I built an internal AI data tool at SAP. It runs on BTP, talks to six live data sources, and lets any PM on my team ask questions in plain English. This is what modern PM work looks like when you treat AI as infrastructure.
Five field notes from a few months of agents on top of the ADT API in my S/4HANA 2023 lab, and five questions I would like to hear your answers to.
Most development frameworks put evaluation at the end. For deterministic software, that was late but recoverable. For agentic AI built with coding agents, it is the wrong sequence - and the cost shows up in production, not in the review.
This blog explores how companies are putting MCP(Model Context Protocol) into practice, drawing on insights from AGNTCon + MCPCon Europe. It covers protocol evolution, tool discovery, skills and agent execution, alongside our work on Open Resource Di...
Three weeks ago a logistic regression beat eight LLMs at reading job postings. I gave it a rematch against a model built for tables. TabPFN-3.5 beat the lion, beat GPT-6 Astra and Claude Fable on the same postings, ran in 12 seconds per thousand, cos...
Letting the LLM decide what to fetch works. It's also non-deterministic, sequentially slow, and hard to audit.A short note on declarative pre-fetch as the default for enterprise agents and where tool calling is still the right answer
There is a long-standing debate about the use of IA and productivity in the corporate environment. This article explores the real-life experiences of an AI Consultant and how the mix of experience, collaboration, and reskilling generated outstanding ...
AI helps us learn and write code. We have been shipping code faster than ever. Someone with no IT background can create software now. But software is not just code. It is structure, security, governance and much more. We deal with sensitive data. An ...
When we started this blog post series, we asked a hard question: how do we keep humans meaningfully involved as AI systems get more autonomous every day? Today, that question is more urgent than ever. SAP’s vision of the Autonomous Enterprise promise...
SAP has spent 2026 building governance infrastructure for AI agents — a verification workflow through AI Agent Hub, policy enforcement through MCP Gateway. Both promise trust badges and audit trails. Neither can deliver on that promise against an obj...
What if your compliance team could stop chasing false alarms and start focusing on what really matters? That’s exactly what happens when AI moves from being a helpful assistant to a tool that automatically handles routine cases.
Part 3 showed how SAP's Custom Code Migration Agent handles the mechanical half of clean core work. This part addresses what the agent explicitly hands back to a human: the objects that get side-by-side extended into CAPM. Done under deadline pressur...
With the advent of AI agents, there is increasing interest in a topic that had been around for a long time in the AI Ethics world: Human oversight and determination. But why did it become so important now, and what does it mean?
A deep-dive into building AI workflows in Joule that turn tabular structured data into key supply chain decision engines using SAP-RPT-1.5 Tabular AI model.
n8n workflows, as you saw in the Week 3 challenge, can be defined by JSON text file, and therefore you can easily vibe code to create complex and useful workflows. I will show you what I did do manage the challenge itself.
A personal experiment: an ABAP report sends a service quotation ID to n8n, n8n applies multi-stage email approval rules, and only the last Approve PATCHes the quotation to Released in SAP. Not a replacement for SAP Business Workflow or Flexible Workf...
Most developers trying to cut AI costs focus on model selection. But the bigger lever is what your agent generates in the first place. Two open-source plugins — Caveman and Ponytail — tackle this from different angles: one cuts the verbosity of agent...
The operator did not vanish when the agent arrived. She split. What she knew became the agent's context and bounds. What she checked before committing became the supervisory surface. The only casualty was the dashboard, and most agents are being buil...
Most AI systems stop at a single agent talking to a single model. A2A is the open protocol that lets agents from different frameworks and teams discover each other, delegate work, and exchange results. This article shows you how to build it from scra...
Everyone is abuzz about the new and improved Joule Studio, announced at Sapphire in May and expected out in the fall. We wanted to take this month’s developer challenge to prepare you for all the excitement that is likely to occur at SAP TechEd in Oc...
How a distributed nervous system inspired the way I organize Claude's knowledge.An octopus has around 500 million neurons in a massive nervous system. Where humans concentrate most neurons in the head, an octopus does the opposite. About two-thirds l...
The hype is on on humanoid robots - price drops make them payable, increasing capabilities, better sensors, more computing power and stroner batteries make them affordable and applicable in a variety of use cases - but is the humanoid robot the answe...
The Architecture That Doesn't Exist Yet Is a TeamPost 11, The Agentic AI Team seriesA claims agent denies a man's insulin reimbursement after a refrigeration outage. Nothing about the denial breaks a rule. The exclusion is ambiguous, the agent reads ...
The Failure No One Is WatchingPost 8, The Agentic AI Team seriesEighteen months after an agentic product ships is the moment it is most likely to be quietly broken and least likely to be caught. Not because anyone stopped watching. Because everyone k...
The Empty ColumnPost 7, The Agentic AI Team seriesTake any team that ships an agentic product and ask them to draw their team structure on a whiteboard. They will draw it fast, because they have drawn it a hundred times before. A product manager deci...
Is the PM Still the Hero?Post 6, The Agentic AI Team seriesSearch for "product manager" and "agentic AI" together and you will find no shortage of PMs telling other PMs that the agentic era finally makes the PM the center of everything. The engineer ...
Do We Still Need Scrum?Post 4, The Agentic AI Team seriesA delivery team plans a two-week sprint the way it always has. Monday, the backlog is groomed. Tuesday, the sprint starts. Over the next two days, an agent drafts most of the committed features...
What Does a Team of 10 Developers Look Like Now?Post 3, The Agentic AI Team seriesPicture a ten-person engineering team six months into using a coding agent well. Nobody writes much code from scratch anymore. What they do, all day, is read pull reque...
The Employee You Never OnboardedPost 10, The Agentic AI Team seriesA company stands up an agent that triages inbound support tickets, drafts responses, and escalates the hard cases to a person. Procurement logged it as a software purchase. IT logged ...
The Green Checkmark Nobody OwnedPost 9, The Agentic AI Team seriesAn enterprise agent handles vendor onboarding. It checks a new supplier against policy, flags exceptions, and clears the routine cases without a human in the loop. Before launch it ran...
The Architect Was Right All AlongPost 5, The Agentic AI Team seriesThere was always one person on the project who was not really on the team. She did not sit in the standup, did not own a backlog, did not ship a feature. She showed up early, at the p...
Is There Still a UX?Post 2, The Agentic AI Team seriesA claims adjuster opens her laptop Monday morning. Overnight, an agent processed a hundred and forty spoilage claims: burst pipes, power outages, a warehouse freezer failure. It paid a hundred and...
The Team Didn't Shrink. It Reshaped.Post 1, The Agentic AI Team seriesA team ships an agent that handles procurement. It reads a purchase requisition, checks it against policy, compares suppliers, and places the order, with no human in the middle for...
The Sixth Archetype the Maps ForgotPost 0, The Agentic AI Team seriesThere was a time when photography was a planned profession. Film gave you thirty-six frames, each one cost money, and none of them existed until a lab developed the roll days later....
What if your AI coding assistant already knew every relevant product standard before you typed a single line?
What happens when you combine SAP's Relational Pretrained Transformer with a multi-agent LLM system and ask it to predict World Cup 2026 match scores? Surprisingly decent football analysis — and one very honest timeout.
Claude Generates So Much - Here's How I Actually Keep UpAI is producing an almost comical amount of output these days. In a single session, Claude can scaffold a feature, write the tests, refactor two files, explain the architecture, and suggest thre...
Post 8 — AI Product Management seriesIn December 1978, United Airlines Flight 173 ran out of fuel while circling Portland, Oregon. The aircraft was mechanically sound. The crew knew the fuel state was critical. The captain, fixated on a landing gear ...
Post 9 — AI Product Management seriesIn 2021, a research team at the University of Michigan published an audit of the most widely deployed sepsis prediction algorithm in American hospitals. Epic Systems had marketed the Epic Sepsis Model with a claim...
The PRD worked when the hard part was building. With agents, building is the easy part, a prototype takes an afternoon. The hard part is deciding what the agent should do, where its authority stops, and how anyone knows when it's wrong. That work spl...
"After 30 days, we'll move the agent to full autonomy." That's a schedule, not a safety criterion. A clean record usually means the hard cases haven't come up yet, not that the agent can handle them. Why autonomy has to be earned against evidence, an...
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...
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...
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...
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...
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...
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GTLC_Vamsi
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My productivity is boosted with Joule work desktop...
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