09-21
What's new with draft handling in RAP?What's new with draft handling in RAP?An ABAP-day session at Devtoberfest 2026 on two additions to draft handling in RAP: collaborative draft, where two users work on the same draft instance and a field is locked only while the other is in it, and draft scope, where editing an instance of one draft-enabled business object puts the related instances of a dependent one into draft as well. Andre Fischer shows what each costs in the behaviour definition and projection, the draft query view and its DCL that collaborative draft needs over a table-based business object, and the CDS table entities that remove both the draft query view and the persistence table, with their current restrictions in ABAP analytics and extensibility; the from-scratch generator in ADT grows a checkbox for them. Both demos run against the DMO flight scenario of SAP-samples/abap-platform-refscen-flight, and the last part hides the draft-related features of an OData V4 app in its manifest, which the session gives as the reason a simple create-update-delete app no longer needs a V2 service binding.published 2026-09-21
🔴 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
CAP in the age of AICAP in the age of AISeven live episodes of Hands-on SAP Dev in which DJ Adams works through CAP's AI features with the people who build them, each one a screen-share against a sample project. The first three are @cap-js/mcp: the @mcp annotation on a service, the describe, query and call tools, CQL as the query format, and what authorisation takes out of the tool list. From episode three the run moves to A2A and @cap-js/agents — human approval of an action, agents.md and skills, session persistence, telemetry and sub-agents — and the last two episodes are vector embeddings in CDS, local on SQLite and native on SAP HANA Cloud.published 2026-08-07
CAP in the age of AI #1 - the MCP adapterCAP in the age of AI #1 - the MCP adapterThe episode that opens the series and the first pass over @cap-js/mcp, with four of the people building it on the call. Two of the adapter's tools are worked through: describe, the one an MCP client reaches for first to get the overview of what it may do, and query, which the panel establishes as read-only. It also writes the server entry into a local agent's own configuration file, which episode three comes back to as auto-wiring.published 2026-08-07
CAP in the age of AI #2 - more on the MCP adapterCAP in the age of AI #2 - more on the MCP adapterWhat the query tool costs in tokens, and the third tool @cap-js/mcp registers. Counted against a model running locally under llama.cpp, the same query is 26 tokens as CQL and 173 as CQN, and the tool definition sent with every system prompt drops from around 5,500 tokens to around 600 — the reason CQL became the default format. The call tool then exposes a service's unbound actions and functions, as one generic tool or, behind a flag, one tool per action with its own description and input schema; a question from the chat about extension points gets the answer that the adapter does the tools, which the panel calls a small subset of the protocol.published 2026-08-14
CAP in the age of AI #3 - from MCP to A2ACAP in the age of AI #3 - from MCP to A2AThe episode that finishes @cap-js/mcp with authorisation and then crosses to agents. @requires and @restrict are the same annotations CAP already has, and the plugin reads them to filter the tool list and the describe output per user and per request, so a model is not told about entities the caller cannot reach — where the OData metadata of the same service lists every exposed entity regardless. The second half annotates a service with @agent from @cap-js/agents, which serves it over A2A with an agent card and a chat preview, runs first against a mocked response and then against SAP AI Core bound with cds bind and a hybrid profile, and reuses the MCP adapter's tools rather than defining new ones.published 2026-08-21
CAP in the age of AI #5 - agents wrap-upCAP in the age of AI #5 - agents wrap-upThe agents topic closed out on what sits around the agent rather than inside it, now that the documentation has moved into capire. The chat preview's session is persisted in the database rather than kept in memory, traces go out through @cap-js/telemetry to a self-hosted MLflow under the OpenTelemetry conventions for generative AI, and the panel is explicit that @agent reuses the MCP adapter's code programmatically without serving an MCP endpoint. It ends in the xtravels sample, where a travel agent delegates to a hotel-service sub-agent and reaches a separately started flight service over MCP through the service binding CAP resolves anyway. Earlier in the hour the same agent answers from a model running on the presenter's laptop, reached as an OpenAI-compatible endpoint.published 2026-10-02
CAP in the age of AI #7 - vector embeddings wrap-upCAP in the age of AI #7 - vector embeddings wrap-upThe same embeddings model taken from SQLite to SAP HANA Cloud, then handed to an agent. Locally it is @cap-js/ai that adds the vector functions SQLite lacks and downloads an all-MiniLM L6v2 ONNX model on first start; on HANA natural language processing has to be switched on, the model name is a mandatory argument, the vectors it returns are 768 dimensions, and dimensions must match on both sides of a comparison. HANA itself can be given SAP AI Core as a remote source for other embedding models, which a CDS.ql expression has to inject because the postfix notation only takes what the CDS model holds, and the hour ends with a search function over cosine similarity exposed over @cap-js/mcp, so an agent asked about low output from solar panels calls semantic search instead of writing the query itself.published 2026-10-16
CAP Node.js Expert Session #6 - The MCP AdapterCAP Node.js Expert Session #6 - The MCP AdapterDaniel Schlachter and DJ Adams add @cap-js/mcp to a bookshop service, inspect its describe, query and action tools, and query the catalogue through an AI agent. The session distinguishes this runtime adapter from the development-time MCP server and demonstrates automatic registration of the running service with a local agent. The recording describes the adapter as beta in July 2026, with read-only queries and writes through unbound actions.
CAP-level Data FederationCAP-level Data FederationA Devtoberfest 2026 session (CAP-31) on letting one CAP application read another's data as if it were local. The modelling half is the same for both answers, which is why the two technical edges hold: the provider defines an API service and exports it with CDS export as an npm package carrying the model, mock data and translated texts, the consumer imports it and puts consumption views on top, and only then is it wired either as service-level replication that copies the rows into local tables each time the server starts, or over the SAP HANA synonyms that cds-federation-synonyms generates, with HDI grants on the provider side and a service replacement that redirects each synonym from its mock table to the provider's container. It is worked through on xflights and xtravels, including the local run where CDS watch mocks the imported service from the CSV files inside the package.SAP Developers, published 2026-10-02
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
Configure an MCP Server Created from an HTTP EndpointConfigure an MCP Server Created from an HTTP EndpointDocuments configuring API Management’s HTTP-source MCP server tools, resources, prompts and policies. Resources are selected from GET operations and have URI templates/content types; prompts define User/Assistant messages with optional arguments, alongside MCP policy configuration.
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
MCP Server — SAP Integration SuiteMCP Server — SAP Integration SuiteSAP's own page for the MCP Server artifact in SAP Integration Suite, and where the gateway that runs it is described: MCP clients and API clients reach the same backends through two gateways that share security, traffic management and multi-protocol connectivity. Sets out the three primitives a server may expose — tools derived from API operations with an input and output schema, resources addressed by URI for context rather than action, and prompts as reusable interaction patterns. Says availability depends on the Integration Suite service plan, and points at the three creation paths as separate pages.
Model Context Protocol (MCP)Model Context Protocol (MCP)Frames the Model Context Protocol as the answer to an M-times-N integration problem: one shared protocol turns M agents and N tools into M plus N connections, and one server can be called by any compliant agent. On SAP BTP its implementation section lists an SAP MCP Hub as a no-code way to expose enterprise tools, SAP Integration Suite's MCP Gateway as what it calls the governed path for exposing SAP and non-SAP APIs as MCP-compliant tools, custom SDK-based servers, SAP's MCP servers for development, and an MCP adapter for CDS as a CAP plugin marked coming soon. That is the ground MCP servers covers; for security it points at a separate page.
Model Context Protocol Adapter — CAP guideModel Context Protocol Adapter — CAP guideDocuments @cap-js/mcp and com.sap.cds:cds-adapter-mcp, service annotations, generated describe/query/call tools and local client setup. The guide records Java doc-comment configuration, unbound-action-based data changes, incomplete XSUAA PKCE support and the adapter’s governance boundaries.
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
SAP Meets the Agentic Web: CAP MCP - UI5 WebMCPSAP Meets the Agentic Web: CAP MCP - UI5 WebMCPA Devtoberfest 2026 session (CAP-42) that puts MCP and WebMCP side by side: MCP exposes a backend to an agent, WebMCP exposes the tools of a web page to whatever agent arrives at it, and only Chrome behind a flag and Cloudflare's Kite browser support the second one today. The CAP half starts with two agents scraping a Fiori elements app with Playwright and browser dev tools, then annotates the catalogue service with the MCP protocol through @cap-js/mcp, after which the agent calls the generated describe tool instead of parsing pages. The UI5 half registers a search-authors tool on the browser's model context API inside the same app, with the cross-origin isolation header the API requires, and lists it through the WebMCP Chrome extension — the agent run against it ends on an exhausted Gemini key rather than a result.published 2026-10-16
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
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
From Inbox to Quotation: An AI-Assisted Sales Workbench in React on SAP CAPFrom Inbox to Quotation: An AI-Assisted Sales Workbench in React on SAP CAPA Devtoberfest 2026 session walking live through a sales workbench that turns an incoming customer e-mail into a quotation in S/4HANA, built as a React UI on CAP. It shows the filterable request inbox, the extracted configuration properties with a confidence indicator per characteristic, the variant configurator rendered in React from a JSON schema the configuration service returns, and the link from a derived value back to the place in the e-mail it was read from; the stated reason for the stack is that CAP keeps authentication, destinations and deployment the same in every project, which is where frontend boundary holds. The inbox grows while a user works because a CAP WebSocket plugin pushes new requests into the list — WebSocket.SAP Developers, published 2026-10-09
Strategy and Tool Updates on BW Modernization with SAP Business Data CloudStrategy and Tool Updates on BW Modernization with SAP Business Data CloudDevtoberfest 2026 session DAT-13, in which a product manager for SAP Business Data Cloud sets out the revised BW modernisation strategy, now called optimise, modernise and innovate, and the three tools that carry it. The data product generator transfers BW InfoProviders into local table files in a dedicated BW inbound space of SAP Datasphere, where a data product is still created by hand in the data sharing cockpit; the query template generator turns BW query metadata into an analytical model template in the HANA space; the BW migration assistant, planned to start in Q4 for BW NetWeaver, takes the data flows and transformations below them, and is shown on slides only. That is the loading a warehouse edge, and the demos cover the BW/4HANA cockpit, the ABAP program for the NetWeaver GUI, mass generation with semantics from the BW modeling tools, and the flattening operator for sharing data outside SAP.SAP Developers, published 2026-09-22
Updates on Embedded Analytics in ABAP Cloud for DevelopersUpdates on Embedded Analytics in ABAP Cloud for DevelopersA Devtoberfest 2026 session (ABA-33) on the generator wizards for Embedded Analytics in ABAP Cloud, run by right-clicking a data definition in the ADT Project Explorer. It first names the artefacts a star schema needs, all of them ABAP CDS — cube view at its centre, dimension, text and hierarchy views reached by association, a hierarchy directory, and an InA service definition and binding — and then generates them: the star schema generator reads a view entity's metadata, sorts its fields into dimensions and measures, asks about the ones it cannot decide, offers the dimension views it found and writes an activated cube view; the hierarchy generator produces directory, node, base and definition views plus a maintenance business object with a generated app, which is used to group airlines into alliances before the hierarchy is switched on in the layout of the multi-dimensional analysis app. That is analytic modelling on the ABAP platform, which is what the edges rest on; the outlook names time-dependent hierarchies, translatable texts and dimensions generated from database tables.published 2026-10-05
🔴 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
Data Product Governance in SAP Business Data CloudData Product Governance in SAP Business Data CloudA Devtoberfest 2026 data-track session (DAT-41) on data product governance in SAP Business Data Cloud, released as an MVP: every data product belongs to a domain, a consumer puts one in a cart and raises an access request with a purpose, a target location and acknowledged terms and conditions, and a data steward's approval becomes an access agreement recording who uses which data product where. The demo runs both sides in the BDC cockpit — domains, access management and data product management for the steward, catalog, cart and request for the consumer, with Databricks as the target workspace — and that is what the Cataloguing and lineage edge rests on. It also states the current limits: one default domain until custom domains and subdomains arrive, auto-approved requests for space copies, transports and intelligent content, stewards who cannot yet revoke an active agreement, and an install step still done by hand after approval.SAP Developers
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
Strategy and Tool Updates on BW Modernization with SAP Business Data CloudStrategy and Tool Updates on BW Modernization with SAP Business Data CloudDevtoberfest 2026 session DAT-13, in which a product manager for SAP Business Data Cloud sets out the revised BW modernisation strategy, now called optimise, modernise and innovate, and the three tools that carry it. The data product generator transfers BW InfoProviders into local table files in a dedicated BW inbound space of SAP Datasphere, where a data product is still created by hand in the data sharing cockpit; the query template generator turns BW query metadata into an analytical model template in the HANA space; the BW migration assistant, planned to start in Q4 for BW NetWeaver, takes the data flows and transformations below them, and is shown on slides only. That is the loading a warehouse edge, and the demos cover the BW/4HANA cockpit, the ABAP program for the NetWeaver GUI, mass generation with semantics from the BW modeling tools, and the flattening operator for sharing data outside SAP.SAP Developers, published 2026-09-22
CAP-level Data FederationCAP-level Data FederationA Devtoberfest 2026 session (CAP-31) on letting one CAP application read another's data as if it were local. The modelling half is the same for both answers, which is why the two technical edges hold: the provider defines an API service and exports it with CDS export as an npm package carrying the model, mock data and translated texts, the consumer imports it and puts consumption views on top, and only then is it wired either as service-level replication that copies the rows into local tables each time the server starts, or over the SAP HANA synonyms that cds-federation-synonyms generates, with HDI grants on the provider side and a service replacement that redirects each synonym from its mock table to the provider's container. It is worked through on xflights and xtravels, including the local run where CDS watch mocks the imported service from the CSV files inside the package.SAP Developers, published 2026-10-02
CAP-level Data FederationCAP-level Data FederationA Devtoberfest 2026 session (CAP-31) on letting one CAP application read another's data as if it were local. The modelling half is the same for both answers, which is why the two technical edges hold: the provider defines an API service and exports it with CDS export as an npm package carrying the model, mock data and translated texts, the consumer imports it and puts consumption views on top, and only then is it wired either as service-level replication that copies the rows into local tables each time the server starts, or over the SAP HANA synonyms that cds-federation-synonyms generates, with HDI grants on the provider side and a service replacement that redirects each synonym from its mock table to the provider's container. It is worked through on xflights and xtravels, including the local run where CDS watch mocks the imported service from the CSV files inside the package.SAP Developers, published 2026-10-02
CDS Associations & JoinsCDS Associations & JoinsA Devtoberfest 2026 session from SAP's performance and scalability team on what an ABAP CDS association becomes on SAP HANA, taken as an excerpt from their internal performance training. The CDS edge rests on the three ways an association is used: a path expression and an explicit join both put a left outer join into the generated view, while exposing the association leaves the view without one and adds the join only for a query that asks for its fields, which the session calls join on demand. The data modelling edge is the advice that follows and the demo under it — cardinality written as precisely as the data allows, because the optimiser trusts it, shown with a view whose missing cardinality let SELECT COUNT(*) prune the join and return 18 rows where selecting the columns returned 56, plus the left-hand, right-hand and left-outer-to-inner rewrites that correct cardinalities make possible.SAP Developers, published 2026-10-12
Developing authorizations for business users in SAP Business AI Platform, ABAP environmentDeveloping authorizations for business users in SAP Business AI Platform, ABAP environmentA Devtoberfest 2026 session that walks the places an authorization check has to be written when a RAP business object is implemented, which is the whole of the authorization edge: read restrictions as DCL access controls that become a filter at query time, a child entity inheriting its parent's conditions through an association, the projection layer inheriting rather than changing them, and the same check repeated on the draft side. The ABAP CDS edge holds on that draft half — until 2608 a draft query view was needed above the draft table so a DCL had something to attach to, while a draft table entity is already on CDS level and takes the DCL directly, as long as the associations used in the inherited conditions are redefined on it. Create, update and delete are then taken handler by handler, including the trap that instance authorization reads the buffer and so cannot see the new value a pre-check would reject, and the session closes on in local mode and privileged EML calls.published 2026-10-12
Updates on Embedded Analytics in ABAP Cloud for DevelopersUpdates on Embedded Analytics in ABAP Cloud for DevelopersA Devtoberfest 2026 session (ABA-33) on the generator wizards for Embedded Analytics in ABAP Cloud, run by right-clicking a data definition in the ADT Project Explorer. It first names the artefacts a star schema needs, all of them ABAP CDS — cube view at its centre, dimension, text and hierarchy views reached by association, a hierarchy directory, and an InA service definition and binding — and then generates them: the star schema generator reads a view entity's metadata, sorts its fields into dimensions and measures, asks about the ones it cannot decide, offers the dimension views it found and writes an activated cube view; the hierarchy generator produces directory, node, base and definition views plus a maintenance business object with a generated app, which is used to group airlines into alliances before the hierarchy is switched on in the layout of the multi-dimensional analysis app. That is analytic modelling on the ABAP platform, which is what the edges rest on; the outlook names time-dependent hierarchies, translatable texts and dimensions generated from database tables.published 2026-10-05
Bridging Python and SAP HANA: Inside the sqlalchemy-hana Open-Source DialectBridging Python and SAP HANA: Inside the sqlalchemy-hana Open-Source DialectA Devtoberfest 2026 data-track session (DAT-21) in which one of the maintainers of sqlalchemy-hana, the open-source SQLAlchemy dialect published in SAP's GitHub organisation, opens up what sits between Python and SAP HANA. It walks the five dialect classes that render statements, types, DDL, identifiers and sequences, and the HANA specifics they absorb: the FROM DUMMY a bare SELECT needs, a limit injected when only an offset is given, string compiled to NVARCHAR, and quoted case-sensitive identifiers against Python's lowercase. The rest covers schema migrations with Alembic on HANA's transactional DDL, the recently added async support and vector types, and that HANA Cloud and HANA 2 are supported while HANA 1 is not.SAP Developers, published 2026-09-29
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
Building your knowledge graph on SAP HANA CloudBuilding your knowledge graph on SAP HANA CloudDevtoberfest 2026 session DAT-11, in which two enterprise architects explain what a knowledge graph is and then build one on SAP HANA Cloud. The first half sets the join across three relational tables against an ontology of classes and predicates, the subject-predicate-object triple written as a turtle file, and a SPARQL query over it, and argues that the chain of relationships is what makes a recommendation traceable back to its reasons. The demo, taken from a Discovery Center mission, curates the ontology and the RDF files for an accounts receivable scenario in VS Code, ingests the triples into HANA Cloud with SQL and walks the resulting graph outward from a customer; that is the graph, spatial and document data edge. It closes by separating three things that share the name: the HANA Cloud knowledge graph engine, SAP Knowledge Graph as the data, and the knowledge graph in SAP Business Data Cloud.SAP Developers, published 2026-09-22
CAP in the age of AI #6 - vector embeddingsCAP in the age of AI #6 - vector embeddingsVector embeddings put to work in the incident management sample, answering whether this problem has been seen before. An embedding element of type Vector is calculated and stored from the vector_embedding function, so the database refreshes it whenever the text behind it changes, and cosine_similarity compares it with a freshly embedded string; because a title says little, a scheduled action first summarises each incident's conversation through a model on SAP AI Core and the embedding is taken from that summary. The similar-incidents list is a view joining incidents to themselves, with order and limit set in a before handler on the expanded query, and the vector element excluded from the service, since OData knows nothing about vectors — on SAP HANA Cloud the function is native, while SQLite needs packages added to the project.published 2026-10-09
CAP in the age of AI #7 - vector embeddings wrap-upCAP in the age of AI #7 - vector embeddings wrap-upThe same embeddings model taken from SQLite to SAP HANA Cloud, then handed to an agent. Locally it is @cap-js/ai that adds the vector functions SQLite lacks and downloads an all-MiniLM L6v2 ONNX model on first start; on HANA natural language processing has to be switched on, the model name is a mandatory argument, the vectors it returns are 768 dimensions, and dimensions must match on both sides of a comparison. HANA itself can be given SAP AI Core as a remote source for other embedding models, which a CDS.ql expression has to inject because the postfix notation only takes what the CDS model holds, and the hour ends with a search function over cosine similarity exposed over @cap-js/mcp, so an agent asked about low output from solar panels calls semantic search instead of writing the query itself.published 2026-10-16
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
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 HANA Data Lake Files (HDLF) Basic FunctionalitiesSAP HANA Data Lake Files (HDLF) Basic FunctionalitiesA Devtoberfest 2026 data-track session on SAP HANA data lake files, the managed object store inside SAP HANA Cloud that is provisioned from HANA Cloud Central, priced per API call and per stored gigabyte, and reached with the same REST API whichever hyperscaler it runs on. Two product managers set up an instance with its IP allow list, client certificates and trusts, then upload, list, read and delete files over the WebHDFS REST API and the HDLFS command-line utility — the Object storage half — and cover file versions with snapshots, access policies per file, and chunked upload with a server-side merge. They then link the instance to a HANA database and query a CSV file as a virtual table: SQL on files now runs through a file adapter in the database, while the older path through the data lake relational engine is deprecated.SAP Developers
Building your knowledge graph on SAP HANA CloudBuilding your knowledge graph on SAP HANA CloudDevtoberfest 2026 session DAT-11, in which two enterprise architects explain what a knowledge graph is and then build one on SAP HANA Cloud. The first half sets the join across three relational tables against an ontology of classes and predicates, the subject-predicate-object triple written as a turtle file, and a SPARQL query over it, and argues that the chain of relationships is what makes a recommendation traceable back to its reasons. The demo, taken from a Discovery Center mission, curates the ontology and the RDF files for an accounts receivable scenario in VS Code, ingests the triples into HANA Cloud with SQL and walks the resulting graph outward from a customer; that is the graph, spatial and document data edge. It closes by separating three things that share the name: the HANA Cloud knowledge graph engine, SAP Knowledge Graph as the data, and the knowledge graph in SAP Business Data Cloud.SAP Developers, published 2026-09-22
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
Strategy and Tool Updates on BW Modernization with SAP Business Data CloudStrategy and Tool Updates on BW Modernization with SAP Business Data CloudDevtoberfest 2026 session DAT-13, in which a product manager for SAP Business Data Cloud sets out the revised BW modernisation strategy, now called optimise, modernise and innovate, and the three tools that carry it. The data product generator transfers BW InfoProviders into local table files in a dedicated BW inbound space of SAP Datasphere, where a data product is still created by hand in the data sharing cockpit; the query template generator turns BW query metadata into an analytical model template in the HANA space; the BW migration assistant, planned to start in Q4 for BW NetWeaver, takes the data flows and transformations below them, and is shown on slides only. That is the loading a warehouse edge, and the demos cover the BW/4HANA cockpit, the ABAP program for the NetWeaver GUI, mass generation with semantics from the BW modeling tools, and the flattening operator for sharing data outside SAP.SAP Developers, published 2026-09-22
SAP HANA Data Lake Files (HDLF) Basic FunctionalitiesSAP HANA Data Lake Files (HDLF) Basic FunctionalitiesA Devtoberfest 2026 data-track session on SAP HANA data lake files, the managed object store inside SAP HANA Cloud that is provisioned from HANA Cloud Central, priced per API call and per stored gigabyte, and reached with the same REST API whichever hyperscaler it runs on. Two product managers set up an instance with its IP allow list, client certificates and trusts, then upload, list, read and delete files over the WebHDFS REST API and the HDLFS command-line utility — the Object storage half — and cover file versions with snapshots, access policies per file, and chunked upload with a server-side merge. They then link the instance to a HANA database and query a CSV file as a virtual table: SQL on files now runs through a file adapter in the database, while the older path through the data lake relational engine is deprecated.SAP Developers
Always in Sync — Field-level and event-driven side effects for reactive UIs in RAPAlways in Sync — Field-level and event-driven side effects for reactive UIs in RAPA Devtoberfest 2026 session on side effects in RAP — the declarations in a behaviour definition that tell a draft UI to reload what a change affected, instead of leaving the user to refresh the browser. Field-level side effects recalculate a total price from a determination when a booking fee is entered, including across the association from a child item up to the root entity, and a permissions side effect toggles a description field between read-only and editable; a global side effect is attached to a determine action, fires when the user presses Enter, and only one may exist per business object, which is why the prepare action and a second determine action cannot both carry it. The last part starts a long-running calculation through the background processing framework and raises a business event that the behaviour definition lists as a side effect source and the projection makes public, so the Fiori app is updated with a notification when the work finishes, whether it was triggered by the user or by an application job — the transactional model and the async processing side the edges rest on.published 2026-10-05
What's new with draft handling in RAP?What's new with draft handling in RAP?An ABAP-day session at Devtoberfest 2026 on two additions to draft handling in RAP: collaborative draft, where two users work on the same draft instance and a field is locked only while the other is in it, and draft scope, where editing an instance of one draft-enabled business object puts the related instances of a dependent one into draft as well. Andre Fischer shows what each costs in the behaviour definition and projection, the draft query view and its DCL that collaborative draft needs over a table-based business object, and the CDS table entities that remove both the draft query view and the persistence table, with their current restrictions in ABAP analytics and extensibility; the from-scratch generator in ADT grows a checkbox for them. Both demos run against the DMO flight scenario of SAP-samples/abap-platform-refscen-flight, and the last part hides the draft-related features of an OData V4 app in its manifest, which the session gives as the reason a simple create-update-delete app no longer needs a V2 service binding.published 2026-09-21
Always in Sync — Field-level and event-driven side effects for reactive UIs in RAPAlways in Sync — Field-level and event-driven side effects for reactive UIs in RAPA Devtoberfest 2026 session on side effects in RAP — the declarations in a behaviour definition that tell a draft UI to reload what a change affected, instead of leaving the user to refresh the browser. Field-level side effects recalculate a total price from a determination when a booking fee is entered, including across the association from a child item up to the root entity, and a permissions side effect toggles a description field between read-only and editable; a global side effect is attached to a determine action, fires when the user presses Enter, and only one may exist per business object, which is why the prepare action and a second determine action cannot both carry it. The last part starts a long-running calculation through the background processing framework and raises a business event that the behaviour definition lists as a side effect source and the projection makes public, so the Fiori app is updated with a notification when the work finishes, whether it was triggered by the user or by an application job — the transactional model and the async processing side the edges rest on.published 2026-10-05
How to Build Application Jobs in SAP Business AI Platform, ABAP environmentHow to Build Application Jobs in SAP Business AI Platform, ABAP environmentA Devtoberfest 2026 session on the application job framework in the cloud ABAP environment, built from the repository objects outwards: a class implementing the new application job interface, whose public attributes become the parameters and select options, the application log object it writes to, a job catalog entry that lays out sections, groups and value helps, and a job catalog template that works like a report variant. The demo schedules and monitors runs in the Application Jobs Fiori app, starts a job from a RAP action through the scheduling API under a job user of its own, and debugs one through the template's run-for-testing entry. It closes on the alternatives for work that should not be a job — the background processing framework for short-running work, and RAP events consumed locally or sent over the event mesh — which is the async processing this session covers for SAP BTP ABAP environment.published 2026-09-28
S/4HANA Custom Development - What happens in case of errors in BAPIs or RAP BOs?S/4HANA Custom Development - What happens in case of errors in BAPIs or RAP BOs?A Devtoberfest 2026 session on what a custom S/4HANA process does when a BAPI or a RAP business object fails. It is framed from project work rather than product development, with the same issues and challenges turning up on project after project, and it offers the ABAP Processing Center, ABAP-PRC, as what fills the gap it names in modern ABAP development. The edges rest on the opening, which states the session's subject as errors in S/4HANA custom development, read as error handling on the ABAP door, and names that framework.SAP Developers, published 2026-09-21
The ECC-to-CAP Starter KitThe ECC-to-CAP Starter KitA Devtoberfest 2026 session that builds a CAP service and a Fiori elements list report over an SAP ECC gateway service, on the argument that the CAP project, its contract and its UI survive a later move to SAP S/4HANA while the APIs behind them change. The service integration edge is the body of the demo: the metadata of the ECC flight service is saved as an EDMX file, imported with cds import so the model holds the structure and none of the data, projected read-only into a flight service, and one line of handler code forwards each read to ECC, with filtering, sorting and paging translated down to the older OData version the system speaks. The SAP Destination service edge covers the on-premise destination and the additional properties the walkthrough insists on, and the SAP Business Application Studio edge covers the full-stack dev space, the CAP project wizard, the service center plugin for picking up another OData service, and cds watch run under the profile that uses those credentials.published 2026-10-09
Event Add-On for ERP: All you need to know about the new Event StudioEvent Add-On for ERP: All you need to know about the new Event StudioA Devtoberfest 2026 integration-track session (INT-43) on Event Studio, the browser-based part of the Event Add-On for ERP that defines events in an S/4HANA or ECC backend without code and sends them to a broker. A custom sales-order event is built live — fields picked into a payload that is published as a CDS view entity, a trigger on a classic business object, a static topic — and arrives in a queue on SAP Integration Suite, advanced event mesh, which is where the Event Mesh edge holds. The rest of the demo covers health and exception monitoring in SAP Cloud ALM, the AsyncAPI definition replicated to Event Portal, and the AI assistant and MCP server now inside Event Studio.SAP Developers
IntegrAItion: Event-Driven IntelligenceIntegrAItion: Event-Driven IntelligenceA Devtoberfest 2026 session, INT-33, whose line is that agents fail because they are not informed enough rather than not clever enough, and that events are how they get informed: what an event is, the source-broker-consumer split, notification against data events, and topic filtering as the thing that decides which agents are woken at all and what that costs in tokens. It covers Event Mesh as the concern — topics, subscriptions, filters and queues — and SAP Integration Suite, advanced event mesh as the product, down to its event portal and catalogue, the mesh and cluster managers and distributed tracing. The closing demo sends an S/4HANA product-defect event through the mesh to wake an agent in Joule Studio, which fetches what it still needs over MCP and reports to a person the next morning.SAP Developers, published 2026-10-07
Edge Integration Cell - what's new?Edge Integration Cell - what's new?A Devtoberfest 2026 integration-track session (INT-41) on Edge Integration Cell, the runtime of SAP Integration Suite a customer runs on their own Kubernetes cluster while design, configuration and monitoring stay in the cloud tenant. It names what the customer has to provide — a supported Kubernetes platform, SAP HANA or PostgreSQL, Redis or Valkey as data store, a load balancer — then the Edge Lifecycle Management cockpit with its monthly rolling updates, the inbuilt and the external Cloud Connector options and why a DMZ placement calls for the second, and the adapters available only on Edge: RFC sender, NFS, OFTP2 and UNF. The demo deploys an OFTP-to-file flow to the Edge runtime and shows the same flow rejected when its runtime profile is switched to cloud, which is where the Integration flows edge holds.SAP Developers
From opportunity to decision: Intelligent Credit Checks with AI Adapter in SAP Cloud IntegrationFrom opportunity to decision: Intelligent Credit Checks with AI Adapter in SAP Cloud IntegrationDevtoberfest 2026 session INT-12, in which an integration consultant builds two scenarios around the AI adapter in Cloud Integration. The first integration flow is triggered by a Salesforce opportunity event, reads that customer's history from S/4HANA over its OData APIs and calls a sales agent through the AI adapter, which writes a credit status and a credit rating band back onto the opportunity for the sales representative to act on; the second calls an operations agent from an exception subprocess and raises a Jira ticket carrying the suggested resolution, the related past tickets and the average resolution time recorded for the issue. The session places the adapter among the HTTP, Open Connectors and application-specific adapter routes, names its SAP Generative AI Hub, OpenAI and Claude variants, and gives the build effort as roughly 50 to 60 hours for the OData calls against the adapter configuration's two tabs.SAP Developers, published 2026-09-23
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
SAP Cloud Integration chamber of horrorsSAP Cloud Integration chamber of horrorsA Devtoberfest 2026 integration-track session that goes through anti-patterns in Cloud Integration iFlows: scripts that re-implement flow steps or make external calls, the ESB_Messaging.send role on every sender channel, default flow-step names, dependence on undocumented platform internals, code that rewrites what the Groovy and Java libraries already hold, XML namespaces stripped to simplify XPath, HTTP calls between iFlows on one tenant where ProcessDirect would stay inside it, externalised parameters too few or too many, and MPL attachments left switched on in production. Each one comes with how to spot it — long scripts, jar files for SFTP communication, the design guidelines and upgrade readiness checks, or a rule in the presenter's own CPILint run locally or in a pipeline — and that pass over flow steps, sender roles, adapters and the message processing log is what the Integration flows edge rests on. The questions afterwards cover the GitHub integration in Cloud Integration, the absence of an official MCP server for building iFlows, and whether generated code shifts the choice between mapping, XSLT and scripting.SAP Developers
Edge Integration Cell - what's new?Edge Integration Cell - what's new?A Devtoberfest 2026 integration-track session (INT-41) on Edge Integration Cell, the runtime of SAP Integration Suite a customer runs on their own Kubernetes cluster while design, configuration and monitoring stay in the cloud tenant. It names what the customer has to provide — a supported Kubernetes platform, SAP HANA or PostgreSQL, Redis or Valkey as data store, a load balancer — then the Edge Lifecycle Management cockpit with its monthly rolling updates, the inbuilt and the external Cloud Connector options and why a DMZ placement calls for the second, and the adapters available only on Edge: RFC sender, NFS, OFTP2 and UNF. The demo deploys an OFTP-to-file flow to the Edge runtime and shows the same flow rejected when its runtime profile is switched to cloud, which is where the Integration flows edge holds.SAP Developers
The ECC-to-CAP Starter KitThe ECC-to-CAP Starter KitA Devtoberfest 2026 session that builds a CAP service and a Fiori elements list report over an SAP ECC gateway service, on the argument that the CAP project, its contract and its UI survive a later move to SAP S/4HANA while the APIs behind them change. The service integration edge is the body of the demo: the metadata of the ECC flight service is saved as an EDMX file, imported with cds import so the model holds the structure and none of the data, projected read-only into a flight service, and one line of handler code forwards each read to ECC, with filtering, sorting and paging translated down to the older OData version the system speaks. The SAP Destination service edge covers the on-premise destination and the additional properties the walkthrough insists on, and the SAP Business Application Studio edge covers the full-stack dev space, the CAP project wizard, the service center plugin for picking up another OData service, and cds watch run under the profile that uses those credentials.published 2026-10-09
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
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 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
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
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
🟣 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
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
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 in the age of AICAP in the age of AISeven live episodes of Hands-on SAP Dev in which DJ Adams works through CAP's AI features with the people who build them, each one a screen-share against a sample project. The first three are @cap-js/mcp: the @mcp annotation on a service, the describe, query and call tools, CQL as the query format, and what authorisation takes out of the tool list. From episode three the run moves to A2A and @cap-js/agents — human approval of an action, agents.md and skills, session persistence, telemetry and sub-agents — and the last two episodes are vector embeddings in CDS, local on SQLite and native on SAP HANA Cloud.published 2026-08-07
CAP in the age of AI #3 - from MCP to A2ACAP in the age of AI #3 - from MCP to A2AThe episode that finishes @cap-js/mcp with authorisation and then crosses to agents. @requires and @restrict are the same annotations CAP already has, and the plugin reads them to filter the tool list and the describe output per user and per request, so a model is not told about entities the caller cannot reach — where the OData metadata of the same service lists every exposed entity regardless. The second half annotates a service with @agent from @cap-js/agents, which serves it over A2A with an agent card and a chat preview, runs first against a mocked response and then against SAP AI Core bound with cds bind and a hybrid profile, and reuses the MCP adapter's tools rather than defining new ones.published 2026-08-21
CAP in the age of AI #4 - more on agentsCAP in the age of AI #4 - more on agentsAsking a human first, and telling the agent how to behave. Ordering a book through @cap-js/agents happens without a question being asked; the human-in-the-loop annotation on the action turns the same request into an approve-or-reject step, which the episode follows down to the A2A status update that stores the task in an input-required state in the database — A2A itself being JSON-RPC 2.0 over HTTP with server-sent events for the stream. The rest is instructions on disk: an agents.md in the service's own folder removes the question about how many copies to order, a skill under a skills folder is advertised by its description and read only when the agent decides the case applies, and either file makes the plugin build a deep agent instead of the plain one.published 2026-09-11
CAP in the age of AI #5 - agents wrap-upCAP in the age of AI #5 - agents wrap-upThe agents topic closed out on what sits around the agent rather than inside it, now that the documentation has moved into capire. The chat preview's session is persisted in the database rather than kept in memory, traces go out through @cap-js/telemetry to a self-hosted MLflow under the OpenTelemetry conventions for generative AI, and the panel is explicit that @agent reuses the MCP adapter's code programmatically without serving an MCP endpoint. It ends in the xtravels sample, where a travel agent delegates to a hotel-service sub-agent and reaches a separately started flight service over MCP through the service binding CAP resolves anyway. Earlier in the hour the same agent answers from a model running on the presenter's laptop, reached as an OpenAI-compatible endpoint.published 2026-10-02
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
Content-based Agents with SAP Joule Studio Agent BuilderContent-based Agents with SAP Joule Studio Agent BuilderJoule Studio, classic edition, the capability in SAP Build the page calls Joule Studio, is where an organisation creates and manages its own Joule skills and Joule agents; its Agent Builder is for a custom agent that handles a multi-step task by combining instructions, model-backed planning and reasoning, and a configured set of tools, Joule skills, document resources, MCP servers, or other agents run as subagents. The page states an agent executes inside the calling user's own security context through SAP Cloud Identity Services, and can be tried against a test conversation before deployment. That is the tool-and-turn-taking ground agent tooling covers, here built through Joule Studio rather than in application code.
Custom Joule SkillsCustom Joule SkillsA custom Joule skill is a workflow written to extend what Joule does out of the box for one specific business need, built and deployed through Joule Studio in SAP Build; the page states this is the supported way to extend Joule's built-in capabilities. Through Joule Studio a skill reaches SAP and external APIs via the destinations already configured in the BTP subaccount and Build environment, with the workflow itself versioned, monitored and deployable from the same tool.
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
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
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
Pro-Code AI AgentsPro-Code AI AgentsPro-code agents are the most flexible way the page frames building an agentic workflow on SAP BTP: full autonomy, custom API integrations and algorithms chosen by the developer, set against declarative alternatives such as content-based agents and Joule Scenarios. It names LangGraph as the framework it recommends for production, enterprise-grade agentic workflows, alongside the ReAct pattern as the plan-act-observe loop such an agent runs. That is the ground agent tooling covers, building an agent's own tool-calling loop rather than exposing an application to somebody else's agent.
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
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
🔴 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
Content FilteringContent FilteringContent filtering screens a large language model's input and output for low-quality, irrelevant or unsafe content: the four categories it names being hateful, violent, sexual and vulgar content, checking a request once on the way in and once on the way back. The page states smaller models can do this filtering efficiently, reading perplexity scores to flag anomalies, with the aim that SAP AI Core produces content meeting a stated safety standard, which is the ground content filtering covers on the BTP door.
Data MaskingData MaskingData masking replaces identifiable or confidential text in a prompt with placeholders such as <Person_0> or <Organization_1> before it reaches a large language model, using pattern matching and machine learning to find what to replace. The page states SAP AI Core supports it as a feature and sets out five steps for applying it, defining the masking scope, choosing a technique, preserving the prompt's intent, checking compliance and risk, then testing and monitoring the result. That is the shape data masking takes on the BTP door.
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
🟣 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
Access to Generative AI ModelsAccess to Generative AI ModelsSets out the plain way to call a deployed generative AI model on SAP BTP: a request that carries the prompt, the model and the parameters that control generation, with the same code able to switch between models. It lists data masking, prompt templating and filtering as features that come with the access rather than as code the caller writes, which is the shape LLM integration takes on the BTP door; the page's implementation sections sit behind its steps and were not read.
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
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 in the age of AI #3 - from MCP to A2ACAP in the age of AI #3 - from MCP to A2AThe episode that finishes @cap-js/mcp with authorisation and then crosses to agents. @requires and @restrict are the same annotations CAP already has, and the plugin reads them to filter the tool list and the describe output per user and per request, so a model is not told about entities the caller cannot reach — where the OData metadata of the same service lists every exposed entity regardless. The second half annotates a service with @agent from @cap-js/agents, which serves it over A2A with an agent card and a chat preview, runs first against a mocked response and then against SAP AI Core bound with cds bind and a hybrid profile, and reuses the MCP adapter's tools rather than defining new ones.published 2026-08-21
CAP in the age of AI #5 - agents wrap-upCAP in the age of AI #5 - agents wrap-upThe agents topic closed out on what sits around the agent rather than inside it, now that the documentation has moved into capire. The chat preview's session is persisted in the database rather than kept in memory, traces go out through @cap-js/telemetry to a self-hosted MLflow under the OpenTelemetry conventions for generative AI, and the panel is explicit that @agent reuses the MCP adapter's code programmatically without serving an MCP endpoint. It ends in the xtravels sample, where a travel agent delegates to a hotel-service sub-agent and reaches a separately started flight service over MCP through the service binding CAP resolves anyway. Earlier in the hour the same agent answers from a model running on the presenter's laptop, reached as an OpenAI-compatible endpoint.published 2026-10-02
CAP in the age of AI #6 - vector embeddingsCAP in the age of AI #6 - vector embeddingsVector embeddings put to work in the incident management sample, answering whether this problem has been seen before. An embedding element of type Vector is calculated and stored from the vector_embedding function, so the database refreshes it whenever the text behind it changes, and cosine_similarity compares it with a freshly embedded string; because a title says little, a scheduled action first summarises each incident's conversation through a model on SAP AI Core and the embedding is taken from that summary. The similar-incidents list is a view joining incidents to themselves, with order and limit set in a before handler on the expanded query, and the vector element excluded from the service, since OData knows nothing about vectors — on SAP HANA Cloud the function is native, while SQLite needs packages added to the project.published 2026-10-09
CAP in the age of AI #7 - vector embeddings wrap-upCAP in the age of AI #7 - vector embeddings wrap-upThe same embeddings model taken from SQLite to SAP HANA Cloud, then handed to an agent. Locally it is @cap-js/ai that adds the vector functions SQLite lacks and downloads an all-MiniLM L6v2 ONNX model on first start; on HANA natural language processing has to be switched on, the model name is a mandatory argument, the vectors it returns are 768 dimensions, and dimensions must match on both sides of a comparison. HANA itself can be given SAP AI Core as a remote source for other embedding models, which a CDS.ql expression has to inject because the postfix notation only takes what the CDS model holds, and the hour ends with a search function over cosine similarity exposed over @cap-js/mcp, so an agent asked about low output from solar panels calls semantic search instead of writing the query itself.published 2026-10-16
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
Content FilteringContent FilteringContent filtering screens a large language model's input and output for low-quality, irrelevant or unsafe content: the four categories it names being hateful, violent, sexual and vulgar content, checking a request once on the way in and once on the way back. The page states smaller models can do this filtering efficiently, reading perplexity scores to flag anomalies, with the aim that SAP AI Core produces content meeting a stated safety standard, which is the ground content filtering covers on the BTP door.
Data MaskingData MaskingData masking replaces identifiable or confidential text in a prompt with placeholders such as <Person_0> or <Organization_1> before it reaches a large language model, using pattern matching and machine learning to find what to replace. The page states SAP AI Core supports it as a feature and sets out five steps for applying it, defining the masking scope, choosing a technique, preserving the prompt's intent, checking compliance and risk, then testing and monitoring the result. That is the shape data masking takes on the BTP door.
Document GroundingDocument GroundingDocument Grounding is a managed retrieval-augmented-generation service under the Generative AI Hub on BTP, which SAP's page on SAP AI Core places inside that service: it ingests documents from Amazon S3, SharePoint, SAP Document Management Service, SAP Work Zone or an SFTP server, and handles chunking, embedding and retrieval itself, refreshing content automatically when a source document changes. The page states this managed path is recommended for most enterprise scenarios because it covers the whole lifecycle end to end, and offers a separate Document Grounding Vector API for data that is already chunked and embedded, for cases that need finer control over chunking and metadata.
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
Prompt TemplatingPrompt TemplatingPrompt templating replaces a static prompt with a structured, reusable template whose placeholders are filled in at runtime, which the page says helps LLM responses stay consistent and lets the same instructions be adapted across tasks. On SAP AI Core this is implemented through the Prompt Registry, and the page states that storing prompts as plain strings in code is possible but not recommended. That is prompt management as a stored and managed object rather than a string embedded in the caller.
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
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
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
Prompt TemplatingPrompt TemplatingPrompt templating replaces a static prompt with a structured, reusable template whose placeholders are filled in at runtime, which the page says helps LLM responses stay consistent and lets the same instructions be adapted across tasks. On SAP AI Core this is implemented through the Prompt Registry, and the page states that storing prompts as plain strings in code is possible but not recommended. That is prompt management as a stored and managed object rather than a string embedded in the caller.
🟣 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
CAP in the age of AICAP in the age of AISeven live episodes of Hands-on SAP Dev in which DJ Adams works through CAP's AI features with the people who build them, each one a screen-share against a sample project. The first three are @cap-js/mcp: the @mcp annotation on a service, the describe, query and call tools, CQL as the query format, and what authorisation takes out of the tool list. From episode three the run moves to A2A and @cap-js/agents — human approval of an action, agents.md and skills, session persistence, telemetry and sub-agents — and the last two episodes are vector embeddings in CDS, local on SQLite and native on SAP HANA Cloud.published 2026-08-07
CAP in the age of AI #6 - vector embeddingsCAP in the age of AI #6 - vector embeddingsVector embeddings put to work in the incident management sample, answering whether this problem has been seen before. An embedding element of type Vector is calculated and stored from the vector_embedding function, so the database refreshes it whenever the text behind it changes, and cosine_similarity compares it with a freshly embedded string; because a title says little, a scheduled action first summarises each incident's conversation through a model on SAP AI Core and the embedding is taken from that summary. The similar-incidents list is a view joining incidents to themselves, with order and limit set in a before handler on the expanded query, and the vector element excluded from the service, since OData knows nothing about vectors — on SAP HANA Cloud the function is native, while SQLite needs packages added to the project.published 2026-10-09
CAP in the age of AI #7 - vector embeddings wrap-upCAP in the age of AI #7 - vector embeddings wrap-upThe same embeddings model taken from SQLite to SAP HANA Cloud, then handed to an agent. Locally it is @cap-js/ai that adds the vector functions SQLite lacks and downloads an all-MiniLM L6v2 ONNX model on first start; on HANA natural language processing has to be switched on, the model name is a mandatory argument, the vectors it returns are 768 dimensions, and dimensions must match on both sides of a comparison. HANA itself can be given SAP AI Core as a remote source for other embedding models, which a CDS.ql expression has to inject because the postfix notation only takes what the CDS model holds, and the hour ends with a search function over cosine similarity exposed over @cap-js/mcp, so an agent asked about low output from solar panels calls semantic search instead of writing the query itself.published 2026-10-16
Document GroundingDocument GroundingDocument Grounding is a managed retrieval-augmented-generation service under the Generative AI Hub on BTP, which SAP's page on SAP AI Core places inside that service: it ingests documents from Amazon S3, SharePoint, SAP Document Management Service, SAP Work Zone or an SFTP server, and handles chunking, embedding and retrieval itself, refreshing content automatically when a source document changes. The page states this managed path is recommended for most enterprise scenarios because it covers the whole lifecycle end to end, and offers a separate Document Grounding Vector API for data that is already chunked and embedded, for cases that need finer control over chunking and metadata.
Vector RAG vs Graph RAGVector RAG vs Graph RAGA section introduction rather than the comparison itself: it states that the choice between Vector RAG and Graph RAG depends on the domain and the task, and that Vector RAG is the one to use when the subject area has a clear description and the model must be held to specific data structures and attribute values. The four sub-pages it introduces, two on vector-based and two on graph-based RAG, carry the comparison. It sits on the same retrieval question retrieval-augmented generation answers, without naming CDS, CAP or a store.
Agentic AI Security & GovernanceAgentic AI Security & GovernanceNames seven threat categories agentic AI introduces beyond ordinary application security: prompt injection, excessive agency, supply-chain and model-integrity compromise, memory poisoning, improper output handling, resource abuse and agent-to-agent communication poisoning. Its answer is a defence-in-depth structure of security controls, input validation, privilege management, supply-chain checks, memory segmentation, output validation, execution quotas, secure communication, paired with governance and oversight: audit logging, explainability, human-in-the-loop review, fairness assessment and continuous monitoring. States the reason plainly: an agent decides, chains actions across turns, keeps memory between them and can act on real systems, a different risk profile from a single request-response call. That is the authorisation and audit-trail question tool governance is named for.
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
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
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
Developing authorizations for business users in SAP Business AI Platform, ABAP environmentDeveloping authorizations for business users in SAP Business AI Platform, ABAP environmentA Devtoberfest 2026 session that walks the places an authorization check has to be written when a RAP business object is implemented, which is the whole of the authorization edge: read restrictions as DCL access controls that become a filter at query time, a child entity inheriting its parent's conditions through an association, the projection layer inheriting rather than changing them, and the same check repeated on the draft side. The ABAP CDS edge holds on that draft half — until 2608 a draft query view was needed above the draft table so a DCL had something to attach to, while a draft table entity is already on CDS level and takes the DCL directly, as long as the associations used in the inherited conditions are redefined on it. Create, update and delete are then taken handler by handler, including the trap that instance authorization reads the buffer and so cannot see the new value a pre-check would reject, and the session closes on in local mode and privileged EML calls.published 2026-10-12
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
🔴 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
Configure an MCP Server Created from an HTTP EndpointConfigure an MCP Server Created from an HTTP EndpointDocuments configuring API Management’s HTTP-source MCP server tools, resources, prompts and policies. Resources are selected from GET operations and have URI templates/content types; prompts define User/Assistant messages with optional arguments, alongside MCP policy configuration.
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
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
How to Build Application Jobs in SAP Business AI Platform, ABAP environmentHow to Build Application Jobs in SAP Business AI Platform, ABAP environmentA Devtoberfest 2026 session on the application job framework in the cloud ABAP environment, built from the repository objects outwards: a class implementing the new application job interface, whose public attributes become the parameters and select options, the application log object it writes to, a job catalog entry that lays out sections, groups and value helps, and a job catalog template that works like a report variant. The demo schedules and monitors runs in the Application Jobs Fiori app, starts a job from a RAP action through the scheduling API under a job user of its own, and debugs one through the template's run-for-testing entry. It closes on the alternatives for work that should not be a job — the background processing framework for short-running work, and RAP events consumed locally or sent over the event mesh — which is the async processing this session covers for SAP BTP ABAP environment.published 2026-09-28
SAP BAIP, ABAP environment – How to build partner solutions and get them certifiedSAP BAIP, ABAP environment – How to build partner solutions and get them certifiedA Devtoberfest 2026 session on the two ways a partner ships an ABAP Cloud solution built on SAP BTP ABAP environment, which the session calls the ABAP environment of SAP Business AI Platform: software delivery, where an add-on product is published with the solution ID from SAP Store onboarding and the customer discovers and deploys it into their own system, and service delivery, where the partner operates the same add-on as a multi-tenant SaaS and a new version is deployed rather than published again. That is the ABAP environment edge; the static analysis edge rests on the quality steps shown in the landscape portal, where the Manage Continuous Testing app released with 2608 runs an ATC check variant against a configured system on a recurrence pattern, beside test product version builds and managed test tenants. The second half walks through the SAP Integration and Certification Center process and the three BTP certification options open to an add-on product.SAP Developers, published 2026-10-12
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
Custom Business Logic Extensibility in CAP (CDS-Oyster)Custom Business Logic Extensibility in CAP (CDS-Oyster)A Devtoberfest 2026 session walking @sap/cds-oyster — at version 0.55, with 1.0 stated for Q4 — end to end on a multitenant xtravels, from the application developer's side and the extension developer's side. The application developer adds a submit-for-review action to the status flow and opens exactly one surface for custom code: a separate extension service marked as extensible code, holding a no-op validate action and two read-only helper entities, which the host application calls before the status change; nothing else is extensible, because the annotation defaults to false. The extension developer works in a project whose base model came from cds pull, with test data, a server.js and types from @cap-js/cds-typer added so the UI and code completion work, debugs the handler locally and pushes it as an @sap/cds-mtxs extension, after which the next request rejects a travel over the policy limit without a restart — the code having been stored as an annotation in the tenant's model and run in a Rust WebAssembly sandbox with no database connection, whose queries go back to the CAP runtime as CQL strings, which is tenant extensibility extended from fields to logic.published 2026-10-09
CAP in the age of AI #5 - agents wrap-upCAP in the age of AI #5 - agents wrap-upThe agents topic closed out on what sits around the agent rather than inside it, now that the documentation has moved into capire. The chat preview's session is persisted in the database rather than kept in memory, traces go out through @cap-js/telemetry to a self-hosted MLflow under the OpenTelemetry conventions for generative AI, and the panel is explicit that @agent reuses the MCP adapter's code programmatically without serving an MCP endpoint. It ends in the xtravels sample, where a travel agent delegates to a hotel-service sub-agent and reaches a separately started flight service over MCP through the service binding CAP resolves anyway. Earlier in the hour the same agent answers from a model running on the presenter's laptop, reached as an OpenAI-compatible endpoint.published 2026-10-02
Custom Business Logic Extensibility in CAP (CDS-Oyster)Custom Business Logic Extensibility in CAP (CDS-Oyster)A Devtoberfest 2026 session walking @sap/cds-oyster — at version 0.55, with 1.0 stated for Q4 — end to end on a multitenant xtravels, from the application developer's side and the extension developer's side. The application developer adds a submit-for-review action to the status flow and opens exactly one surface for custom code: a separate extension service marked as extensible code, holding a no-op validate action and two read-only helper entities, which the host application calls before the status change; nothing else is extensible, because the annotation defaults to false. The extension developer works in a project whose base model came from cds pull, with test data, a server.js and types from @cap-js/cds-typer added so the UI and code completion work, debugs the handler locally and pushes it as an @sap/cds-mtxs extension, after which the next request rejects a travel over the policy limit without a restart — the code having been stored as an annotation in the tenant's model and run in a Rust WebAssembly sandbox with no database connection, whose queries go back to the CAP runtime as CQL strings, which is tenant extensibility extended from fields to logic.published 2026-10-09
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