Everything in CAP / Java
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GraphQLUnmapped
September 15th: What's New on developers.sap.comSeptember 15th: What's New on developers.sap.comThomas Jung walks through a week of changes aimed at agentic consumption of developers.sap.com itself: the hosted MCP server gains a published .well-known/mcp.json manifest, curated tools (search_tutorials, get_tutorial_step with a Markdown format option, search_channels), and a listing in the ORD catalog beside its OData, REST and GraphQL APIs. It also documents the site's existing A2A endpoint for the first time and ships a way to turn a tutorial into an installable, cryptographically signed AI Skill with a generated verification script, both concrete instances of agent tooling; separately, five broken GraphQL example queries were fixed and the full SDL is now served, and new sitemap.md, llms.txt fixes and ORD entries round out the site's own metadata publishing.published 2026-09-15
Metadata publishingSAP only
How to rename an OData V4 service?How to rename an OData V4 service?Renaming an OData V4 service binding changes its Service Alias and the resulting service URL, breaking any app already deployed against the old one — shown on a /DMO/TRAVEL-based example in the SAP BTP ABAP environment by unpublishing, renaming and republishing the binding, then reading the new URL back from the OData V4 service catalog's ServiceGroups entry. It weighs that against two alternatives: adding a second service definition and publishing it as a new service version under the same binding, or creating an entirely new service definition and binding, which keeps the original URL live during the cutover.published 2026-07-04
September 15th: What's New on developers.sap.comSeptember 15th: What's New on developers.sap.comThomas Jung walks through a week of changes aimed at agentic consumption of developers.sap.com itself: the hosted MCP server gains a published .well-known/mcp.json manifest, curated tools (search_tutorials, get_tutorial_step with a Markdown format option, search_channels), and a listing in the ORD catalog beside its OData, REST and GraphQL APIs. It also documents the site's existing A2A endpoint for the first time and ships a way to turn a tutorial into an installable, cryptographically signed AI Skill with a generated verification script, both concrete instances of agent tooling; separately, five broken GraphQL example queries were fixed and the full SDL is now served, and new sitemap.md, llms.txt fixes and ORD entries round out the site's own metadata publishing.published 2026-09-15
ODataSAP and community
Adding Immutable Blockchain Proofs to SAP With CAP - Cardano and OData V4Adding Immutable Blockchain Proofs to SAP With CAP - Cardano and OData V4The write-up behind ODATANO, by its author: how a public blockchain gets reachable from CAP as an ordinary OData V4 service rather than through a bespoke client. The premise it starts from is worth the read on its own — SAP systems are trusted but mutable, which is what an immutable anchor is for — and Cardano is chosen for peer-reviewed research and formal methods rather than for popularity. Written as an experiment with feedback invited, not as a recommendation.maxalexweber, published 2026-05-15
AI-assisted full stack development using model context protocol serversAI-assisted full stack development using model context protocol serversMCP servers in Visual Studio Code used to configure, query and change a full-stack application built with CAP, CDS and OData: the agent access to your code concern, a coding assistant reading and changing the project it works in. The abstract names no server, so neither @cap-js/mcp-server nor any other is attached, and it does not say which changes are made. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Sergio Guerrero, written here from SAP's abstract; the recording is not yet published.
Consume Remote Services in a Full-Stack CAP ApplicationConsume Remote Services in a Full-Stack CAP ApplicationExtending the Developer's Guide application with a remote S/4HANA service — connectivity, importing the Business Partner API, and running against it. SAP publishes this as four separate paths: mock server or real S/4HANA Cloud, times Cloud Foundry or Kyma. One entry covers all four, because the difference between them is which backend and which runtime, not what you learn.SAP
Extend SAP SuccessFactors on SAP BTP with the SAP Cloud Application Programming ModelExtend SAP SuccessFactors on SAP BTP with the SAP Cloud Application Programming ModelTwelve tutorials, about two hours, building a side-by-side extension of SuccessFactors on BTP. The spine is remote services: importing the SuccessFactors OData service definitions into a CAP model, then treating them as entities the extension reads and writes through, rather than as an API called from a handler. Indexed as one entry because the parts only make sense in order.SAP
OpenAPIUnmapped
SAP Job Scheduling Service: 🔧 Generate Your Own Client Library from OpenAPI SpecSAP Job Scheduling Service: 🔧 Generate Your Own Client Library from OpenAPI SpecA tutorial on generating a type-safe client library for the SAP Job Scheduling service's REST API from its OpenAPI specification, using the OpenAPI Generator CLI to target Node.js, TypeScript, Java, Python, Go or C#. It walks through OAuth 2.0 client-credentials authentication and the generated client's Jobs API, listing, creating and reading jobs with their cron schedules, and lists what the service's error statuses (400, 401, 404, 409, 429, 503) mean to a caller. It states that the official @sap/jobs-client will be deprecated and tells readers to use a generated client for now.DenisDuev, published 2026-05-04
Serve your application over MCPSAP only
Add MCP capabilities to a CAP serviceAdd MCP capabilities to a CAP serviceA fifteen-minute walkthrough of turning a plain CAP service into an MCP server: annotate the service with @mcp, install @cap-js/mcp, and it is served alongside OData at /mcp/<path>. The part worth reading it for is what happens next — cds watch writes the endpoint into the local agent's own configuration file, so OpenCode or Claude Code can call the service without anyone editing JSON by hand. It is built on the tiny-sample facet, so there is nothing to prepare, and it shows the protocol traffic rather than only the result. Written while the adapter was in beta, and it says so.published 2026-08-13
Agentic AI on BTP: a Multi‑Agent App with Pydantic AIAgentic AI on BTP: a Multi‑Agent App with Pydantic AISplits a single CAP/TypeScript agent that had grown to juggle five BTP MCP servers behind one bloated tool list into btp-multiagent-app, a Python and Pydantic AI rewrite where the Cloud Foundry and BTP Core MCP servers each get a dedicated specialist agent, with an audit log specialist scaffolded but left disabled, behind an orchestrator whose only tools are delegation calls to those specialists, which is the agent-tooling pattern the piece works through. Each specialist authenticates to its MCP server over Streamable HTTP with OAuth 2.1, and a shared module centralises the SAP AI Core GenAI Hub model setup behind two credential layouts, one for local runs and one for the Cloud Foundry service binding, the LLM integration side of the rewrite. Tool lists per agent drop from well over a hundred to a dozen or two, and routing failures become separable from tool-misuse failures by reading the trace.published 2026-05-03
Agentic AI on BTP: a Single Agent with LangGraphAgentic AI on BTP: a Single Agent with LangGraphA CAP TypeScript agent puts a LangGraph StateGraph in front of AzureOpenAiChatClient from @sap-ai-sdk/langchain, reaching SAP AI Core's Generative AI Hub, and lets its tool-calling loop draw on five deployed MCP servers — OData MCP Proxy, CI MCP Server, AI Core MCP Server, BTP MCP Server and BTP CF MCP Server — through @langchain/mcp-adapters' MultiServerMCPClient. Because agent, servers and APIs share one XSUAA tenant, the chat service forwards the signed-in user's own JWT instead of a service account, so each downstream server enforces that user's own authorizations. Past roughly a hundred combined tools the single prompt slows down and stops separating concerns, which is why the author's next post splits it into one specialist agent per MCP server behind an orchestrator.published 2026-05-03
Agentic CAP: Build MCP servers and enterprise AI agentsAgentic CAP: Build MCP servers and enterprise AI agentsCAP applications become AI agents over the Model Context Protocol and the Agent2Agent protocol, which is the serve your application over MCP concern, and SAP AI Core is the LLM integration through which AI is embedded in a CAP app, with recommendations from the SAP-RPT-1 model as the abstract's example. The abstract names the two protocols and the one model and does not say which packages carry them. A two-hour TechEd 2026 session in a hands-on room (Tuesday 27 October, Berlin), presented by Daniel Hutzel, Daniel Schlachter, Marc Huber and Sami Lechner, written here from SAP's abstract; the recording is not yet published.
API Composition: Seamless Enterprise Data Access for Developers and AI AgentsAPI Composition: Seamless Enterprise Data Access for Developers and AI AgentsAPI Composition (formerly Graph, a capability of API Management) curates business data graphs from existing SAP and non-SAP API providers, so a query can navigate and expand relationships across systems through one composed API rather than hand-written integration code. Palak walks through combining SAP S/4HANA warehouse-stock data with Everstream Analytics risk data into one API, then exposing that composed API as an MCP server so an AI agent calls it with the same semantic context — the scenario behind API Management's MCP servers coverage.published 2026-07-27
Examine the details of the Model Context Protocol on startupExamine the details of the Model Context Protocol on startupWhat the MCP adapter actually does when a CAP server boots, watched rather than described — the companion to the tutorial that switches it on.
Expose S/4HANA Cloud OData API as an MCP Server via CAP Node.jsExpose S/4HANA Cloud OData API as an MCP Server via CAP Node.jsA step-by-step walkthrough that wraps SAP S/4HANA Cloud's Outbound Delivery OData v2 API in a CAP Node.js service and exposes it through @cap-js/mcp, so an MCP client can list the generated tools, query the delivery entities and call a custom createDelivery action over JSON-RPC. The remote S/4HANA connection is configured two ways in package.json: direct Basic Authentication credentials for local hybrid testing, and a named BTP destination for the app once deployed to Cloud Foundry.Jacky_Liu1, published 2026-07-29
Expose S/4HANA Cloud OData API as an MCP Server via CAP Node.jsExpose S/4HANA Cloud OData API as an MCP Server via CAP Node.jsA CAP Node.js service imports the S/4HANA Cloud Outbound Delivery OData v2 API's EDMX metadata with cds import, proxies its reads and a custom createDelivery action against it, and annotates the service @protocol: ['odata-v4', 'mcp'] with @cap-js/mcp's per_action_tool setting on, so the custom action gets its own MCP tool rather than one generic call_action. It tests the result with raw JSON-RPC tools/list and tools/call requests before deploying to SAP BTP, Cloud Foundry Runtime.Jacky Liu, published 2026-07-29
From Dashboard to Conversational AI in Minutes: Adding MCP to an Existing CAP ApplicationFrom Dashboard to Conversational AI in Minutes: Adding MCP to an Existing CAP ApplicationA walkthrough of adding @cap-js/mcp to an existing CAP service behind the SuccessFactors Localization Dashboard: two annotations (@odata, @mcp) expose the service over MCP beside its existing OData endpoint, and doc comments added to the 18 entities and their fields are surfaced through the describe tool so a querying model gets business context instead of bare field names. During local development cds watch auto-registers the endpoint in ~/.claude.json, and the author connects the same endpoint to Joule Work Desktop as an MCP connector so users can ask coverage questions in natural language.i533678, published 2026-08-24
From SAP Sales and Service Cloud V2 APIs to AI: Building an MCP Server with CAP Node.jsFrom SAP Sales and Service Cloud V2 APIs to AI: Building an MCP Server with CAP Node.jsA step-by-step CAP Node.js walkthrough that wraps the SAP Sales Cloud V2 Case API as a remote service, then exposes the resulting service over both OData V4 and MCP through a single @protocol: ['odata-v4', 'mcp'] annotation together with @cap-js/mcp's per_action_tool setting. Each CDS action — listCases, getCaseById, createCase, patchCase — becomes its own MCP tool served at /mcp/caseservices, discoverable through tools/list and invoked from a natural-language request.pvsbprasad, published 2026-08-31
MCP Servers are the New Z-TablesMCP Servers are the New Z-TablesA single CAP service exposed as three overlapping MCP servers tools, queried by the same prompt nineteen times, returned the same tool every time — evidence, the author argues, that tool selection rests on the resemblance between a prompt and a tool's description rather than on any binding a where-used list could enumerate before retiring it. It contrasts that setup with @cap-js/mcp, which exposes a whole service as three generic tools instead of one per operation, and quotes the adapter's own beta documentation admitting no rate limiting, audit logging, input validation or approval workflow, and no use as a gateway to SAP Application APIs. From there it names four small Tool governance practices it has adopted: an owner recorded in the tool's own metadata, logging every invocation, deprecating inside the description, and exposing fewer tools.published 2026-08-21
Natural Language Queries for SAP CAP via MCP: The LLM Translates, CDS ExecutesNatural Language Queries for SAP CAP via MCP: The LLM Translates, CDS ExecutesThe division of labour is the argument, and it is in the subtitle: the model turns English into a CDS query and CDS runs it, so nothing generates SQL and nothing hallucinates a join. Schema annotations do the resolving. Long, with the package, the repository and the MCP registry entry all linked.Shahid, published 2026-06-25
The Easiest Way to Expose a CAP Node.js Project as an MCP ServerThe Easiest Way to Expose a CAP Node.js Project as an MCP ServerFrom cds init to a running MCP server in a handful of steps, ending at the MCP Inspector so the result is something you can see rather than something you have to trust. The claim it makes for the plugin is the absence of work: no REST wiring by hand, the CAP application exposed as a server because the package is installed. A walkthrough rather than an argument — the reasoning about what should be exposed lives elsewhere.Jacky Liu, published 2026-07-03
WebSocketUnmapped
Reading Between the Lines: Under-Documented Fiori Elements Capabilities in SAPUI5 1.149Reading Between the Lines: Under-Documented Fiori Elements Capabilities in SAPUI5 1.149Reads SAPUI5 1.149's framework source, not its release notes, to show Fiori Elements shifting side-effect refresh, AI field placeholders and multi-user drafting from controller extensions into what the backing service annotates. Event-driven SideEffects push over a WebSocket channel through @cap-js-community/websocket, while Draft handling gains ABAP RAP's live field locking on CAP Node.js through Sören Leibach's own cap-collaborative-draft plugin. Both rest on Fiori annotations such as Common.SideEffects and CollaborativeDraft.enabled, which the frontend reads rather than requiring a manifest flag.published 2026-07-09
AttachmentsSAP only
CAP Foundry: Engineering SAP CAP Applications from Business Intent with Guardrailed AICAP Foundry: Engineering SAP CAP Applications from Business Intent with Guardrailed AICAP Foundry is a prototype that generates a CAP Node.js project with SAP Fiori elements from a written business requirement, discovering the actual data shape from a chosen source — SQLite, a configured SAP HANA HDI container, offline EDMX, live OData through the SAP Destination service, or approved SAP BTP ABAP objects — instead of inventing one. The generated application can carry a Fiori draft lifecycle with optimistic concurrency via ETags and annotation-driven Fiori elements list and object screens, localized independently of the underlying service contract. Attachments can be added with upload, download and delete, gated on a malware-scan status, and the generated project still has to compile, build and pass its generated tests before the run is accepted.Shahid, published 2026-08-20
Concurrency controlSAP only
Handling Concurrent Updates in SAP CAP JavaHandling Concurrent Updates in SAP CAP JavaAlice and Bob open the same employee record; Bob saves last and quietly erases Alice's change. The lost-update problem stated concretely and then answered in CAP Java, which is the only entry here on the subject — hence the capability.Anjali_Pathak, published 2026-05-26
Data modellingSAP only
Analyze and optimize ABAP Cloud model apps built on core data servicesAnalyze and optimize ABAP Cloud model apps built on core data servicesPerformance anti-patterns in data models built with ABAP CDS under ABAP Cloud applications, and the tools that find them: the abstract names ABAP cross trace, the SQL analyzer (PlanViz) in Visual Studio Code and the SAP HANA database explorer as what the session uses to follow a bottleneck from the application to the database. The anti-patterns are taken from real business applications, which is where the data modelling edge holds; which ones are shown is not in the abstract. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Ingo Braeuninger, Robert Werlich, Steffen Siegmund and Thomas Fiedler, written here from SAP's abstract; the recording is not yet published.
Deep Insert in SAP CAPM Using Composition and Fiori ElementsDeep Insert in SAP CAPM Using Composition and Fiori ElementsParent and children created in one transaction, which composition already gives you in the model — the post is about what Fiori elements does with it, and what the payload looks like when the UI sends both at once.published 2026-05-22
Learn how to define constraints declaratively in your CDS modelLearn how to define constraints declaratively in your CDS modelConstraints expressed in the model rather than checked in a handler — the distinction the atlas draws between input validation the framework enforces and validation somebody writes.SAP
Database connectorsSAP only
Agentic memory: Knowledge graph engine and recall in SAP HANA CloudAgentic memory: Knowledge graph engine and recall in SAP HANA CloudThe knowledge graph engine in SAP HANA Cloud as an agent's memory: what the engine, the graph side of graph, spatial and document data, does in an agentic workflow, how an agent keeps what it learns there, the state agent tooling holds between turns, and the SAP AI Core integration through which the database calls LLMs and tabular foundation models such as SAP-RPT-1. The abstract names the engine, the memory role and the AI Core link and does not say how the memory is written or read. DA263 on Wednesday 28 October is a two-hour hands-on on the same engine with a different cast. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Markus Fath and Shraddha Shetty, written here from SAP's abstract; the recording is not yet published.
Analyze and optimize ABAP Cloud model apps built on core data servicesAnalyze and optimize ABAP Cloud model apps built on core data servicesPerformance anti-patterns in data models built with ABAP CDS under ABAP Cloud applications, and the tools that find them: the abstract names ABAP cross trace, the SQL analyzer (PlanViz) in Visual Studio Code and the SAP HANA database explorer as what the session uses to follow a bottleneck from the application to the database. The anti-patterns are taken from real business applications, which is where the data modelling edge holds; which ones are shown is not in the abstract. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Ingo Braeuninger, Robert Werlich, Steffen Siegmund and Thomas Fiedler, written here from SAP's abstract; the recording is not yet published.
Automate Recurring Data Updates in SAP HANA CloudAutomate Recurring Data Updates in SAP HANA CloudA walkthrough for marking inventory rows stale after 30 days using SAP HANA Cloud's own scheduler: a SQLScript procedure, a CREATE SCHEDULER JOB statement with its 7-field cron pattern, the M_SCHEDULER_JOBS monitoring view, and the matching DROP statements to remove both. It then names where that approach stops and lists the alternatives for scheduling outside the database: SAP Integration Suite's Timer Event, the SAP Job Scheduling service, SAP Automation Pilot for infrastructure commands, and a custom approach for triggering scheduled REST calls from an application.Joni, published 2026-06-11
Build AI agents and applications natively on SAP HANA CloudBuild AI agents and applications natively on SAP HANA CloudSAP HANA Cloud as the base for agentic applications on SAP Business AI Platform: the session goes through CAP, the SAP HANA Cloud vector engine and SAP AI Core, with architecture patterns and lessons learned from building AI-supported applications. SAP's abstract names the three parts of that stack and the vector engine as the database's feature in it, and describes none of the patterns. A TechEd 2026 session (Wednesday 28 October, Berlin; also DA113V, virtual), presented by Christoph Morgen and Shraddha Shetty, written here from SAP's abstract; the recording is not yet published.
Build your custom knowledge layer with SAP HANA CloudBuild your custom knowledge layer with SAP HANA CloudSAP HANA Cloud's multi-model engines, the knowledge graph engine among them, as the base for a custom knowledge layer over the enterprise's data, with SAP Business Data Cloud as the product that includes the database. Graph, spatial and document data put to an AI use; the abstract names the graph engine and not the query language or the vector side. A TechEd 2026 session (Wednesday 28 October, Berlin; also ST108V, virtual), presented by Niklas Siemer and Sebastian Schmidt, written here from SAP's abstract; the recording is not yet published.
Building agentic applications with SAP HANA CloudBuilding agentic applications with SAP HANA CloudA CAP application extended with semantic search and agent features on top of SAP HANA Cloud's vector engine and SAP AI Core, built in a hands-on workshop. The abstract names the parts, CAP, the vector engine and AI Core, and the two additions: semantic search, the retrieval half of retrieval-augmented generation, and LLM-supported agent capabilities inside the application, which is agent tooling. Which embedding model, which CAP runtime and how the agent calls its tools are not stated. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Hui Li, Ritty Joseph, Shraddha Shetty and Tanuja Jadhav, written here from SAP's abstract; the recording is not yet published.
Building an SAP BTP Agent Architecture from Scratch: Python + CAP + HANABuilding an SAP BTP Agent Architecture from Scratch: Python + CAP + HANAA first-person build log of a Flask orchestrator on Cloud Foundry that reduces a question to keywords, searches a Node.js service's Documents entity, and passes what it finds to Claude for a grounded answer. Getting there means learning that HANA's fuzzy .search() matches one word but not a full sentence, fixed by splitting the query into terms and merging the per-term hits, and that provisioning SAP HANA Cloud hits a database-level free-tier quota rather than an HDI-container one, with a stopped instance needing to be resumed first. It also covers @sap/cds-dk needing to sit in dependencies rather than devDependencies, since Cloud Foundry's buildpack skips the latter, before cds deploy --to hana can run as part of the push.neilaspin, published 2026-07-28
CAP Foundry: Engineering SAP CAP Applications from Business Intent with Guardrailed AICAP Foundry: Engineering SAP CAP Applications from Business Intent with Guardrailed AICAP Foundry is a prototype that generates a CAP Node.js project with SAP Fiori elements from a written business requirement, discovering the actual data shape from a chosen source — SQLite, a configured SAP HANA HDI container, offline EDMX, live OData through the SAP Destination service, or approved SAP BTP ABAP objects — instead of inventing one. The generated application can carry a Fiori draft lifecycle with optimistic concurrency via ETags and annotation-driven Fiori elements list and object screens, localized independently of the underlying service contract. Attachments can be added with upload, download and delete, gated on a malware-scan status, and the generated project still has to compile, build and pass its generated tests before the run is accepted.Shahid, published 2026-08-20
Connect SAP CAP (Node.js) to On-Premise/Private PostgreSQL using SAP Cloud ConnectorConnect SAP CAP (Node.js) to On-Premise/Private PostgreSQL using SAP Cloud ConnectorAn end-to-end route from a CAP Node.js application on Cloud Foundry to a PostgreSQL database that is never made publicly reachable, over BTP Connectivity and the Cloud Connector using a TCP destination and SOCKS5. The part worth having is that it covers the deployer as well as the server: the generated PostgreSQL deployer has to reach the same private database to deploy the CDS model, and a guide that only connects the runtime leaves you with a schema you cannot install.Kalaikovan, published 2026-08-07
Connect SAP CAP (Node.js) to On-Premise/Private PostgreSQL using SAP Cloud Connector
Database connectors changed in @sap/cds 10.1.0, 2026-09-07. Affects A recipe.
Flexible analytics at speed: Calculation views in SAP Business Data CloudFlexible analytics at speed: Calculation views in SAP Business Data CloudCalculation views in SAP HANA Cloud, the reusable analytic modelling blocks built in its graphical modelling environment, with three newer parts the abstract names: AI-assisted modelling, refactoring, and advanced materialisation, and the way the views sit inside SAP Business Data Cloud. What a materialisation is chosen on, and what the AI assistance generates, is not stated. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Hansika Colomboge Dona, Jan Zwickel, Niklas Siemer and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
Fullstack CAP Application with HANA Cloud (Decoupled Architecture) [Part-1]Fullstack CAP Application with HANA Cloud (Decoupled Architecture) [Part-1]The first of six, and it does the thing the later parts depend on: build the Incident Management application against SQLite on a laptop, with no cloud database in sight. The series is called decoupled because the front end and the back end are deployed separately, and this part is entirely the back end.sanjucs, published 2026-05-06
Fullstack CAP Application with HANA Cloud (Decoupled Architecture) [Part-1]
Database connectors changed in @sap/cds 10.1.0, 2026-09-07. Affects A recipe, Runnable code.
Fullstack CAP Application with HANA Cloud (Decoupled Architecture) [Part-3]Fullstack CAP Application with HANA Cloud (Decoupled Architecture) [Part-3]The cloud database appears: a HANA Cloud instance created on BTP and mapped to a Cloud Foundry space. No application code — this is the part where the platform has to be right before the next part can connect to it.sanjucs, published 2026-05-08
Fullstack CAP Application with HANA Cloud (Decoupled Architecture) [Part-4]Fullstack CAP Application with HANA Cloud (Decoupled Architecture) [Part-4]The switch from SQLite to HANA and the first deploy of the back end to Cloud Foundry — the point in the series where the persistence stops being a file and the build starts producing HDI artifacts.sanjucs, published 2026-05-12
Fullstack CAP Application with HANA Cloud (Decoupled Architecture) [Part-4]
Database connectors changed in @sap/cds 10.1.0, 2026-09-07. Affects A recipe.
Get hands on with tabular AI and forecasting models in SAP HANA CloudGet hands on with tabular AI and forecasting models in SAP HANA CloudPrediction and forecasting as predictive models inside SAP HANA Cloud, worked through hands-on: tabular AI models such as SAP-RPT-1 for on-the-fly predictions, time series foundation models for ad hoc forecasts, and the AutoML in the predictive analysis library. The abstract names the model kinds and the library and does not say how a model is called from SQL or from an application. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Christoph Morgen, Markus Fath, Ritty Joseph and Tanuja Jadhav, written here from SAP's abstract; the recording is not yet published.
Knowledge graph and agent memory: Build an agent that remembersKnowledge graph and agent memory: Build an agent that remembersThe knowledge graph engine in SAP HANA Cloud as an agent's memory: what the engine, the graph side of graph, spatial and document data, does in an agentic workflow, how an agent keeps what it learns there, the state agent tooling holds between turns, and the SAP AI Core integration through which the database calls LLMs and tabular foundation models such as SAP-RPT-1. The abstract names the engine, the memory role and the AI Core link and does not say how the memory is written or read. DA205 on Tuesday 27 October is the 45-minute talk on the same engine, with a near-identical abstract and a different cast. A two-hour hands-on TechEd 2026 session (Wednesday 28 October, Berlin), presented by Christoph Morgen, Jan Zwickel, Markus Fath and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
Modernize your database landscape with SAP HANA CloudModernize your database landscape with SAP HANA CloudWhy to move a database estate to SAP HANA Cloud, and the migration tools and services for doing so, which is the platform migration concern. SAP's abstract is one sentence and names none of the tools. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Niklas Siemer and Roman Belosludtsev, written here from SAP's abstract; the recording is not yet published.
Road map for SAP HANA Cloud: What’s next for the AI databaseRoad map for SAP HANA Cloud: What’s next for the AI databaseSAP's road map for SAP HANA Cloud, which the abstract places as a core component of SAP Business AI Platform within SAP Business Data Cloud. The abstract promises a firsthand look at what is next for the database and names no feature, release or date, so the two edges rest on the products it names and nothing more. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Niklas Siemer and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
SAP HANA Cloud advisors and automationSAP HANA Cloud advisors and automationSAP HANA Cloud's advisors and the tasks they hand off: the elastic compute node, the partition, index and native storage extension advisors that produce recommendations for performance and efficiency, and SAP Automation Pilot as the service that runs the resulting tasks, which is operations automation on the database. The abstract lists the features and stops there, so what each advisor recommends and how a recommendation becomes an Automation Pilot command is not stated. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Hansika Colomboge Dona, Hui Li, Javier Martin and Roman Belosludtsev, written here from SAP's abstract; the recording is not yet published.
SAP HANA Cloud as a self-managed database: Advisors and automationSAP HANA Cloud as a self-managed database: Advisors and automationSAP HANA Cloud advisors generate recommendations for database administration, aimed at system performance and efficiency, and SAP Automation Pilot runs the manual and administrative tasks around the database as automated processes, which is the operations automation concern on the database side. SAP's abstract names the two services and claims reduced operational overhead; which advisors exist and which tasks the automation covers are not said. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Javier Martin and Roman Belosludtsev, written here from SAP's abstract; the recording is not yet published.
SAP HANA Cloud as the AI database for SAP Business Data CloudSAP HANA Cloud as the AI database for SAP Business Data CloudSAP HANA Cloud as the AI database at the centre of SAP Business Data Cloud: the strategy behind its AI-first direction, and a Carl Zeiss speaker on how it runs in production today. The abstract names the two products and the customer and no feature, workload or figure, so the edges rest on the products as its subject. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Kush Kashyap and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
SAP HANA Cloud: The data foundation for contextualizing and reasoningSAP HANA Cloud: The data foundation for contextualizing and reasoningWhere SAP is taking SAP HANA Cloud, described in the abstract as the anchor of SAP's data strategy and a unified layer to store, contextualise and reason across a business, and what that means for a data platform decision. The abstract is a direction statement and names no feature, release or date, so the one edge rests on the product itself. A TechEd 2026 session (Tuesday 27 October, Berlin; also ST106V, virtual), presented by Matthew Zenus and Stefan Baeuerle, written here from SAP's abstract; the recording is not yet published.
Stop guessing, start counting: How generative AI fixed an inventory messStop guessing, start counting: How generative AI fixed an inventory messAn inventory-counting application a business built on SAP Business AI Platform with SAP HANA Cloud and generative AI, to replace recount lists kept by gut feel across SAP ERP Central Component, SAP S/4HANA and Microsoft Excel; the talk promises the app, its architecture and what went wrong. The generative AI part is LLM integration from application code; the abstract names HANA Cloud and generative AI as the two building blocks and says nothing about how either is used. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Ranjeet Kumar, written here from SAP's abstract; the recording is not yet published.
Talking to your database: The new data exploration tools in SAP HANA CloudTalking to your database: The new data exploration tools in SAP HANA CloudSAP HANA Cloud's new data exploration tools take a business question in plain language, find the right database objects and run the query, with no data model and no SQL written beforehand, shown live on a standard business data set. SAP's abstract says the session covers how the tools work, what they need and where they hit their limits, and states none of the three. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Anna Hartmann, written here from SAP's abstract; the recording is not yet published.
Unlock predictive and generative AI with your data in SAP HANA CloudUnlock predictive and generative AI with your data in SAP HANA CloudThe AI features SAP lists for SAP HANA Cloud: the function libraries for tabular prediction and forecasting, where predictive models run inside the database, the vector engine, the knowledge graph engine, which is graph, spatial and document data put to generative use, and SQL to LLM calls. The abstract names the engines and the use cases they are meant for and gives no detail of any one of them. A TechEd 2026 session (Tuesday 27 October, Berlin; also DA204V, virtual), presented by Christoph Morgen and Javier Martin, written here from SAP's abstract; the recording is not yet published.
Use SAP HANA as the Database for a CAP Java ApplicationUse SAP HANA as the Database for a CAP Java ApplicationMoving a CAP Java application off the development database onto HANA, which is the step where the persistence choice stops being invisible.SAP
Native SAP HANA artifactsUnmapped
Connecting Two SAP CAP Projects Without Duplicating Your DataConnecting Two SAP CAP Projects Without Duplicating Your DataCross-container HDI synonyms, argued from the alternatives rather than presented as a recipe: copying the table, standing up an API, or hard-coding the values are the three things the author reports seeing teams do, and each is named as working but unclean. With synonyms in place the consuming project queries the owner's HANA tables through ordinary SQL and ordinary CAP service code, with no replication and nothing to drift between environments. Covers the same ground as Mio Yasutake's 2021 post from a different angle — that one enumerates four topologies, this one argues for one of them.Inderpreet, published 2026-07-08
Schema evolutionCommunity only
SAP Developer New, July 3rd 2026SAP Developer New, July 3rd 2026A "Did You Know" segment in this SAP Developer News video walks through schema evolution: CAP's ability to add a new field to an entity, or make a compatible change to an existing one, then redeploy the model with no data loss or manual migration. The rest of the July 2026 episode covers that month's Developer Challenge, a SAP HANA Cloud Q2 release announcement and a UI5 survey call, none explained in substance here.published 2026-07-02
SearchSAP only
Building an SAP BTP Agent Architecture from Scratch: Python + CAP + HANABuilding an SAP BTP Agent Architecture from Scratch: Python + CAP + HANAA first-person build log of a Flask orchestrator on Cloud Foundry that reduces a question to keywords, searches a Node.js service's Documents entity, and passes what it finds to Claude for a grounded answer. Getting there means learning that HANA's fuzzy .search() matches one word but not a full sentence, fixed by splitting the query into terms and merging the per-term hits, and that provisioning SAP HANA Cloud hits a database-level free-tier quota rather than an HDI-container one, with a stopped instance needing to be resumed first. It also covers @sap/cds-dk needing to sit in dependencies rather than devDependencies, since Cloud Foundry's buildpack skips the latter, before cds deploy --to hana can run as part of the push.neilaspin, published 2026-07-28
Understanding Fuzzy Search in SAP Fiori ApplicationsUnderstanding Fuzzy Search in SAP Fiori ApplicationsExplains SAP HANA Enterprise Search's fuzzy, relevance-ranked matching behind Fiori's global search bar, its exact-match Search Query Syntax operators, and how a CAP CDS project on @sap/cds tunes the gap between them with @cds.search and @Search.fuzzinessThreshold, shown on a Contracts entity's contractNumber field. Raising the threshold to 0.95 narrows that field to near-exact matches for structured identifiers such as contract numbers, while an unset field keeps HANA's default (~80%) fuzziness for broader free-text discovery.Ruchi5, published 2026-07-27
DestinationsSAP only
CAP Foundry: Engineering SAP CAP Applications from Business Intent with Guardrailed AICAP Foundry: Engineering SAP CAP Applications from Business Intent with Guardrailed AICAP Foundry is a prototype that generates a CAP Node.js project with SAP Fiori elements from a written business requirement, discovering the actual data shape from a chosen source — SQLite, a configured SAP HANA HDI container, offline EDMX, live OData through the SAP Destination service, or approved SAP BTP ABAP objects — instead of inventing one. The generated application can carry a Fiori draft lifecycle with optimistic concurrency via ETags and annotation-driven Fiori elements list and object screens, localized independently of the underlying service contract. Attachments can be added with upload, download and delete, gated on a malware-scan status, and the generated project still has to compile, build and pass its generated tests before the run is accepted.Shahid, published 2026-08-20
Connect SAP CAP (Node.js) to On-Premise/Private PostgreSQL using SAP Cloud ConnectorConnect SAP CAP (Node.js) to On-Premise/Private PostgreSQL using SAP Cloud ConnectorAn end-to-end route from a CAP Node.js application on Cloud Foundry to a PostgreSQL database that is never made publicly reachable, over BTP Connectivity and the Cloud Connector using a TCP destination and SOCKS5. The part worth having is that it covers the deployer as well as the server: the generated PostgreSQL deployer has to reach the same private database to deploy the CDS model, and a guide that only connects the runtime leaves you with a schema you cannot install.Kalaikovan, published 2026-08-07
Connect SAP CAP (Node.js) to On-Premise/Private PostgreSQL using SAP Cloud Connector
Database connectors changed in @sap/cds 10.1.0, 2026-09-07. Affects A recipe.
Consume Remote Services in a Full-Stack CAP ApplicationConsume Remote Services in a Full-Stack CAP ApplicationExtending the Developer's Guide application with a remote S/4HANA service — connectivity, importing the Business Partner API, and running against it. SAP publishes this as four separate paths: mock server or real S/4HANA Cloud, times Cloud Foundry or Kyma. One entry covers all four, because the difference between them is which backend and which runtime, not what you learn.SAP
Consume SOAP Web Services in SAP Cloud Application Programming ModelConsume SOAP Web Services in SAP Cloud Application Programming ModelCalling a SOAP service from CAP — the case the remote-service story does not cover, since CAP's own import path speaks OData and OpenAPI.SAP
Expose S/4HANA Cloud OData API as an MCP Server via CAP Node.jsExpose S/4HANA Cloud OData API as an MCP Server via CAP Node.jsA step-by-step walkthrough that wraps SAP S/4HANA Cloud's Outbound Delivery OData v2 API in a CAP Node.js service and exposes it through @cap-js/mcp, so an MCP client can list the generated tools, query the delivery entities and call a custom createDelivery action over JSON-RPC. The remote S/4HANA connection is configured two ways in package.json: direct Basic Authentication credentials for local hybrid testing, and a named BTP destination for the app once deployed to Cloud Foundry.Jacky_Liu1, published 2026-07-29
Extend SAP SuccessFactors on SAP BTP with the SAP Cloud Application Programming ModelExtend SAP SuccessFactors on SAP BTP with the SAP Cloud Application Programming ModelTwelve tutorials, about two hours, building a side-by-side extension of SuccessFactors on BTP. The spine is remote services: importing the SuccessFactors OData service definitions into a CAP model, then treating them as entities the extension reads and writes through, rather than as an API called from a handler. Indexed as one entry because the parts only make sense in order.SAP
Fullstack CAP Application with HANA Cloud (Decoupled Architecture) [Part-5]Fullstack CAP Application with HANA Cloud (Decoupled Architecture) [Part-5]The consequence of decoupling: with the back end live on its own Cloud Foundry route, the front end needs a BTP destination to reach it rather than a relative path. Short, and it is the join the architecture creates.sanjucs, published 2026-05-18
Use the SAP Cloud SDK in the SAP Cloud Application Programming ModelUse the SAP Cloud SDK in the SAP Cloud Application Programming ModelReaching for the Cloud SDK from inside a CAP service, for the calls CAP's own remote services do not make.SAP
Event MeshSAP only
Build real-time event-driven integrations for your enterpriseBuild real-time event-driven integrations for your enterpriseEvent-driven integration with SAP Integration Suite, advanced event mesh inside SAP Integration Suite: where events beat request-response, how publish and subscribe decouple systems, and what a phased move to event-driven integration looks like. Event Mesh as architecture; the abstract names no broker protocol and no CDS mapping. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Daniel Dorst and Karsten Strothmann, written here from SAP's abstract; the recording is not yet published.
Build your own event-driven scenario with advanced event meshBuild your own event-driven scenario with advanced event meshAn event-driven scenario built on SAP Integration Suite, advanced event mesh: queues, topics and subscriptions first, then filtering and event replay, in two parallel tracks, a guided one for newcomers and a second for experienced practitioners. It covers the brokered side of Event Mesh; which systems publish and consume, and which protocol the clients speak, is not stated. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Claudia Carabineiro, Emily Mui, Karsten Strothmann and Tobias Griebe, written here from SAP's abstract; the recording is not yet published.
Unlock composable business using SAP Integration Suite, advanced event meshUnlock composable business using SAP Integration Suite, advanced event meshSAP Integration Suite, advanced event mesh as SAP's product for event-driven, real-time and loosely coupled integration between SAP and third-party systems, which the abstract ties to composable business architecture. The session is about that product and the Event Mesh concern it answers; the abstract states the positioning and no feature, topic or protocol, and a speaker from CCB Management Services is listed without a stated case. A TechEd 2026 session (Tuesday 27 October, Berlin; also IN111V, virtual), presented by Goran D. Stevanovic and Karsten Strothmann, written here from SAP's abstract; the recording is not yet published.
Agent access to your codeSAP and community
AI-assisted full stack development using model context protocol serversAI-assisted full stack development using model context protocol serversMCP servers in Visual Studio Code used to configure, query and change a full-stack application built with CAP, CDS and OData: the agent access to your code concern, a coding assistant reading and changing the project it works in. The abstract names no server, so neither @cap-js/mcp-server nor any other is attached, and it does not say which changes are made. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Sergio Guerrero, written here from SAP's abstract; the recording is not yet published.
OData to outcomes—Build AI-enabled SAP Fiori apps using SAP Fiori elementsOData to outcomes—Build AI-enabled SAP Fiori apps using SAP Fiori elementsA Fiori elements app built through SAP's MCP servers: the OData V4 service comes from the MCP server for RAP, which the atlas holds as the ADT MCP Server, or from @cap-js/mcp-server for CAP, and the UI from @sap-ux/fiori-mcp-server, with annotations and actions added before the app is tied to SAP's AI features. Agent access to your code on both the service and the UI side; SAP's abstract names the servers and the steps and says nothing about which AI features or which agent host. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Benedikt Schoelch, Sebastian Steinhauer, Sebastian Werner and Stefan Engelhardt, written here from SAP's abstract; the recording is not yet published.
Agent guidanceSAP and community
Teaching AI Agents Best Practices: A Skills Workspace for CAP DevelopmentTeaching AI Agents Best Practices: A Skills Workspace for CAP DevelopmentStates the gap this capability exists for more precisely than most: an agent already knows CAP well enough to generate models, handlers and deployments, but knowing a framework and following its current practice reliably are different things, because a model defaults to whatever it saw most of during training — which may be outdated, subtly wrong, or simply not how a given team works. Skills are offered as the closing mechanism, and the post describes a workspace pattern rather than a single file, with the architecture claimed to be framework-agnostic.daniel_schlachter, published 2026-06-09
Agent toolingSAP only
Adapting SAP Joule for Purchase Order Creation from an Existing Purchase RequisitionAdapting SAP Joule for Purchase Order Creation from an Existing Purchase RequisitionA custom Joule Agent and Joule Skill, built in Joule Studio, classic edition to extend SAP Joule past its built-in Purchase Order display and change features: a buyer's single sentence naming a Purchase Requisition number becomes a created Purchase Order, with the skill wrapping the Purchase Requisition and Purchase Order OData V4 APIs as Action Packages reached through two destinations. The author anchors the agent's success condition to a PurchaseOrderNumber in the skill's output rather than an HTTP status code, and reports that the Purchase Requisition item structure does not map one-to-one onto the Purchase Order creation payload.jonathanvi59, published 2026-08-19
Agent-led test management: Hands-on lab with Joule in SAP Cloud ALMAgent-led test management: Hands-on lab with Joule in SAP Cloud ALMThe Test Management Assistant, a Joule capability in SAP Cloud ALM, worked through on project scenarios: scoping requirements, detecting coverage gaps and generating test cases with AI. The edge is to SAP Joule, which the assistant runs on; SAP Cloud ALM has no entry here, and the atlas's testing concern, proving a service's model and handlers, is not this session's test management. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Christina Pickhardt, Daniel Lorenz, Niclas Weidner and Tobias Keller, written here from SAP's abstract; the recording is not yet published.
Agentic AI on BTP: a Multi‑Agent App with Pydantic AIAgentic AI on BTP: a Multi‑Agent App with Pydantic AISplits a single CAP/TypeScript agent that had grown to juggle five BTP MCP servers behind one bloated tool list into btp-multiagent-app, a Python and Pydantic AI rewrite where the Cloud Foundry and BTP Core MCP servers each get a dedicated specialist agent, with an audit log specialist scaffolded but left disabled, behind an orchestrator whose only tools are delegation calls to those specialists, which is the agent-tooling pattern the piece works through. Each specialist authenticates to its MCP server over Streamable HTTP with OAuth 2.1, and a shared module centralises the SAP AI Core GenAI Hub model setup behind two credential layouts, one for local runs and one for the Cloud Foundry service binding, the LLM integration side of the rewrite. Tool lists per agent drop from well over a hundred to a dozen or two, and routing failures become separable from tool-misuse failures by reading the trace.published 2026-05-03
Agentic AI on BTP: a Single Agent with LangGraphAgentic AI on BTP: a Single Agent with LangGraphA CAP TypeScript agent puts a LangGraph StateGraph in front of AzureOpenAiChatClient from @sap-ai-sdk/langchain, reaching SAP AI Core's Generative AI Hub, and lets its tool-calling loop draw on five deployed MCP servers — OData MCP Proxy, CI MCP Server, AI Core MCP Server, BTP MCP Server and BTP CF MCP Server — through @langchain/mcp-adapters' MultiServerMCPClient. Because agent, servers and APIs share one XSUAA tenant, the chat service forwards the signed-in user's own JWT instead of a service account, so each downstream server enforces that user's own authorizations. Past roughly a hundred combined tools the single prompt slows down and stops separating concerns, which is why the author's next post splits it into one specialist agent per MCP server behind an orchestrator.published 2026-05-03
Agentic memory: Knowledge graph engine and recall in SAP HANA CloudAgentic memory: Knowledge graph engine and recall in SAP HANA CloudThe knowledge graph engine in SAP HANA Cloud as an agent's memory: what the engine, the graph side of graph, spatial and document data, does in an agentic workflow, how an agent keeps what it learns there, the state agent tooling holds between turns, and the SAP AI Core integration through which the database calls LLMs and tabular foundation models such as SAP-RPT-1. The abstract names the engine, the memory role and the AI Core link and does not say how the memory is written or read. DA263 on Wednesday 28 October is a two-hour hands-on on the same engine with a different cast. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Markus Fath and Shraddha Shetty, written here from SAP's abstract; the recording is not yet published.
AI-accelerated RISE with SAP migration with the system transition workbenchAI-accelerated RISE with SAP migration with the system transition workbenchSAP Joule for Consultants and the RISE with SAP system transition workbench in a move to SAP S/4HANA Cloud Private Edition: readiness assessments, migration workflows and the SAP tools involved. The edge is to SAP Joule, of which Joule for Consultants is a part; the system transition workbench has no entry here, and Platform migration covers applications leaving older BTP platforms, not an ERP system's move. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Daniel Funkert, Kristin Aleksandrova, Mirja Kempin and Moritz Gysler, written here from SAP's abstract; the recording is not yet published.
AI-enhanced analytics with SAP Business AI PlatformAI-enhanced analytics with SAP Business AI PlatformSAP Business Data Cloud data products joined to an ontology, a semantic layer the abstract says is supported by the Model Context Protocol, and read from Joule Work (SAP Joule) and SAP Analytics Cloud: that is the architecture SAP's abstract states for its AI-enabled analytics. The abstract names the parts and not how the semantic layer is modelled or what an analytics developer builds against. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Hacen Benkhedah, Joaquin Recio Huertas, Matilda Hyka and Oliver Huth, written here from SAP's abstract; the recording is not yet published.
Banking Sentinel: A Multi-Agent Credit-Risk Copilot on SAP BTP, Built on a Mixed AI StackBanking Sentinel: A Multi-Agent Credit-Risk Copilot on SAP BTP, Built on a Mixed AI StackThe risk it is chasing is a graph problem stated in banking terms: a borrower who looks safe alone and is the linchpin of a group ten times the size. Multi-agent, mixed AI stack, on BTP and CAP.Shahid, published 2026-06-24
Banking Sentinel: A Multi-Agent Credit-Risk Copilot on SAP BTP, Built on a Mixed AI Stack
Agent tooling changed in @cap-js/agents 0.9.1, 2026-08-14. Affects A recipe, Runnable code.
Build your first agent with Joule Studio in a pro-code wayBuild your first agent with Joule Studio in a pro-code wayThe command line interface of Joule Studio, which the atlas holds as @sap/joule-work-dev-cli-early-adopters, carries an agent from a structured intent through generated product requirements documentation and wired APIs to a deployment on Joule Studio's SAP-managed runtime, in one guided flow. SAP's abstract names the stages of that pipeline and promises working code at the end; what the generated requirements and APIs look like is not described. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Charan Ravikumar, Evgenii Skrebtcov, Maria Kondratyeva and Simon Endres, written here from SAP's abstract; the recording is not yet published.
Building agentic applications with SAP HANA CloudBuilding agentic applications with SAP HANA CloudA CAP application extended with semantic search and agent features on top of SAP HANA Cloud's vector engine and SAP AI Core, built in a hands-on workshop. The abstract names the parts, CAP, the vector engine and AI Core, and the two additions: semantic search, the retrieval half of retrieval-augmented generation, and LLM-supported agent capabilities inside the application, which is agent tooling. Which embedding model, which CAP runtime and how the agent calls its tools are not stated. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Hui Li, Ritty Joseph, Shraddha Shetty and Tanuja Jadhav, written here from SAP's abstract; the recording is not yet published.
Building an LLM Agent in CAP Java with Spring AIBuilding an LLM Agent in CAP Java with Spring AIThe Java counterpart to the author's own Node.js post, and written as one: connecting to AI Core with the SAP AI SDK, then calling an agent and a tool through Spring AI. Opens with a section on libraries and workflows — which framework does what, and what is left to you — before any code.published 2026-06-08
Building an LLM Agent in CAP Java with Spring AI
Agent tooling changed in @cap-js/agents 0.9.1, 2026-08-14. Affects Runnable code.
Building an LLM Agent using CAPBuilding an LLM Agent using CAPThe argument is that CAP is already most of what an agent framework wants — services, handlers, a typed model — so the agent is built inside it rather than beside it. AI Core through sap-ai-sdk, then Langchain for the agent and its tools. Long, with a TLDR at the top for people who want the shape without the walk.published 2026-05-27
Building an LLM Agent using CAP
Agent tooling changed in @cap-js/agents 0.9.1, 2026-08-14. Affects Runnable code.
Building custom Joule Agents with SAP Knowledge GraphBuilding custom Joule Agents with SAP Knowledge GraphCustom Joule Agents built in a hands-on with SAP Knowledge Graph and Joule Studio: discovering APIs from a user's intent, grounding an agent's answers in business context, and integrating data products for SAP Business Data Cloud. The agents are SAP Joule's; the Knowledge Graph is not an atlas entry, and the abstract does not say which Joule Studio edition the exercises use. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Jan Portisch, Lucas Kiesow, Pavithra G K and Rafael Martin, written here from SAP's abstract; no recording is announced.
Building Durable AI Agents - Announcing the cds-langgraph-persistence PluginBuilding Durable AI Agents - Announcing the cds-langgraph-persistence PluginThe announcement, and the argument behind it. Treating an agent as a software architecture rather than a model with tools makes a list of production requirements — identity, authn and authz, multitenancy, persistence, event-driven flows, scalability, observability, CI/CD — and the author's point is that CAP already answers most of them for BTP, which is what makes LangGraph inside CAP Node.js worth doing. The post then narrows to one of those requirements, durability, and the checkpointer that supplies it. Written from a year of building agents next to real business systems rather than as a framework tour.merbinjanselm, published 2026-07-15
Building Durable AI Agents - Announcing the cds-langgraph-persistence Plugin
@mi8y/cds-langgraph-persistence has been through 3 major lines since this was published: 0.5 (2026-07), 0.6 (2026-07), 0.7 (2026-09). Affects Runnable code.
Building enterprise agent extensions with the Joule Studio solutionBuilding enterprise agent extensions with the Joule Studio solutionExtending SAP's standard agents with third-party integrations and business actions in Joule Studio: agents that run a process across systems, call an external service, put an approval step in the middle and bring the result back into the business context, which is what SAP Joule's agents do and what Joule Studio, classic edition is in the atlas. The abstract names Joule Studio without saying which edition the exercise uses, and lists outcomes rather than the steps built. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Charan Ravikumar, Jacob Hornberger, Maria Kondratyeva and Michael Zadikowitsch, written here from SAP's abstract; the recording is not yet published.
Connecting AI agents to the ABAP RESTful application programming modelConnecting AI agents to the ABAP RESTful application programming modelJoule Studio, classic edition connects Joule Agents to applications built with the ABAP RESTful application programming model through actions and skills, calling the OData services those applications expose their business objects through: the tools an agent may call, which is the agent tooling concern seen from the ABAP side. The abstract promises alternative integration patterns and does not name them. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Leon Karlau, written here from SAP's abstract; the recording is not yet published.
Deploy, review, break, fix: Govern cloud transports with agility and AIDeploy, review, break, fix: Govern cloud transports with agility and AIFive BTP services in one delivery chain, as the abstract lays it out: a transport is triggered in SAP Content Agent Service, tested in SAP Cloud Transport Management, its failure is raised by SAP Alert Notification service for SAP BTP and remediated by a SAP Joule agent with SAP Automation Pilot, and SAP Cloud Logging keeps the history for root-cause analysis. The chain from alert to remediation is the operations automation concern; what the Joule agent decides on its own is not in the abstract. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Biser Simeonov, Daniel Funkert, Sven Rullmann and Thorsten Sandfuchs, written here from SAP's abstract; the recording is not yet published.
Discover fast-track implementation of SAP Cloud ERP with AIDiscover fast-track implementation of SAP Cloud ERP with AISAP's implementation practice for SAP S/4HANA Cloud Public Edition and the AI-driven tooling SAP says is changing stages of a project, with faster and more predictable deployments, less manual effort and lower risk as the stated outcomes. The abstract names the product, an external here, and no tool; the edge is to SAP Joule because SAP's AI tooling for implementation in the sibling sessions TM109, TM263 and TM265 is Joule for Consultants, and whether this session shows it is not stated. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Anurag Barua and Khaled MUSILHY, written here from SAP's abstract; the recording is not yet published.
Discover how SAP Joule for Consultants transforms cloud implementationsDiscover how SAP Joule for Consultants transforms cloud implementationsA customer's use of SAP Joule for Consultants in a cloud transformation: grounding project data, running fit-to-standard workshops faster and keeping teams aligned, followed by the technical architecture behind those capabilities and an early road map preview on feasibility for developers and enterprise architects. The edge is to SAP Joule, of which Joule for Consultants is the offering for consultants and has no entry of its own here; the abstract leaves the customer as a placeholder and the architecture to the session. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Philipp Kandziora and Yi Hsuan Lin, written here from SAP's abstract; the recording is not yet published.
Experience core foundational capabilities of SAP Cloud ERPExperience core foundational capabilities of SAP Cloud ERPGuided exercises in SAP S/4HANA Cloud Public Edition, which SAP calls the execution backbone of the Autonomous Enterprise: validating AI capabilities against master data for industry and domain needs, generating AI-driven KPIs and reporting summaries. The product is an external here and the abstract names no AI feature by name; the edge is to SAP Joule, SAP's AI layer across its applications and the one entry the AI capabilities of SAP Cloud ERP attach to, which the abstract itself does not name. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Akshat Kharial, Ankush Thareja and Nises Soni, written here from SAP's abstract; the recording is not yet published.
From intent to extension: Joule and the future of solution extensibilityFrom intent to extension: Joule and the future of solution extensibilityHow Joule turns natural-language intent into extensions across SAP Autonomous Suite: intent-based agent extensions, enriching the agents SAP delivers, packaging options for partners and what SAP calls a harmonised extensibility experience. The edges are to SAP Joule, which does the translating, and to Extensibility, the concern; the abstract names the directions and no feature that ships today. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Amitha Kamath, Oren Shatil and Richard Kuba, written here from SAP's abstract; the recording is not yet published.
Generate agentic workflows using SAP-managed n8n in Joule StudioGenerate agentic workflows using SAP-managed n8n in Joule StudioSAP-managed n8n inside Joule Studio generates a workflow from a business intent a developer states, and the workflow is then tested and deployed, consuming line-of-business application APIs, events and agents in SAP Business AI Platform: process automation with the workflow generated from intent, and agent tooling where the workflow calls agents. The generated workflow sends notifications to the Joule Work mobile app of SAP Joule, to Microsoft Teams or to Slack. SAP's abstract names the pieces and not how the generation or the n8n hosting works. A two-hour hands-on TechEd 2026 session (Tuesday 27 October, Berlin), presented by Rama Sulakshani Murari, Rumen Dimitrov, Seshadri Sreenivas Ramanarayanan and Venugopal Chembrakalathil, written here from SAP's abstract; the recording is not yet published.
Get to know our AI-enhanced mobile apps across the Autonomous EnterpriseGet to know our AI-enhanced mobile apps across the Autonomous EnterpriseA demo of the Joule Work mobile app, part of SAP Joule, and selected SAP mobile apps, showing the mobile AI features meant for using SAP Autonomous Suite on the go, followed by the mobile AI patterns and how to build your own Mobile apps with SAP Business AI Platform. The abstract names the apps and the patterns and states no feature or tool, so what building your own involves is not said. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Sandeep Tetali and Thilo Berndt, written here from SAP's abstract; the recording is not yet published.
Inside Joule Studio runtime: Agent deployment and integrationsInside Joule Studio runtime: Agent deployment and integrationsJoule Studio runtime from the inside: the tools and services SAP manages to deploy, integrate, run, extend and operate agents at scale, and the integrations through the agent gateway and SAP S/4HANA Cloud Private Edition. The edge is to SAP Joule, whose agents the runtime runs; the atlas reaches that runtime through @sap/joule-work-dev-cli-early-adopters, which deploys a solution to it, and the abstract names neither the CLI nor a service by name. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Andre Lamego and Jens Huesken, written here from SAP's abstract; the recording is not yet published.
Joule and related AI offerings from SAP: One platform, many systemsJoule and related AI offerings from SAP: One platform, many systemsSAP Joule run across dozens of SAP systems: the SAP for Me portal, orchestration across systems, configuration and credential management, monitoring and tenant isolation are the topics SAP's abstract lists. It stays on the operating side and says nothing about building on Joule. A TechEd 2026 session (Wednesday 28 October, Berlin; also JW301V, virtual), presented by Lukas Lochner, Marvin Klaus and Mathias Rup, written here from SAP's abstract; the recording is not yet published.
Joule and SAP Knowledge Graph: Context-aware AI across SAP solutionsJoule and SAP Knowledge Graph: Context-aware AI across SAP solutionsThe catalogue carries RA107's abstract under this title, and what it describes is SAP AI Core as the management and orchestration layer of an AI architecture: extending Joule Agents in SAP Joule, the model library in Joule Studio for contextual reasoning, connecting data products from SAP Business Data Cloud, and embedding AI in SAP S/4HANA. The SAP Knowledge Graph the title names does not appear in that text, so the edges rest on the abstract as published, and whether the session follows the title or the abstract is not known until it is recorded. A TechEd 2026 session (Wednesday 28 October, Berlin; also RA110V, virtual), presented by Jan Portisch and Pavithra G K, written here from SAP's abstract; the recording is not yet published.
Joule without walls: From personal skills to enterprise interoperabilityJoule without walls: From personal skills to enterprise interoperabilitySAP Joule connects outward over two protocols, A2A and MCP, which SAP's abstract names as the foundation of its open ecosystem, with Joule Assistants as composable agents and extensibility built in. The session draws the line between a personal extension of Joule and one that needs enterprise governance; the abstract does not say where that line falls. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Mathis Boerner and Thomas Mueller, written here from SAP's abstract; the recording is not yet published.
Knowledge graph and agent memory: Build an agent that remembersKnowledge graph and agent memory: Build an agent that remembersThe knowledge graph engine in SAP HANA Cloud as an agent's memory: what the engine, the graph side of graph, spatial and document data, does in an agentic workflow, how an agent keeps what it learns there, the state agent tooling holds between turns, and the SAP AI Core integration through which the database calls LLMs and tabular foundation models such as SAP-RPT-1. The abstract names the engine, the memory role and the AI Core link and does not say how the memory is written or read. DA205 on Tuesday 27 October is the 45-minute talk on the same engine, with a near-identical abstract and a different cast. A two-hour hands-on TechEd 2026 session (Wednesday 28 October, Berlin), presented by Christoph Morgen, Jan Zwickel, Markus Fath and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
SAP Joule for Consultants: Unified knowledge for requirements and designsSAP Joule for Consultants: Unified knowledge for requirements and designsFit-to-standard analysis as a consultant on a cloud transformation project: connecting an organisation's data to SAP Joule for Consultants through SAP AI Core, getting answers from SAP knowledge and that content, then building an expert, loading project files and running guided prompts. The edges are to SAP Joule, of which Joule for Consultants is a part, and to SAP AI Core, named as the connection path; how the data is grounded is left to the session. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Anantharaman Ravi, Natalie Han, Sachin Kaura and Yi Hsuan Lin, written here from SAP's abstract; the recording is not yet published.
SAP’s compositional design system: Craft enterprise UIs with AI on the flySAP’s compositional design system: Craft enterprise UIs with AI on the flySAP's compositional design system is the engine behind the generated interface in Joule Work, the front of SAP Joule: SAP's abstract says AI assembles the UI at runtime from primitives and composites under a body of design knowledge, inside a brand-safe design system, and that the session covers the architecture that keeps the result consistent. A third shape of Generative UI beside the two the capability describes, since here the model composes the interface at runtime. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Philip Miseldine and Sophia Levens, written here from SAP's abstract; the recording is not yet published.
The road map for SAP Joule for Consultants—your go-to SAP consulting toolThe road map for SAP Joule for Consultants—your go-to SAP consulting toolSAP's road map for SAP Joule for Consultants, which the abstract describes as becoming the tool for SAP software projects: landscape awareness and secure system connectivity, so that Joule understands an organisation's SAP environments and gives project teams more contextual guidance. The atlas holds no entry for Joule for Consultants, so the piece enters on SAP Joule, the product it is an edition of; the abstract states outcomes and no feature or date. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Natalie Han and Sachin Kaura, written here from SAP's abstract; the recording is not yet published.
Transform business data into AI-supported insightsTransform business data into AI-supported insightsBusiness metrics turned into insights, narratives and recommendations by SAP Joule's agents, with People Intelligence, the SAP Snowflake solution extension for SAP Business Data Cloud and SAP Analytics Cloud connected in SAP Business Data Cloud. The abstract names what is connected and what comes out, and does not say what the exercise builds or where the Snowflake extension sits in it; People Intelligence and the extension are not atlas entries. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Babacar Toure, Maximilian Paul Gander, Neetha Pucknat and San Tran, written here from SAP's abstract; the recording is not yet published.
What’s next for agentic analytics and planning in SAP Business Data CloudWhat’s next for agentic analytics and planning in SAP Business Data CloudWhat is next for agentic analytics and planning in SAP Business Data Cloud: SAP Joule's agents automating insight delivery, analysis, narrative generation and modelling tasks. A road map session; the abstract names the four kinds of task and no agent or date. A TechEd 2026 session (Tuesday 27 October, Berlin; also DA806V, virtual), presented by Kristian Ruemmelin, written here from SAP's abstract; the recording is not yet published.
What’s next for the core platform capabilities of SAP Business AI PlatformWhat’s next for the core platform capabilities of SAP Business AI PlatformA preview of the operations layer beneath SAP Business AI Platform: selected road map highlights across Joule Studio runtime, Cloud Identity Services and SAP Cloud Logging, on how enterprise AI is governed and run. The edges are to the two named services and to SAP Joule, whose agents the Joule Studio runtime runs; the abstract names the three areas and no highlight. A TechEd 2026 session (Tuesday 27 October, Berlin; also XP825V, virtual), presented by Andre Lamego and Jens Huesken, written here from SAP's abstract; the recording is not yet published.
Zero token architecture for Joule AgentsZero token architecture for Joule AgentsA pattern for SAP Joule's agents in which an agent maps the solution path once, solves the problem, generates reusable code or configuration and validates it, and later requests reuse that output, so discovery is done by the model and execution is repeatable. The abstract states the pattern as an idea and names no Joule component and no case it was tried on. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by EDGAR ADRIAN MARTINEZ ARCE, written here from SAP's abstract; the recording is not yet published.
Document extractionSAP only
Behind the Autonomous Enterprise: SAP Knowledge Graph and SAP Domain ModelsBehind the Autonomous Enterprise: SAP Knowledge Graph and SAP Domain ModelsThe strategy behind SAP Business AI's intelligence layer: SAP Knowledge Graph for enterprise context, SAP Domain Models for SAP-specific expertise and tabular AI for predictions, unified on SAP AI Core with SAP Document AI. Knowledge Graph and Domain Models are not atlas entries, so the edges rest on the two products the abstract names as the infrastructure and on Predictive models for the tabular AI; nothing is stated about what any of them does in the layer. A TechEd 2026 session (Tuesday 27 October, Berlin; also ST103V, virtual), presented by Jan Portisch and Richard Grandpierre, written here from SAP's abstract; the recording is not yet published.
Hands on SAP Document AI: Next-generation intelligent document processingHands on SAP Document AI: Next-generation intelligent document processingSAP Document AI configured and run by hand: schema design, splitting and classifying documents, enriching the extracted data and custom prompting are the exercises SAP's abstract names. Document extraction from the configuring side, with the schema the participant's own; which document types or models the exercises use is not stated. A TechEd 2026 hands-on session (Thursday 29 October, Berlin), presented by Christoph Lenschow, Tobias Weller and Tomasz Janasz, written here from SAP's abstract; no recording is announced.
How SAP Document AI brings agentic intelligence to business documentsHow SAP Document AI brings agentic intelligence to business documentsSAP Document AI as SAP's abstract now describes it: composable, agent-ready skills for schemaless extraction, classification and summarisation of business documents, so Joule Agents can read and act on unstructured content, plus new document foundation models and agentic validation in its workflow engine. That widens document extraction past the fixed-schema fields the atlas entry records; the abstract names the features and not their release state. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Dheeraj Diwan, Soeren Leibach and Tomasz Janasz, written here from SAP's abstract; the recording is not yet published.
Use Free Tier to Create a Service Instance for SAP Document AIUse Free Tier to Create a Service Instance for SAP Document AIFour steps in the SAP BTP cockpit that end with a service key for SAP Document AI: open the cockpit, check the subaccount's entitlements and add the service on the free tier plan if it is not listed, create the instance, then create the key. It names the plans to use in production instead, blocks_of_100, embedded_edition and premium_edition, and stops at the credentials, before any document is uploaded.
Use Free Tier to Subscribe to SAP Document AI Basic UIUse Free Tier to Subscribe to SAP Document AI Basic UIEight steps from an entitled subaccount to the SAP Document AI basic UI open in a browser, and most of them are identity work rather than document work: getting a tenant for Cloud Identity Services, which the basic UI requires, activating the account and establishing trust with the subaccount, then subscribing, creating a user and assigning the Document_Information_Extraction_UI_Templates_Admin role collection. Using the UI to read a document is the subject of Use Machine Learning to Extract Information from Documents with the SAP Document AI Basic UI, which this tutorial names as what to read next.
What a Second Document AI Workshop Taught Me About GovernanceWhat a Second Document AI Workshop Taught Me About GovernanceFrom questions raised at a second SAP Document AI workshop: the retention period for extracted data is a setting in the service's administration rather than a fixed property, with the source file deleted after processing and the decommissioning period for the extracted data configured to the customer's own policy. It also draws a boundary readers kept merging: Document AI extracts across languages but does not translate, so turning a document into a reviewer's own language is a separate step, pointing on BTP at SAP Translation Hub.Nicolas_BacaStorni, published 2026-08-25
Generative UIUnmapped
SAP’s compositional design system: Craft enterprise UIs with AI on the flySAP’s compositional design system: Craft enterprise UIs with AI on the flySAP's compositional design system is the engine behind the generated interface in Joule Work, the front of SAP Joule: SAP's abstract says AI assembles the UI at runtime from primitives and composites under a body of design knowledge, inside a brand-safe design system, and that the session covers the architecture that keeps the result consistent. A third shape of Generative UI beside the two the capability describes, since here the model composes the interface at runtime. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Philip Miseldine and Sophia Levens, written here from SAP's abstract; the recording is not yet published.
LLM integrationSAP only
Agentic AI on BTP: a Multi‑Agent App with Pydantic AIAgentic AI on BTP: a Multi‑Agent App with Pydantic AISplits a single CAP/TypeScript agent that had grown to juggle five BTP MCP servers behind one bloated tool list into btp-multiagent-app, a Python and Pydantic AI rewrite where the Cloud Foundry and BTP Core MCP servers each get a dedicated specialist agent, with an audit log specialist scaffolded but left disabled, behind an orchestrator whose only tools are delegation calls to those specialists, which is the agent-tooling pattern the piece works through. Each specialist authenticates to its MCP server over Streamable HTTP with OAuth 2.1, and a shared module centralises the SAP AI Core GenAI Hub model setup behind two credential layouts, one for local runs and one for the Cloud Foundry service binding, the LLM integration side of the rewrite. Tool lists per agent drop from well over a hundred to a dozen or two, and routing failures become separable from tool-misuse failures by reading the trace.published 2026-05-03
Agentic AI on BTP: a Single Agent with LangGraphAgentic AI on BTP: a Single Agent with LangGraphA CAP TypeScript agent puts a LangGraph StateGraph in front of AzureOpenAiChatClient from @sap-ai-sdk/langchain, reaching SAP AI Core's Generative AI Hub, and lets its tool-calling loop draw on five deployed MCP servers — OData MCP Proxy, CI MCP Server, AI Core MCP Server, BTP MCP Server and BTP CF MCP Server — through @langchain/mcp-adapters' MultiServerMCPClient. Because agent, servers and APIs share one XSUAA tenant, the chat service forwards the signed-in user's own JWT instead of a service account, so each downstream server enforces that user's own authorizations. Past roughly a hundred combined tools the single prompt slows down and stops separating concerns, which is why the author's next post splits it into one specialist agent per MCP server behind an orchestrator.published 2026-05-03
Agentic CAP: Build MCP servers and enterprise AI agentsAgentic CAP: Build MCP servers and enterprise AI agentsCAP applications become AI agents over the Model Context Protocol and the Agent2Agent protocol, which is the serve your application over MCP concern, and SAP AI Core is the LLM integration through which AI is embedded in a CAP app, with recommendations from the SAP-RPT-1 model as the abstract's example. The abstract names the two protocols and the one model and does not say which packages carry them. A two-hour TechEd 2026 session in a hands-on room (Tuesday 27 October, Berlin), presented by Daniel Hutzel, Daniel Schlachter, Marc Huber and Sami Lechner, written here from SAP's abstract; the recording is not yet published.
Agentic memory: Knowledge graph engine and recall in SAP HANA CloudAgentic memory: Knowledge graph engine and recall in SAP HANA CloudThe knowledge graph engine in SAP HANA Cloud as an agent's memory: what the engine, the graph side of graph, spatial and document data, does in an agentic workflow, how an agent keeps what it learns there, the state agent tooling holds between turns, and the SAP AI Core integration through which the database calls LLMs and tabular foundation models such as SAP-RPT-1. The abstract names the engine, the memory role and the AI Core link and does not say how the memory is written or read. DA263 on Wednesday 28 October is a two-hour hands-on on the same engine with a different cast. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Markus Fath and Shraddha Shetty, written here from SAP's abstract; the recording is not yet published.
AI-enabled administration: Automating log analysis with generative AI hubAI-enabled administration: Automating log analysis with generative AI hubA log analysis tool for incident work, built in SAP Business Application Studio with the generative AI hub feature, which SAP AI Core ships as its LLM integration by its own documentation: it automates root-cause analysis over system errors and masks sensitive data. SAP's abstract states the tool's jobs and not how the hub is called, what the masking covers or which model answers. A TechEd 2026 session (Wednesday 28 October, Berlin), with no speaker listed in the catalogue at the time of writing, written here from SAP's abstract; the recording is not yet published.
Banking Sentinel: A Multi-Agent Credit-Risk Copilot on SAP BTP, Built on a Mixed AI StackBanking Sentinel: A Multi-Agent Credit-Risk Copilot on SAP BTP, Built on a Mixed AI StackThe risk it is chasing is a graph problem stated in banking terms: a borrower who looks safe alone and is the linchpin of a group ten times the size. Multi-agent, mixed AI stack, on BTP and CAP.Shahid, published 2026-06-24
Banking Sentinel: A Multi-Agent Credit-Risk Copilot on SAP BTP, Built on a Mixed AI Stack
Agent tooling changed in @cap-js/agents 0.9.1, 2026-08-14. Affects A recipe, Runnable code.
Behind the Autonomous Enterprise: SAP Knowledge Graph and SAP Domain ModelsBehind the Autonomous Enterprise: SAP Knowledge Graph and SAP Domain ModelsThe strategy behind SAP Business AI's intelligence layer: SAP Knowledge Graph for enterprise context, SAP Domain Models for SAP-specific expertise and tabular AI for predictions, unified on SAP AI Core with SAP Document AI. Knowledge Graph and Domain Models are not atlas entries, so the edges rest on the two products the abstract names as the infrastructure and on Predictive models for the tabular AI; nothing is stated about what any of them does in the layer. A TechEd 2026 session (Tuesday 27 October, Berlin; also ST103V, virtual), presented by Jan Portisch and Richard Grandpierre, written here from SAP's abstract; the recording is not yet published.
Build AI agents and applications natively on SAP HANA CloudBuild AI agents and applications natively on SAP HANA CloudSAP HANA Cloud as the base for agentic applications on SAP Business AI Platform: the session goes through CAP, the SAP HANA Cloud vector engine and SAP AI Core, with architecture patterns and lessons learned from building AI-supported applications. SAP's abstract names the three parts of that stack and the vector engine as the database's feature in it, and describes none of the patterns. A TechEd 2026 session (Wednesday 28 October, Berlin; also DA113V, virtual), presented by Christoph Morgen and Shraddha Shetty, written here from SAP's abstract; the recording is not yet published.
Build business differentiation with SAP AI CoreBuild business differentiation with SAP AI CoreSAP AI Core as the orchestration layer for enterprise AI, worked through with SAP's engineers: extend Joule Agents with models from its library, ground them in SAP Business Data Cloud products, embed them in SAP S/4HANA flows, then govern, scale and monitor them from prototype to production. The abstract says what the layer does for an agent and not which services carry each step. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by David Knaack, Franziska Dobrigkeit, Hadi Hares and Jonas Israel, written here from SAP's abstract; the recording is not yet published.
Building agentic applications with SAP HANA CloudBuilding agentic applications with SAP HANA CloudA CAP application extended with semantic search and agent features on top of SAP HANA Cloud's vector engine and SAP AI Core, built in a hands-on workshop. The abstract names the parts, CAP, the vector engine and AI Core, and the two additions: semantic search, the retrieval half of retrieval-augmented generation, and LLM-supported agent capabilities inside the application, which is agent tooling. Which embedding model, which CAP runtime and how the agent calls its tools are not stated. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Hui Li, Ritty Joseph, Shraddha Shetty and Tanuja Jadhav, written here from SAP's abstract; the recording is not yet published.
Building an LLM Agent in CAP Java with Spring AIBuilding an LLM Agent in CAP Java with Spring AIThe Java counterpart to the author's own Node.js post, and written as one: connecting to AI Core with the SAP AI SDK, then calling an agent and a tool through Spring AI. Opens with a section on libraries and workflows — which framework does what, and what is left to you — before any code.published 2026-06-08
Building an LLM Agent in CAP Java with Spring AI
Agent tooling changed in @cap-js/agents 0.9.1, 2026-08-14. Affects Runnable code.
Building an LLM Agent using CAPBuilding an LLM Agent using CAPThe argument is that CAP is already most of what an agent framework wants — services, handlers, a typed model — so the agent is built inside it rather than beside it. AI Core through sap-ai-sdk, then Langchain for the agent and its tools. Long, with a TLDR at the top for people who want the shape without the walk.published 2026-05-27
Building an LLM Agent using CAP
Agent tooling changed in @cap-js/agents 0.9.1, 2026-08-14. Affects Runnable code.
Enriching AI models with SAP AI Core in SAP Business Data CloudEnriching AI models with SAP AI Core in SAP Business Data CloudThe integration between SAP Business Data Cloud and SAP AI Core, through which data products with their semantics feed AI models for benchmarking, custom AI development and agentic analytics and applications. The abstract names the two products and the three uses and states nothing about how the data reaches AI Core or what the integration consists of. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by San Tran and Sandy Tran, written here from SAP's abstract; the recording is not yet published.
Joule and SAP Knowledge Graph: Context-aware AI across SAP solutionsJoule and SAP Knowledge Graph: Context-aware AI across SAP solutionsThe catalogue carries RA107's abstract under this title, and what it describes is SAP AI Core as the management and orchestration layer of an AI architecture: extending Joule Agents in SAP Joule, the model library in Joule Studio for contextual reasoning, connecting data products from SAP Business Data Cloud, and embedding AI in SAP S/4HANA. The SAP Knowledge Graph the title names does not appear in that text, so the edges rest on the abstract as published, and whether the session follows the title or the abstract is not known until it is recorded. A TechEd 2026 session (Wednesday 28 October, Berlin; also RA110V, virtual), presented by Jan Portisch and Pavithra G K, written here from SAP's abstract; the recording is not yet published.
Knowledge graph and agent memory: Build an agent that remembersKnowledge graph and agent memory: Build an agent that remembersThe knowledge graph engine in SAP HANA Cloud as an agent's memory: what the engine, the graph side of graph, spatial and document data, does in an agentic workflow, how an agent keeps what it learns there, the state agent tooling holds between turns, and the SAP AI Core integration through which the database calls LLMs and tabular foundation models such as SAP-RPT-1. The abstract names the engine, the memory role and the AI Core link and does not say how the memory is written or read. DA205 on Tuesday 27 October is the 45-minute talk on the same engine, with a near-identical abstract and a different cast. A two-hour hands-on TechEd 2026 session (Wednesday 28 October, Berlin), presented by Christoph Morgen, Jan Zwickel, Markus Fath and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
Natural Language Queries for SAP CAP via MCP: The LLM Translates, CDS ExecutesNatural Language Queries for SAP CAP via MCP: The LLM Translates, CDS ExecutesThe division of labour is the argument, and it is in the subtitle: the model turns English into a CDS query and CDS runs it, so nothing generates SQL and nothing hallucinates a join. Schema annotations do the resolving. Long, with the package, the repository and the MCP registry entry all linked.Shahid, published 2026-06-25
SAP AI Core deep dive: Models, agents, and business context at scaleSAP AI Core deep dive: Models, agents, and business context at scaleSAP AI Core read as the management and orchestration layer of an AI architecture, beyond the model runtime: SAP's abstract lists extending Joule Agents, the model library in Joule Studio for contextual reasoning, connecting data products from SAP Business Data Cloud, and embedding AI in SAP S/4HANA. It names the connections and not the APIs behind them. A TechEd 2026 session (Tuesday 27 October, Berlin; also RA107V, virtual), presented by Franziska Dobrigkeit and Hadi Hares, written here from SAP's abstract; the recording is not yet published.
SAP Joule for Consultants: Unified knowledge for requirements and designsSAP Joule for Consultants: Unified knowledge for requirements and designsFit-to-standard analysis as a consultant on a cloud transformation project: connecting an organisation's data to SAP Joule for Consultants through SAP AI Core, getting answers from SAP knowledge and that content, then building an expert, loading project files and running guided prompts. The edges are to SAP Joule, of which Joule for Consultants is a part, and to SAP AI Core, named as the connection path; how the data is grounded is left to the session. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Anantharaman Ravi, Natalie Han, Sachin Kaura and Yi Hsuan Lin, written here from SAP's abstract; the recording is not yet published.
SAP-RPT and TabPFN: Get started with tabular foundation modelsSAP-RPT and TabPFN: Get started with tabular foundation modelsTabular foundation models, SAP-RPT and TabPFN, in a hands-on with SAP and Prior Labs: the model families first, then predictions run through SAP AI Core with a workflow built on tabular orchestration and connected to the participant's own data for real-time predictions. A predictive models session with the models as the subject; the abstract does not name the SDK or API the workflow is built with. A TechEd 2026 hands-on session (Thursday 29 October, Berlin), presented by Eliott Kalfon, Janick Zaehringer-Frasch, Johannes Hoehne, Katharina Schell, Nilay Mehta and Sherene Tan, written here from SAP's abstract; no recording is announced.
Ship your own sandboxed AI operations agent to Kyma in two hoursShip your own sandboxed AI operations agent to Kyma in two hoursAn operations agent built and then broken on purpose: the abstract has participants deploy a reasoning agent to SAP BTP, Kyma runtime, connect it to SAP AI Core, give it observability over the runtime and cause a failure for it to diagnose, the operations automation concern with an agent doing the diagnosis. Patterns for cost control and monitoring are promised at the end; the agent framework and how the sandbox is drawn are not named. A TechEd 2026 session (Tuesday 27 October, Berlin, two hours), presented by Christian Lechner, Piotr Tesny, Thorsten Sandfuchs and Vipin VijayKumar, written here from SAP's abstract; the recording is not yet published.
Stop guessing, start counting: How generative AI fixed an inventory messStop guessing, start counting: How generative AI fixed an inventory messAn inventory-counting application a business built on SAP Business AI Platform with SAP HANA Cloud and generative AI, to replace recount lists kept by gut feel across SAP ERP Central Component, SAP S/4HANA and Microsoft Excel; the talk promises the app, its architecture and what went wrong. The generative AI part is LLM integration from application code; the abstract names HANA Cloud and generative AI as the two building blocks and says nothing about how either is used. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Ranjeet Kumar, written here from SAP's abstract; the recording is not yet published.
UI5 AI Features library is now an npm PackageUI5 AI Features library is now an npm PackageThe release note for a demo turning into a dependency, and it is explicit about why that matters: the earlier version worked, but using it meant cloning the repo and copying both halves, which stops working the moment one of them changes. The post walks through what shipping the CAP plugin and the be.wl.ai control library in one npm version buys — a client and server contract that cannot drift — then lists the eleven controls by group, shows the two-line configuration that activates each half, and notes that this version is actually deployed on BTP behind both a standalone approuter and Work Zone. It closes on the demo repository, written with no library source in it as the test that the package stands alone.published 2026-08-31
UI5 AI Features library is now an npm Package
cds 8, line ended. Affects Runnable code.
What an AI infra engineer sees when opening SAP's AI stack (1/3): the model gatewayWhat an AI infra engineer sees when opening SAP's AI stack (1/3): the model gatewayA first look at SAP AI Core's Generative AI Hub from someone who builds gateways outside SAP for a living: the orchestration service harmonizes provider calls onto one API (a model name string switches providers, and SAP Note 3437766 carries the current model list, token rates and deprecation dates), runs a fixed, non-reorderable module pipeline — templating, masking through SAP Data Privacy Integration, grounding, content filtering, then the model call — and retries down an ordered fallback list whose entries can each carry their own model and rules. It places @sap-ai-sdk/orchestration among the official JavaScript, Java and Python SDKs, and notes SAP's own LiteLLM provider as a way to put a different gateway in front of it.amishkush, published 2026-09-30
RAG on CDSUnmapped
Building agentic applications with SAP HANA CloudBuilding agentic applications with SAP HANA CloudA CAP application extended with semantic search and agent features on top of SAP HANA Cloud's vector engine and SAP AI Core, built in a hands-on workshop. The abstract names the parts, CAP, the vector engine and AI Core, and the two additions: semantic search, the retrieval half of retrieval-augmented generation, and LLM-supported agent capabilities inside the application, which is agent tooling. Which embedding model, which CAP runtime and how the agent calls its tools are not stated. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Hui Li, Ritty Joseph, Shraddha Shetty and Tanuja Jadhav, written here from SAP's abstract; the recording is not yet published.
Tool governanceUnmapped
MCP Servers are the New Z-TablesMCP Servers are the New Z-TablesA single CAP service exposed as three overlapping MCP servers tools, queried by the same prompt nineteen times, returned the same tool every time — evidence, the author argues, that tool selection rests on the resemblance between a prompt and a tool's description rather than on any binding a where-used list could enumerate before retiring it. It contrasts that setup with @cap-js/mcp, which exposes a whole service as three generic tools instead of one per operation, and quotes the adapter's own beta documentation admitting no rate limiting, audit logging, input validation or approval workflow, and no use as a gateway to SAP Application APIs. From there it names four small Tool governance practices it has adopted: an owner recorded in the tool's own metadata, logging every invocation, deprecating inside the description, and exposing fewer tools.published 2026-08-21
AuthenticationSAP only
Effective from June 30th 2026 - XSUAA Deprecation of GET Method for OAuth Token RetrievalEffective from June 30th 2026 - XSUAA Deprecation of GET Method for OAuth Token RetrievalEffective June 30th 2026, the SAP Authorization and Trust Management service (XSUAA) deprecates the HTTP GET method for retrieving an OAuth access token from its /oauth/token endpoint, leaving only POST supported in line with RFC 6749. A client still requesting a token via GET with grant_type and credentials in the query string stops working after the cutover and must switch to a POST request with form-encoded body parameters.Yogananda, published 2026-06-14
Evolving the identity lifecycle for an AI-first futureEvolving the identity lifecycle for an AI-first futureCloud Identity Services as the foundation for authentication, identity lifecycle management and access across SAP landscapes, and the agent identity concepts and SAP-managed identity and access management scenarios SAP says reduce operational effort. The edges are to the service and to the two concerns the abstract names it for, Authentication and Identity provisioning; the abstract names the agent identity concepts and does not say what they are. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Sonia Petrescu and Swetta Singh, written here from SAP's abstract; the recording is not yet published.
How SAP secures enterprise AI agents with identity propagationHow SAP secures enterprise AI agents with identity propagationCloud Identity Services as the identity layer for AI agents as well as people: the abstract states that both are managed in one directory, that user context is propagated by token exchange, and that authorisation is enforced at every hop, so no agent holds back-end credentials. Agents from Microsoft, Google and partners take the same flow through the agent gateway. Token exchange across a hop is the authentication side and the per-hop check the authorisation side; what the agent gateway is, and whether it is a product, the abstract does not say. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Gunnar Kosche and Sebastian Ries, written here from SAP's abstract; the recording is not yet published.
Identity lifecycle and governance with SAP services and Microsoft EntraIdentity lifecycle and governance with SAP services and Microsoft EntraCloud Identity Services beside SAP Cloud Identity Access Governance and Microsoft Entra for one user lifecycle across SAP and third-party applications: the abstract states that SAP business roles can be included in Entra access packages, so that provisioning and governance run from Entra in a hybrid environment, which is the identity provisioning concern. Which SAP systems' roles, and over which protocol, is not stated. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Martin Raepple of Microsoft, Plamen Pavlov, Regine Schimmer and Swetta Singh, written here from SAP's abstract; the recording is not yet published.
Road map: SAP Business AI Platform security and SAP Cloud Identity ServicesRoad map: SAP Business AI Platform security and SAP Cloud Identity ServicesThe road map for SAP Business AI Platform's security and compliance services, Cloud Identity Services and SAP Key Management Service among them, and the upcoming changes SAP files under security, governance and compliance. The edge is to Cloud Identity Services, the one named service with an entry here; SAP Key Management Service has none, and the abstract names no item of the road map. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Michael Friedrich and Sascha Vierlinger, written here from SAP's abstract; the recording is not yet published.
Use Free Tier to Subscribe to SAP Document AI Basic UIUse Free Tier to Subscribe to SAP Document AI Basic UIEight steps from an entitled subaccount to the SAP Document AI basic UI open in a browser, and most of them are identity work rather than document work: getting a tenant for Cloud Identity Services, which the basic UI requires, activating the account and establishing trust with the subaccount, then subscribing, creating a user and assigning the Document_Information_Extraction_UI_Templates_Admin role collection. Using the UI to read a document is the subject of Use Machine Learning to Extract Information from Documents with the SAP Document AI Basic UI, which this tutorial names as what to read next.
What’s next for the core platform capabilities of SAP Business AI PlatformWhat’s next for the core platform capabilities of SAP Business AI PlatformA preview of the operations layer beneath SAP Business AI Platform: selected road map highlights across Joule Studio runtime, Cloud Identity Services and SAP Cloud Logging, on how enterprise AI is governed and run. The edges are to the two named services and to SAP Joule, whose agents the Joule Studio runtime runs; the abstract names the three areas and no highlight. A TechEd 2026 session (Tuesday 27 October, Berlin; also XP825V, virtual), presented by Andre Lamego and Jens Huesken, written here from SAP's abstract; the recording is not yet published.