The Agentic AI Mirage: Why Your ‘Personalized’ Assistant is Working for the Vendor, Not You
The Ghost of Cluetrain In 1999, the Cluetrain Manifesto famously declared that “markets are conversations.” It was an inspiring, romantic notion that promised to democratize commerce, wresting power from faceless corporate monoliths and handing it back to a sovereign consumer. Fast forward to today, and that conversation has been thoroughly co-opted. What was supposed to be a bilateral dialogue has devolved into an automated, highly-optimized monologue. The emergence of agentic AI, which features autonomous software agents supposedly operating on our behalf, promises a return to that original democratic vision. But let us be honest: is this actually a revolutionary shift, or is it just another iteration of vendor-controlled slop designed to monetize our decisions before we even make them? The dream of conversational commerce was simple: technology enables humans to speak to other humans at scale. Instead, the vendor community realized that humans are expensive, inconsistent, and prone to demanding fair treatment. The corporate response was to replace them with IVR systems, chatbots, and automated messaging. These tools were never designed to foster actual conversations; they were designed to create efficient deflection barriers. Now, we are told that generative AI and agentic systems will change all this by acting as our personal proxies. But will it come true? 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 Illusion of Agentic Agency During our recent CRMKonvo with Dan Miller, founder of Opus Research, we wrestled with this paradox. We have been apocaloptimists when it comes...
Usage-Based Pricing for Copilot Is Good for Microsoft’s Investors. Read That Sentence Again.
TheStreet ran a piece this week arguing that, of Microsoft’s two Copilot announcements, the shift to usage-based pricing matters more to investors than the DeepSeek flirtation. That read is correct. It is also the tell. Here is what Microsoft actually did. Copilot Cowork, the agent that reaches across Microsoft 365 to run multi-step work on your data, is coming off the flat per-seat add-on and moving onto consumption billing the company calls “Copilot Credits.” Charles Lamanna, who runs Copilot, told Axios the product could not be offered on an unlimited-use basis. The users he pointed to are the ones doing hundreds of tasks a week. He called them “way productive.” And then he said the part vendors normally keep off the slide: their costs go very high. So the most productive users are the expensive ones. Hold that thought, because the whole argument lives there. What “good for investors” is really saying A pricing model earns the label “good for investors” when three things are true. Revenue starts to track cost-to-serve. Revenue scales with consumption instead of sitting flat per seat. And the vendor stops eating the margin on its heaviest users. All three are true here. None of them is a statement about whether a customer got value. That is the gap I want to sit in for a minute. Usage-based pricing meters an input. Tokens, compute, credits, whatever the unit. The customer does not buy tokens because they want tokens. They want a finished report, a resolved ticket, a reconciled spreadsheet. The token count is the cost of producing the outcome, not the outcome. And the relationship...
Pega’s fix for runaway AI costs: stop the agents from thinking at runtime
The news At its PegaWorld conference in Las Vegas on June 8, 2026, Pegasystems announced Pega Infinity 26, which it says will be available in Q3 2026. The principal change is commercial: Pega is moving away from per-token pricing for its AI agents toward a flat charge per completed “case,” which it defines as a task carried out from start to finish, such as a customer changing an order, a loan approval, or a claim. Pega frames the move as removing what it calls the “AI token tax“. The pricing change rests on an architecture Pega calls Predictable AI. Reasoning-heavy AI work is concentrated at design time, when workflows are authored in Pega Blueprint and the new Infinity Studio. At runtime, a lighter-weight model identifies the user’s intent, selects a pre-approved workflow, and executes it step by step; where an individual step requires a language model, for example to parse a document or summarize a prior interaction, that step is given bounded instructions rather than open-ended latitude. Pega gives two reasons: more consistent outcomes, because agents follow approved workflows rather than re-reasoning each request, and more predictable cost, because the heavier processing happens only once during design rather than on every transaction. The architecture is not new to this release. Pega introduced Predictable AI Agents in May 2025 and integrated them into Pega Infinity ’25, which reached general availability in December 2025. Infinity 26 primarily adds the outcomes-based pricing model, alongside a companion announcement that exposes Pega processes as Model Context Protocol (MCP) servers, allowing third-party agents from Anthropic, OpenAI, Google, and AWS to call them under Pega’s governance...