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...
Don’t Step Into The Platform Trap: What Microsoft Build 2026 Could Mean for Your Next AI Stack Decision
Microsoft Build 2026 produced two announcements that, read together, describe something more interesting than the usual conference launch cadence: a plausible scenario in which enterprise AI stack decisions made in the next 12 months could become significantly harder to reverse. The operative word is “could”. Several pieces of the announced architecture are not fully shipping yet. But the direction is clear. The News Microsoft delivered two related announcements at Build 2026. The first came from Jay Parikh, EVP of CoreAI: the model is not the differentiator; the system governing it is. Microsoft’s answer is a six-step loop. Agents are built in GitHub, contextualized with Microsoft IQ, which grounds them in enterprise data from Microsoft 365, core business systems, knowledge bases, and the web, run in Foundry, governed via Agent 365, and continuously improved through a hill-climbing optimization cycle. Agent 365, combined with Entra, Purview, and Defender, catalogues every agent in the estate, regardless of where it was built, and lets IT enforce policy across all of them. The second came from Mustafa Suleyman, CEO of Microsoft AI: seven new MAI models built from scratch, with no distillation from third-party models. MAI-Thinking-1, the flagship reasoning model at 35 billion active parameters, benchmarks at parity with Anthropic’s Claude Sonnet 4.6 on software engineering tasks at significantly lower per-token cost. MAI-Code-1-Flash is integrated natively into GitHub Copilot. MAI-Transcribe-1.5 claims leading accuracy across 43 languages at five times the speed of competing models. Image and voice models complete the family. Alongside the models, Microsoft introduced Frontier Tuning: enterprises can train MAI models on their own workflow data using reinforcement learning environments. The model...
Your Sales Funnel Is an Architectural Disaster, And How to Change This
Every single week, I sit through pitches from enterprise software vendors boasting about the next iteration of their ” AI-powered sales pipeline optimization platforms”. They promise to auto-magically turn cold leads into closed contracts while minimizing human intervention. That sounds great on a slide deck designed to pump the stock price before an earnings call. In reality, however, these systems are automating an architectural flaw that has plagued B2B organizations since, well, forever: the linear sales funnel. Let me be clear here. The classic sales funnel is not an asset; it is a structural failure. It assumes a predictable, straight line where marketing captures raw interest, tosses a lead over a wall to a sales development representative, who then passes it to an account executive to close the deal. Once the contract is signed, the customer disappears from the pipeline, and is handed off to an underfunded customer success department that operates like a glorified complaints department. This system assumes that buying journeys have a finite endpoint. The B2B buying journey does not end when a contract is signed. By treating marketing, sales, and service as isolated phases with independent processes and technology stacks, enterprise organizations create massive amounts of friction. Norbert Schuster, a veteran B2B strategist who joined us in the latest episode of the CRMKonvos podcast, summarized this beautifully when he described the classic setup as the “Currywurst-Pommes effect“. Individually, a sausage or a plate of chips is acceptable; combined, they become something functional. Yet, in most organizations, marketing automation platforms and CRM instances do not communicate well. They sit side by side as poorly connected line...