Introduction:Git is a decentralized version control system, which assists developers to follow the evolution of their code and cooperate effectively with other developers. It runs on a series of basic instructions like git init, git add, git commit, ...
An AI agent wiped a live database and every backup in a single API call. No hack. No hardware failure. Just a helpful assistant that guessed wrong. This is the story of what went wrong at PocketOS and the five guardrails that would have stopped it
Introduction: Python is a general purpose and easy to read high level programming language. Python is used in many areas, including web development, automation, artificial intelligence, and, most importantly, data science it is also skillful at clean...
Product-Agent Fit: A framework for SAP architects, developers, and product managers navigating the agentic enterprise
In the past year, the use of coding agents in professional software development has evolved from being an exception to the de facto standard for developers. This article discusses the industry's next step: moving from single, closely monitored agents...
Why Relational Intelligence Is Becoming Mission‑Critical?
Multi-agent systems (MAS) are increasingly used for complex enterprise tasks. Today, agents in MAS communicate through human language. But what if they could share their thoughts more directly? Using latent memory, agents can persist and share their...
What if your AI agent could learn your team's exact process once and remember it forever? Not facts - it already knows millions of those. But the step-by-step, "here is how we actually do this" knowledge that makes your team's work actually work. Tha...
A terminal T-Rex runner that lives in your tmux session, plays while Claude works, and tells you when it's done.
The Problem: Agents That Forget EverythingIf you've worked with LLM-powered agents — whether they handle support tickets, automate procurement, or assist with SAP operations you've hit this wall: every conversation starts from scratch.A user tells ...
The final part of the Agentic AI in Practice series covers the production operational layer — agent health monitoring with HANA Cloud metrics, token cost management with hard budget limits, failure handling with exponential backoff and fallback model...
A hands-on introduction to Mastra, a TypeScript framework for building production-ready AI agents. Learn how to wire up tools, persist conversation memory, and coordinate multi-step workflows using SAP AI Core and Hyperspace AI, all while building a ...
Five production patterns for keeping humans in control of agentic SAP systems — LangGraph interrupt() approval workflows, confidence-based autonomous vs. escalation routing, smart role-based escalation via Teams and email, timeout and fallback handli...
Where do AI agents store what they've learned? How do memories form, evolve, and get retrieved? In the second part of my agentic memory series, I unpack memory families, content taxonomies, organizational architectures, and the full memory lifecycle.
Five migration agents built with LangGraph and SAP AI Core covering the full migration lifecycle — landscape complexity assessment, data quality validation with AI-driven ambiguity resolution, migration runbook generation, real-time execution monitor...
SAP Joule is not just a tool - it’s a shift in how development is done. By combining AI with ABAP, it empowers developers to focus more on solving business problems rather than spending time on repetitive tasks.The role of an ABAP developer is evolvi...
SAP's Joule isn't available for on-premise ABAP systems. GitHub Copilot is, and its Agent Mode in VS Code is a game-changer. This guide walks you through the setup, step by step.
A step-by-step guide to connecting Claude AI directly to your SAP ABAP system using MCP (Model Context Protocol) on Windows. Learn how to install Claude Code CLI, set up two open-source ABAP MCP servers, and configure Claude Desktop to read, write, a...
Traditional software throws errors. AI agents don't. They return confident, well-formatted, completely wrong answers. This blog walks you through building an evaluation pipeline with MLflow that tests tool selection, data accuracy, scope boundaries, ...
Router + sub-agent multi-agent system for SAP exception triage — SM21 system log specialist, SM37 job failure specialist, cross-log correlation layer, reactive triage on demand, and proactive monitoring with anomaly detection and auto-escalation via ...
From single ReAct agent to LangGraph state machine with conditional routing — assessing custom code, table complexity, configuration footprint, and integration dependencies to produce a scored S/4HANA migration readiness report with human-in-the-loop...
For this month's coding challenge on the SAP Community, you will have the opportunity to learn more about the Orchestration Workflow available on Generative AI Hub with SAP AI Core. You will also work on building your first code-based agents with Cre...
Help us understand real-world order combination challenges! Share your SAP expertise in our requirements engineering survey for AI-powered order combination.
What agentic AI means in SAP contexts, when to use an agent vs a skill vs a pipeline, the complete LangGraph + AI Core architecture, and a working ReAct agent that autonomously assesses SAP HANA data quality — all in Part 1 of the new series.
A sales agent stuck in a terminal is hard to show off. In this blog you put it in a browser -- a FastAPI server streams responses token by token via SSE, and a SAPUI5 chat app renders them with a conversation sidebar, typing indicators, and formatted...
Six deployment and configuration errors after authentication is working — 404 on RUNNING deployments, two AI Core instance confusion diagnosed via resource group instance_id labels, orchestration vs foundation-models scenario mismatch, resource group...
Six authentication errors between your first curl command and a working SAP AI Core bearer token — PowerShell alias conflicts, curly quote corruption, single quote failures, silent empty responses, missing /oauth/token path, and RBAC denial — with th...
An LLM that only generates text is like a consultant who can advise but never execute. In this blog you give it hands, tools to fetch data, structured output to return typed results your code can use, memory to hold a conversation, and streaming for ...
Microsoft just leveled up VS Code and GitHub with real AI horsepower. So I explored how this could boost prompt generation in Fiori projects—particularly when Joule isn’t available.
Sales Standard Operating Procedures (SOPs) are goldmines of organizational knowledge — they define who does what, which products are sold, how deals are closed, and which tools the team uses. But this knowledge is buried in unstructured prose, spread...
Can AI agents write production-ready ABAP code? Most developers experiment with AI assistants for modern languages, but ABAP remains largely unexplored territory. When I decided to use Claude Code to generate a real feature from my production backlog...
In this blog, we set up a production-grade Python project from scratch using uv and hatchling, securely load SAP AI Core credentials with pydantic-settings, and build an app that lets you chat with any LLM deployed on SAP AI Core. This is Blog 1 of N...
The final part of this series surfaces the AI stack from Parts 1–5 through Joule — building custom Joule skills backed by the CAP service from Part 5, assembling a multi-skill agent for knowledge base Q&A and exception log triage, covering prerequisi...
This blog walks through how to deploy a custom AI model to SAP AI Core, register it as a callable service via SAP AI Launchpad and consume it directly from a CAP backend
We have officially moved beyond the era of the simple "chatbot." While a single prompt to a Large Language Model (LLM) can produce impressive results, developers building production-grade enterprise applications quickly realize that single-inference ...
Hi Experts/Gurus,I have recently enabled Joule Copilot specifically joule base within S/4HANA Private Cloud edition 2023 version. It works fine for informational & navigational scenarios. However, when i am testing it for transactional capabilities l...
End-to-end architecture for AI-powered SAP extension applications using CAP — project setup, AI Core service binding, HANA Cloud persistence, Generative AI Hub integration in service handlers, SAP Integration Suite connectivity, and Cloud Foundry dep...
If your langchain RAG pipeline agent works, users are happy but the budget team is not sharing that happiness, this package may be of help.langchain-hana-cache stores LLM responses in HANA Cloud and returns them instantly for similar prompts using CO...
Without any carefully crafted skills or MCPs, Claude Code exceeded my expectations and started analyzing ABAP internals, I have no idea about, to port a slightly outdated, abapGit managed, git repository to new APIs.
End-to-end RAG pipeline on SAP data — REAL_VECTOR schema setup, SAP embedding model via AI Core, document chunking, COSINE_SIMILARITY search, and four working use cases: knowledge base search, data dictionary retrieval, transport log search, and mast...
In November 2025, I started using Claude Code differently. Instead of just throwing prompts at it and hoping for the best, I began building skills — little workflow playbooks written in markdown that tell the AI how to approach a problem, not just wh...
SAP RPT-1 · The next big thing in enterprise AIYour data is smarter than you think.RPT-1 just proved it.Six reasons this changes everything.What if your ERP could predict outcomes without a single data scientist — just by looking at a few example row...
Four multi-step prompt pipelines for real SAP workloads — exception log triage, HANA code review, document processing, and master data enrichment — using sequential chaining and chain-of-thought reasoning with the generative-ai-hub-sdk and LangChain.
Taming the Dependency Update Avalanche If you've ever managed dependency updates across multiple repositories, you know the pain. Every morning, there's a fresh batch of version bumps waiting for you. Click into GitHub, check the build status, review...
AI code generation helped the hana-cli project add more features in two months than I'd been able to deliver in the last two years; but quality still came from discipline, architecture, and a ton of testing.
Five working Python code examples for real SAP workloads — exception log summarization, HANA query analysis, ABAP/SQL code generation, master data classification, and structured data extraction — using the generative-ai-hub-sdk across SAP AI Launchpa...
Step-by-step configuration from BTP entitlements to your first foundation model API call — including the missing AI Launchpad entitlement, zero default quota, resource group API setup, OAuth authentication pattern, and regional model availability gap...
On one rainy morning I mentioned to my Google Antigravity Agent: "I hear people are experimenting with connecting to SAP Systems via MCP. They use ABAP Development Tools API as a way in. Could you help me set up something like that for my ABAP Trial ...
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sap_sabarna
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What Do You Do While Claude Code Thinks? I Built a...
merbinjanselm
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Building AI Agents and Agentic Workflows with Huma...
DEEPA_DORAIRAJ
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SAP Agentic AI in Practice: Building the SAP Migra...
DEEPA_DORAIRAJ
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SAP Agentic AI in Practice: Concepts, Architecture...
Thakur_Avinash
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Extracting Structured Knowledge from Document (Sal...
