Thoughts from SAP TechEd, Bangalore

SAP did a very nice job bringing TechEd in Bangalore, India to analysts and other registered users around the world. They had a preview for analysts on Monday and had keynotes on Thursday and Friday conveniently timed for viewers who were several time zones away.

There were a slew of announcements, especially around GenAI and other AI , growing BTP product functionality and growing customer base for the development tools.

I was particularly fascinated by the Vector Engine, Datasphere and the Build Code discussions.

Juergen Mueller, the CTO simplified vector talk – which honestly, I mostly associate with pilot communications with air traffic controllers. We live in a 3-dimensional world and vectors allow for representation of many more – hundreds and thousands of - dimensions. As Juergen explained “The embedding function maps semantically similar text to vectors close to each other in a high dimensional space. Running a semantic search, then simply becomes a nearest neighbor search and that vector space with 1536 dimensions. So where it differentiates is you're not searching content, you're searching for condensed semantic meaning.” It should hopefully allow us to go beyond today’s excitement around LLM’s powering text and document-centric sources to include many more structured and unstructured data formats.

Datasphere promises to unify all your data into a single semantic model. Over the years, customers have been exporting SAP data into data lakes. SAP’s delays in integrating many of its acquisitions encouraged some of that thinking.  Competitors have also been encouraging customers to bring operational data into their supposedly “more user friendly’ analytical tools.  From my early conversations with SAP customers there is plenty of excitement around Datasphere

Build Code brings generative AI and Joule copilot capabilities to ease/speed up development of new applications and extensions to SAP applications. There was plenty of talk around how that would accelerate low and no-code development.

However, reality struck me when Juergen jokingly said “I didn't know if I will have a headache tonight thinking about the space that has more than 1500 dimensions”.

It’s tough to reconcile enterprise complexity with promises of citizen developers.  I am hearing similar promises from hyperscalers and IBM that turbocharged DevOps will be the killer app from GenAI. The rapid adoption of ChatGPT has fired up the imagination of every enterprise vendor – we have to make our tools way more consumer friendly.

Like our solar system, enterprise landscapes continue to expand exponentially.  After 25 years of cloud applications you cannot find decent choice for most cells if you look at a grid by country/by industry.   

I wished I had gone in person to Bangalore. There were TechEd strategy sessions that were not streamed I would have like to have watched. But even more I would have liked to have visited with many Indian outsourcers and tried to understand how they are using GenAI on their own projects.

As an industry we have done several million ERP and CRM implementations, global rollouts and upgrades. Vast number are around SAP products. Which means we have at least 10X the number of artifacts – test scripts, parameter configurations, data conversion code, training modules etc. Can we populate LLMs and generate fairly decent first versions for the next 10,000 or 100,000 customers, rather than reinventing the wheel each time? Can you imagine the labor savings we could deliver?

I did several trips to Bangalore and other Indian and E. European cities in the first few years at Deal Architect I founded in 2003. I took C level customer executives on due diligence trips to many vendor campuses. May be time to start doing more of that.

We are staring at a massively different enterprise landscape. New DevOps tools. And very promising roles for everyday developers.

Time for new approaches.