thomas.wieberneit@aheadcrm.co.nz
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....
Data Wars: SAP Vs. Salesforce In The AI-Driven Enterprise Future

Data Wars: SAP Vs. Salesforce In The AI-Driven Enterprise Future

The past weeks certainly brought a lot of news, with SAP Sapphire and Salesforce’s surely strategically timed announcement of acquiring Informatica, ranging at the top. I have covered both in recent articles. The enterprise software landscape is crackling with energy, and Artificial Intelligence (AI) is certainly the star of the show. It isn’t anymore about AI as a mere feature; it’s about AI as the strategic core of enterprise software. Two recent announcements underscored this shift: SAP’s ambitious AI-centric vision that was unveiled at its Sapphire 2025 conference, and, arriving hot on its heels, Salesforce’s agreement to acquire data management titan Informatica for $8 billion. Both signal an intensified battle for AI supremacy, where trusted, enterprise-wide data is the undisputed new monarch. Of course, SAP and Salesforce are not the only ones duking this one out. SAP’s Sapphire Vision: An AI-Powered, Integrated Enterprise At its Sapphire 2025 event in Orlando, SAP laid out a sweeping vision for an AI-driven future. The central themes resonating from Sapphire were “AI everywhere” and “the AI flywheel”, with intelligence deeply woven into its integrated suite of applications and powered by the SAP Business Data Cloud as a strong, unified data layer. Joule, SAP’s AI copilot, is slated to become “omnipresent,” extending its reach not only across the entire SAP ecosystem but also into third-party applications. It’s designed to proactively assist users and launch autonomous “Joule Agents” to automate a wide array of workflows. SAP has ambitious plans to significantly expand its library of these specialized agents. Underpinning this is the SAP AI Foundation that includes Joule Studio for agent development, a Knowledge Graph...
Informatica – Salesforce’s Precious; one Platform to Govern all Data

Informatica – Salesforce’s Precious; one Platform to Govern all Data

The news On May 27, 2025, Salesforce announced that it has reached a definitive agreement to acquire Informatica for about $8bn. According to the press release, “bringing together Informatica’s cloud-native capabilities — including its extensive data catalog, data integration, governance, quality and privacy, metadata management, and MDM — with the Salesforce platform will unlock new capabilities for Salesforce’s enterprise data stack, delivering a complete solution to the challenges of AI at scale”. The acquisition is planned to enhance Salesforce’ data foundation which is critical for deploying agentic AI. “The combination of Informatica’s rich data catalog, data integration, governance, quality and privacy, metadata management, and Master Data Management (MDM) services with the Salesforce platform will establish a unified architecture for agentic AI — enabling AI agents to operate safely, responsibly, and at scale across the modern enterprise”. The bigger picture For agentic AI systems – or agents in general – to operate efficiently, it needs two things: data and data. Data from a vendor’s own systems as well as data from external systems that can get harmonized and accessed/used by the software agents. SAP during its annual Sapphire event just made exactly this point by showcasing how its Joule family of agents can use data from SAP and non-SAP applications. As there is no vendor to rule them all (thanks to J.R.R. Tolkien for this inspiration) there is an importance on again two things: (zero copy) data integration and data management including its governance. These seemingly not-so-sexy capabilities are sorely lacked by many application vendors but, again, thanks to AI, increasingly necessary. Again, AI, especially autonomous AI systems, cannot be...