SAP Draws a Perimeter around Agentic AI and What That Means for the Rest of US
The most consequential enterprise AI governance document published this year arrived in late April with surprisingly little fanfare. SAP’s updated API Policy, version 4/2026, is a short document in plain English. The clause that is most interesting is Section 2.2.2. It restricts how autonomous and generative AI systems are permitted to interact with SAP APIs. Read literally, it has the potential to change the architecture of agentic AI projects across every SAP customer landscape. Read carefully, it is also more interesting than the lock-in headlines suggest. The policy targets a specific category of AI behavior, not AI as such. It connects to commercial mechanics that go well beyond API stability. And the literal text, in its current form, will probably not survive the next two policy revisions intact. There is a lot to unpack. I will walk through what the policy actually says, how the SAP-watching community is reading it, what the rest of the major enterprise vendors are doing in comparison, what counts as an “endorsed architecture”, and what customers and partners should be doing about it now. I’ll close with a view on whether the policy can stand the test of time. What Section 2.2.2 actually says The operative sentence is direct. “Except through and within the limits of SAP-endorsed architectures, data services, or service-specific pathways expressly identified and intended for such purposes, SAP prohibits API use for interaction or integration with semi-autonomous or generative AI systems that plan, select, or execute sequences of API calls”. The same paragraph also prohibits scraping, harvesting, or systematic large-scale data extraction. Three things flow from that. First, only Published APIs,...
The Orchestration Layer in Enterprise AI Just Got Named. It Has a Gemini Logo on It.
What Google Cloud Next 2026 actually told us about the titan pecking order Google Cloud Next 2026 wrapped last week. The official version of the story is the one Google wanted you to read: 260 announcements, 1,302 customer use cases, the Gemini Enterprise Agent Platform, eighth-generation TPUs, a $750 million partner fund, an $240 billion Marketplace backlog. Big numbers. On-message keynote. Tidy “agentic era” framing. The more interesting story is who showed up to validate it, and what Google actually built underneath. Five of the seven enterprise titans I track walked into Las Vegas and announced expanded partnerships that all rest on the same architecture: Gemini Enterprise as the agent control plane, with the titan’s product playing the role of premium ingredient. Salesforce. SAP. ServiceNow. Oracle. Adobe. Add Workday and Palantir Technologies to the picture, both adjacent to my titan list but visibly aligned in the same direction. Two titans were not in the picture. Microsoft, because Copilot is the direct counter-position and Cloud Next is not Microsoft’s stage. Zoho, because Zoho’s stack does not need a Google motion and Zoho’s buyer is not the same buyer. Both absences matter. More about them a little later. What Google actually built Let’s start with the framing. Google did not just ship a model platform with new features. It repositioned Google Cloud from “AI development environment” to enterprise agent control plane. Vertex AI services and roadmap evolutions are now delivered through the new Agent Platform rather than as a standalone product. That is not a naming change, it’s an entirely different playground. The Agent Platform stack now visibly includes: Agent Identity...
The Agent Wars Are Over. The Substrate Wars Just Started
Three titan announcements in two weeks reveal what enterprise software vendors are actually fighting over in 2026, and it is not agents. If you have been tracking enterprise AI announcements through 2025, you have been watching a race about agent counts. How many prebuilt agents. How many industry-specific use cases. How many customer stories. Agents were the marketing, the demo, the SKU. A year of the same playbook. Something shifted in April 2026. Inside a two-week window, Salesforce, SAP, and ServiceNow each published an announcement that, at first glance, looks like more of the same agent theater. Salesforce launched Headless 360 at TDX 2026 and the Agentforce Experience Layer. SAP pushed a simplified-architecture argument alongside a persistent agent memory layer on BTP. ServiceNow rolled out Context Engine and, on its SPM community blog, Fred Champlain published an essay reframing governance itself as “strategic decision debt”. Different products. Different audiences. The same structural move. All three titans just walked one layer down the stack. Read individually, each announcement is a product release. Read together, they are a category shift. The competition is no longer about who has the best agent. It is about who owns the substrate those agents operate on. And each titan is staking a different piece of it. The Pattern Nobody Is Naming Strip the vendor branding from all three sets of material and the structural claim is identical: “Your agents are only as good as the layer underneath them. The data they ground on, the logic they inherit, the memory they carry, the permissions they respect, and the decisions they represent. That layer is what we...
The vCon Reality Check: Moving Beyond Generative Hype to Actual Conversational Architecture
Welcome to Reality. Leave Your “AI Magic” at the Door. The AI hype train is moving at terminal velocity, but the tracks are missing. We have vendors pitching artificial general intelligence that will solve world peace, and executives panicking because they think a conversational wrapper around a large language model is a strategy. In the latest episode of CRMKonvos, Ralf sat down with Dan Miller, formerly of Opus Research to discuss something that actually matters: infrastructure. Specifically, we are talking about vCons, or Virtual Conversations. It is an IETF standard that threatens to finally bring architectural integrity to the chaotic mess we currently call conversational AI. TL;DR If you want to watch the full CRMKonvo, please go ahead here (optimized for smartphones) or here (optimized for tablets/computers). Else, be my guest and continue to read. Or do both … The “PDF Problem”: Why Your Call Recordings Are Useless For decades, the contact center has relied on the clunky mechanics of Automatic Call Distributors, green screen terminals, and audio recordings. As Dan rightly points out, a traditional call recording is essentially the conversational equivalent of a PDF. You get a static document or an audio file that you cannot easily manipulate, query, or extract meaningful context from. It captures one part of the conversation at a specific point in time, freezes it, and historically required overnight batch processing just to transcribe it for basic analytics. These days, we have swarms of AI agents acting on our behalf, yet the enterprise plumbing remains grossly neglected. You are trying to deliver a data stream simultaneously with historical information about that stream to...