Most AI coding agents compete by adding more features. Pi competes by removing them. Built around just four tools and a 200-word system prompt, Pi takes the opposite bet from Claude Code: keep the core small, push everything else into extensions. Her...
I’ve been hearing a lot lately about fine-tuning being “dead,” but the reality is much more interesting. In this SAP Community post, I share what fine-tuning actually is, where it still shines, and why it continues to matter for real-world enterprise...
Every sprint, we had the same problem. A refinement meeting would go well — real decisions made, edge cases surfaced, implementation approach agreed. Then the ticket would get updated with a fraction of it. By the time a developer picked it up three ...
First, the content of this blog was initially written in Chinese by me (not an AI), but later it was translated into English with the help of AI, and the AI also enhanced and structured the content.Second, the content reflects my own experiences and ...
What if business users could simply ask questions about SAP S/4HANA data and instantly receive interactive visualisations in return? I built a prompt-driven AI agent on top of SAP BusinessObjects that makes this possible transforming natural language...
Alert is generated in Alert Inbox in English by default,You want to generate alert with other language e.g. Japanese.You want to forward alert to Third-Party via SNMP adapter with other language e.g. Japanese.
How I Built an AI Agent That Generates SAP Analytical Artifacts (CDS VDM → Cube → Analytic Query) via OData — Part 1 of 2: Architecture and First ArtifactHow I stopped writing CDS Views by hand and started generating the whole S/4HANA analytical stac...
Introduction:It is possible to connect to a remote PostgreSQL database using Python and then use your application to access and manipulate the data wherever you are. Visual Studio supports writing Python code, and using libraries such as psycopg2 to ...
Personal wikis are powerful — but as they grow, maintaining them becomes a burden. Andrej Karpathy's LLM Wiki concept flips the script: instead of manually keeping sources categorized, refactoring articles, and updating conclusions, you supply theraw...
Introduction:Creating an employee table in a Cloud PostgreSQL database using Python helps in organizing and storing employee information in a structured way. By using libraries like psycopg2, Python can easily connect to the database and execute SQL ...
We’re proud to share that ABAP FS now has 290+ GitHub stars and 53K active installs - gaining 10K new active installs since v2 went live! And this doesn’t even include offline versions probably floating around inside enterprise environments!
Moving on from the two very basic custom Joule Skills created in the previous post — which could only create and update ServiceNow incidents with a very limited and hardcoded set of input values — this blog takes a much bigger leap toward a fully aut...
Enterprise AI becomes significantly more powerful when it can access organization-specific knowledge instead of relying only on generic model responses.With document grounding in SAP Joule, Joule can retrieve information from enterprise repositories ...
In this blog I go over the scenario of creating an agent that based on user queries interprets them, translates mails and content to business partner and material, and then creates a sales order in the system. This is part 1, in parts 2 and 3 I will ...
Step-by-step guide to deploying Claude Sonnet 4, Claude Haiku 4.5, and GPT-4o through SAP AI Core and the Generative AI Hub — with working Python code, model selection guidance for SAP-specific use cases, and a practical comparison table. Updated fol...
Drift is not one thing. An agent can drift in four independent directions simultaneously: model, data, supervision, and scope. None of the four announces itself. The combination can be more dangerous than any single vector. This post covers the four ...
An agent that is not monitored does not sit and wait. It continues to act, autonomously, at scale, until a supplier calls to ask about orders that never arrived. This post covers the six observation instruments every agentic product needs, why automa...
The QA mental model that has served you for twenty years breaks in exactly three places when software starts making decisions instead of executing code. Pass@K replaces binary pass/fail. Compound probability means component accuracy and system reliab...
Introduction:Installing PostgreSQL to use it on the server will assist you in storing and processing data used by your application safely.It will imply the installation of PostgreSQL, the creation of a database, and the configuration of server access...
Claude Code ships powerful primitives - skills, memory, subagents, MCP servers. But primitives alone do not make a production system. This post teaches the harness architecture - seven composable pillars that turn Claude Code into a predictable, cont...
Most agentic products ship with only the agent designed. The supervisory system, how humans monitor, intervene, audit, and recover from what the agent does, is an afterthought. This post covers the four runtime artifacts every agentic product require...
Explore how AI transforms processes for your business using Customer Projects as an example. From opportunity to delivery and closure, AI helps you make better decisions, automate routine tasks, and gain real-time insights at every stage. Every succe...
Business cases for agentic AI are systematically 40 to 60 percent too low. Not because people are careless. Because the cost structure is genuinely different, token pricing is not what you expect, and the governance stack nobody budgeted is the line ...
The most expensive mistake in agentic AI does not happen in production. It happens before a single line of engineering is written, when a team decides to build an agent for a problem that should have been solved with a clearer dashboard or a better r...
A practical guide to working effectively with Claude Code. Covers workflow principles, planning strategies, model selection, and the full tooling ecosystem.Who This Is ForDevelopers — from first-time Claude Code users to power users. Part 1 covers pr...
"Build a A Agentic Hyrid RAG system that combines knowledge graphs and vector search — withself-correcting agents on SAP BTP & A step-by-step guide to building Agentic Hybrid RAG with Python, HANA Cloud, and AI Core."
Seven mental model shifts every product manager needs before any agentic AI project begins. Not because they are advanced. Because they are prerequisites. From suggestion vs. action to the two channels most teams never build — the concepts that separ...
Agentic AI is not just smarter software. It is probabilistic, it acts autonomously, and it does not know when to stop and ask for help. This series maps the frameworks product managers need to design the system around the agent, not just the agent it...
In one of the most crucial sectors – Aviation, safety relies on identifying and mitigating risks through robust, multi-layered systems designed to counter cognitive biases and organizational failures. Modern safety management integrates human factors...
SAP Joule isn’t a magical ITSM plug that sits between systems wearing a badge. It’s more like an enthusiastic translator at a networking event who says, “Oh, you’ve got an incident in ServiceNow? I’ll just whisper that into the API for you.”
Introduction:A Python virtual environment is a local directory that maintains project dependencies distinct from the rest of the system. It prevents conflicts of version and provides a uniform development in various presuppositions. This is needed to...
Exploring how AI can actually help in SAP QA, from writing test cases to debugging automation, with real learnings and limitations from my experience.
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.
| User | Count |
|---|---|
| 27 | |
| 17 | |
| 12 | |
| 12 | |
| 7 | |
| 6 | |
| 6 | |
| 4 | |
| 4 | |
| 4 |
| Subject | Likes |
|---|---|
| 20 | |
| 9 | |
| 6 | |
| 6 | |
| 5 | |
| 5 | |
| 4 | |
| 4 |