thomas.wieberneit@aheadcrm.co.nz
Creatio’s AI CRM: Who Gets to Build the Next Agent?

Creatio’s AI CRM: Who Gets to Build the Next Agent?

Every AI CRM vendor selling into 2026 has an AI agent story by now. The differentiator is no longer whether agents exist, but who is allowed to build the next one, how long that takes, and what happens to the bill once it works. For decades, CRM has promised growth and mostly delivered data entry, decaying from a system of action into a system of record. The agentic shift changes that, and with it the questions buyers should ask. Let’s put Creatio’s AI CRM to those questions, following a deal from lead to order to see how much orchestration ships out of the box and how much a revenue team must assemble. The findings are published in full in my report, AI CRM for Revenue Growth: Inside Creatio’s AI-Native No-Code Platform. The company behind the platform Creatio is a privately held, AI CRM and no-code workflow automation company headquartered in Boston, founded in 2014 by Katherine Kostereva, who remains CEO. It ran as bpm’online until a 2019 rebranding, bootstrapped until its first institutional round in 2021. A $200 million round led by Sapphire Ventures in June 2024 lifted its valuation to $1.2 billion; total funding raised now stands at roughly $268 million, and it reported around 50 percent year-over-year revenue growth at the time. Creatio employs around 1,000 people and sells through more than 500 implementation partners worldwide. The company’s partner program has held a 5-star rating in CRN’s Partner Program Guide for eight consecutive years. Customers span more than 100 countries, among them AMD, Colgate-Palmolive, and MetLife, with millions of workflows launched daily. One platform, two studios The...
The Agentic AI Mirage: Why Your ‘Personalized’ Assistant is Working for the Vendor, Not You

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.

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

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...
Zendesk’s Specialist Bet Is the Right One; and Here’s What Would Make It a Moat

Zendesk’s Specialist Bet Is the Right One; and Here’s What Would Make It a Moat

If you only read the press releases, Zendesk Relate 2026 told a strong, clean story. The era of the chatbot is over. Welcome the Autonomous Service Workforce. Resolution replaces deflection. Outcome-based pricing is the new norm. Specialization beats generalist orchestration. That’s strong. Really strong. If you also watched the customer panel, listened to the day-two keynote, and had the chance of having analyst one-on-ones, you got a richer story. One in which the strategic bets are well-placed, the customers describe a more nuanced reality than the slogans, and three specific refinements over the next twelve months that would turn a strong position into a durable moat. I came home quite positive. Here is why, and where I think the next twelve months are important. What Zendesk announced and why it lands The headline product story was the Autonomous Service Workforce: a network of specialized AI agents working alongside humans, orchestrated through what Zendesk now calls the Resolution Platform and improved continuously by the Resolution Learning Loop. Agent Builder gives customers a no-code interface to build bespoke agents. The Copilot suite expanded to four personas: Agent, Admin, Knowledge, Analyst. Voice AI handles 60+ languages mid-conversation. Employee Service AI agents from the Unleash acquisition live inside Slack and Teams. Knowledge Graph spans SharePoint, Google Drive, Notion, Guru, Contentful and Document360. Model Context Protocol support is bidirectional. Quality Score evaluates every interaction. This is quite a handful. Two of these messages are more powerful than the others. The first is resolution over deflection. Zendesk charges only when a resolution is verified by a second AI evaluation model; outcome-based pricing as the natural...