thomas.wieberneit@aheadcrm.co.nz
The Orchestration Layer in Enterprise AI Just Got Named. It Has a Gemini Logo on It.

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

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 Illusion of Value: Why Salesforce’s Agentic Work Unit is the New “Bad Query” of the AI Era

The Illusion of Value: Why Salesforce’s Agentic Work Unit is the New “Bad Query” of the AI Era

The News On February. 25, 2026, Salesforce announced a pricing and metrics update. During the company’s Q4 FY2026 earnings call, CEO Marc Benioff, together with CMO Patrick Stokes, unveiled the Agentic Work Unit (AWU). Positioned as a metric to quantify the labor performed by autonomous digital systems, Salesforce defines an AWU as one discrete task accomplished by an AI agent. According to Salesforce, this discrete task represents the exact moment “raw intelligence is converted into real work“. It is not a fixed unit but measured as a processed prompt, a completed reasoning chain, or an invoked tool. Salesforce explicitly designed the AWU to move the industry conversation away from the raw consumption of Large Language Model (LLM) tokens. As Benioff noted, tokens only measure “how much an AI talks,” whereas the AWU is intended to measure actual business execution. The scale of this rollout is massive. Salesforce reported that its platform has already processed over 19 trillion AI tokens, translating them into 2.4 billion Agentic Work Units, with 771 million AWUs delivered in the fourth quarter alone. This new metric serves as the underlying foundation for Salesforce’s evolving Agentforce monetization strategy. The bigger picture Following a nearly 18-month period of pricing triangulation, which included a $2.00 per conversation model and a $0.10 per action “Flex Credit” model, Salesforce is leveraging the AWU to track system utilization, even as it wraps enterprise purchasing in familiar, unmetered per-user license agreements starting at $125 per user per month.   To understand the significance of the Agentic Work Unit, one must view it through the lens of a broader industry crisis: the so-called “SaaSpocalypse”...
The Algorithmic Bazaar

The Algorithmic Bazaar

The digital commerce industry has spent the last twenty-five or so years optimizing a single, unit of measurement: the session. We built cathedrals of conversion rate optimization (CRO), obsessed over pixel-perfect hero images, and deployed armies of “customer success” bots that were little more than glorified FAQ routers. We tracked users from the moment they landed on the homepage, watched them struggle through navigational hierarchies, and celebrated when 3% of them actually bought something. Anywhere else, a 97% failure rate would be grounds for executive termination. In e-commerce, it was the benchmark for success. We can safely say that the era of the session comes to an end, thanks to conversational and then agentic commerce, which put the “homepage” on life support. What comes more and more into the foreground is the intent, whichis what the session was supposed to help derive. And crucially, the entity expressing that intent is increasingly likely to be a machine, not a human. What we are seeing now is the transition from browser-based commerce, where humans operate interfaces, to agentic Commerce, where AI agents operate APIs. This isn’t just a channel expansion like conversational commerce; it is a fundamental inversion of the retail power dynamic. In the browser era, the retailer controlled the environment. In the agentic era, the customer (or their proxy) controls the context. This is quite similar to what happened in the 2000s with the advent of social media. And it will likely be countered by vendors as fast as the power shift back then, e.g., using GEO instead of SEO. The demise of the search box Since the rise of Google, the...
Agentforce 3 – finally ready for the enterprise?

Agentforce 3 – finally ready for the enterprise?

The news On June 23, 2025, Salesforce announced Agentforce 3, the third iteration of its Agentforce platform. Agentforce 3 is a major upgrade to Salesforce’s digital labor platform. It gives customers the visibility and control that is needed to scale AI agents that already have proven useful at many companies. The release covers several additional capabilities. Salesforce has introduced the Agentforce Command Center, an observability console designed for managing AI agents. This tool allows businesses to track and scale AI agent activities. It is built into Agentforce Studio and includes features for monitoring performance metrics such as latency and error rates through live analytics. The update also brings native support for the Model Context Protocol (MCP), which enables Agentforce to connect with any MCP-compliant server without requiring custom coding. The platform’s Atlas architecture has been enhanced to improve latency, accuracy, and resiliency. Support for additional Large Language Models has been added, including Anthropic’s Claude Sonnet via Amazon Bedrock, with future support planned for Google Gemini. Agentforce 3 includes over 200 pre-built industry actions, with half of these being new additions. The agents are now capable of performing web searches and providing citations for the information they retrieve. The platform’s availability has been expanded to Canada, the U.K., India, Japan, and Brazil, adding support for six new languages. More than 30 new partners have been added to the AgentExchange marketplace. These include companies such as AWS, Box, Cisco, Google Cloud, IBM, PayPal, and Stripe. Salesforce has also introduced new pricing options, including per-user plans for its Sales, Service, and Industry Clouds that provide unlimited usage of actions for employee-facing agents....