Putting AI where the work actually happens

What we're tracking

• •The bigger story is not AI replacing software The loudest narrative about business software right now is that AI is dismantling it — replacing seats, collapsing pricing, eating the workflow. It is worth reading the argument that this framing, while not wrong, is not the main event. One industry commentary published this week opens by naming exactly that reflex: "Everyone wants the story to be about AI." [1] The point it goes on to make is that many of the problems attributed to AI were already present in how software companies priced, retained, and served customers.
• •Turning what your best people do into something repeatable Much of the value a small business loses is tacit. Your most effective salesperson knows which objection to answer first and when to stop talking, and that knowledge usually leaves when they do. A startup called Encore AI raised $30M this week to attack exactly that gap. It "analyzes calls, messages, and CRM data to identify effective sales techniques and turn them into playbooks for AI agents." [2]
• •Moving past the open browser tab There is a wide gap between using AI and building it into how work gets done. The common state in most companies is a chat window someone keeps open and pastes into when they remember. Guidance published this week names that state plainly: "If your company's idea of 'using AI' is keeping ChatGPT open in a browser tab—congrats, you're doing the bare minimum." [4]
• •When a platform vendor calls AI an enterprise opportunity On its second-quarter earnings call, Meta signalled how broadly it intends to sell into business. Its chief executive said the company sees a "large enterprise opportunity" spanning AI agents, APIs, compute, and internal software. [3] The breadth of that list is the thing to notice. It is not a single product; it is agents, the interfaces to reach them, the compute beneath them, and the software a company runs internally.
• •Keeping automation from becoming noise Not every automation story this week was about AI, and one of the most useful was about the opposite problem: automation that works so eagerly it drowns the people it serves. GitHub published guidance on taming Dependabot, the tool that keeps software dependencies current. It states the trade-off directly: "Dependabot keeps your dependencies current, but its defaults can flood your repository with pull requests." [5]
• •What faster actually changes Most automation is sold on time saved, and that is the least interesting part of it. A Zapier account of a lawyer who made his practice several times faster reframes the question: "This one is about what happens after you save it." [6] The saved hour is only the input. What you do with it — take on clients you previously could not afford to serve, lower a price, or simply go home — is the actual decision, and it is a business decision, not a technical one.