When AI spend meets the question of what it returns

What we're tracking

• •What spending five times as much has to show for it A recorded conversation among investors and operators kept circling one figure: "Companies quintupled their token spend in the first half of the year." [1] A token is the unit an AI model is billed in — roughly a fragment of a word going in and coming out. When your spend on tokens goes up five times, that is only good news if the work those tokens did is worth more than five times what it was before. Otherwise it is a meter running faster with nothing extra to show.
• •One person doing the work of ten The clearest example of that discipline came from Vercel, whose chief operating officer described taking a sales-development team from ten people to one, with the whole arrangement costing about five thousand dollars a year. The person making the call is not new to go-to-market: "Vercel's COO Jeanne DeWitt Grosser ran go-to-market at Google and Stripe for roughly a decade each before joining Vercel."
• •Microsoft builds a company to put AI to work Building a model and deploying it are two different jobs, and the day made the split visible. "Microsoft follows Amazon, OpenAI, and Anthropic with its new AI deployment group," [3] standing up its own company, with a two-and-a-half-billion-dollar commitment behind it, focused on getting AI into actual use rather than on the models themselves.
• •A new challenger to the office suite The incumbents are not unchallenged. An Indian entrepreneur is backing a new venture with thirty million dollars of his own money aimed squarely at the software most offices run on: "This time he's taking on Microsoft Office and Google Apps with AI." [4] It is described as "Bhavin Turakhia's fifth venture and his latest involving enterprise software." [4]
• •Cleaning up twenty thousand alerts Security work rarely makes headlines, but this piece is a useful lesson in operating at scale. "GitHub had 20,000+ secret scanning alerts across 15,000 repositories," [5] and the account describes separating signal from noise, building a remediation process, and clearing the backlog over nine months.
• •Two automation tools that look alike Finally, a reminder that similar-looking tools are often built for different jobs. On Power Automate and UiPath: "Power Automate and UiPath overlap just enough to look like rivals, but they're built for very different kinds of work." [6]