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Every small business has one person who is the office search engine. Where is the refund form. What goes in the Friday report. Which supplier do we use for rush jobs. The answers are written down somewhere, but asking that person is faster than finding them, so the questions keep coming and that person never gets a full hour of their own work. An SOP chatbot fixes exactly that. Staff type the question, and the bot answers with the steps from the procedures you already wrote, and shows which document it took them from. Nothing else. This article explains how that works using one picture, shows two bots we actually run, and is honest about what the bot will never do. The box Picture the AI as a very capable temp worker who shows up every morning with no memory of your business at all. Not the address, not the prices, not how you handle a late delivery. Smart, fast, and completely blank. Before you ask them anything, you hand them a box. In the box are your documents. The rule, taped to the lid, says: answer only from what is in the box, and if the answer is not in the box, say so. That box is what people in the AI world call the context. Everything the bot knows about you at the moment it answers is what you put in the box for that one question. It does not learn your business over time. It reads the box, answers, and forgets. Next question, new box. Two things follow from this picture, and they explain almost everything about SOP chatbots. The box has a size. Anthropic, the company behind the Claude models, says in its engineering write-up on contextual retrieval that a knowledge base under about 200,000 tokens, roughly 500 pages, can simply be included with every question, with no extra machinery. Most small businesses have far less than 500 pages of procedures. So for most of you, the whole manual fits in the box every time. If the manual is bigger than the box, someone has to pick. Then a librarian step runs first: it reads the question, pulls the few pages that m

While philosophers ponder AI consciousness, the models have ideas of their own.

More than 200 people in roles such as engineering, finance, and communications will now be represented by the Communication Workers of America.

ChatGPT, Claude, and Grok all suffered outages at nearly the exact same time for reasons that remain murky.

This week on Uncanny Valley, we dig into the latest prediction market buzz, Flock’s AI-powered police search tool, and how tech bros don’t know how to talk about “rouge” AI agents

OpenAI leaders think the company’s next generation model, which excels at computer use and coding, may mark a major milestone in AI development.

OpenAI recently estimated its Cursor partnership would make more than $1 billion in revenue a year, WIRED has learned. It still walked away after Elon Musk’s SpaceX acquired the AI coding startup.

The long-rumored deal will give the chip giant access to—and help it promote—a huge repository of open-source AI models and data sets.

Nvidia has agreed to buy Hugging Face for $12.93 billion, bringing one of the most popular hosting platforms for open-source AI models, datasets, and tools under the ownership of the world's biggest AI chipmaker. Hugging Face is an online platform founded in 2016 that gives AI developers a space to share their projects and data […]

Microsoft is changing how it reports its finances to investors by splitting its businesses into two segments and disclosing quarterly revenue for its Azure cloud business for the first time. The changes are meant to reflect the ongoing impact of AI on Microsoft and how the company now operates. The software giant has previously reported […]

The company is reducing pressure on workers to use artificial intelligence tools while encouraging them to experiment with Hatch, its most advanced AI project yet.

The US government wrote a letter in support of OpenAI’s argument that training AI on others' intellectual property is fair use.

A startup called Mostik has a wild new approach to combining the capabilities of AI models.

Christopher was sick of being ghosted by AI recruiters. So he unleashed ChatGPT on his robot interviewer.

Meet the AI police who can make or break careers—in publishing and beyond.

Every time I tried to explain technical debt to a business leader early in my career, I watched their eyes glaze over at roughly the same word. I would talk about coupling, legacy modules, and refactoring, and they would hear a developer asking for time to tidy up code that already worked. From where they sat, it sounded like a hobby. The system ran, customers paid, revenue arrived. Why would anyone spend money making invisible internals prettier when there were features to ship and deadlines to hit? The breakthrough, for me, was to stop explaining the engineering and start describing the finance, because technical debt is a loan whether anyone chose to take it or not. Every time we shipped a shortcut to hit a date, we borrowed speed today against effort tomorrow. That is often a completely rational trade. Getting to market fast can be worth far more than a clean design nobody ever sees. The problem is not the borrowing. The problem is that this loan accrues interest silently, and the business had been making payments for years without ever seeing the statement. That interest shows up in ways leaders actually feel, once you connect the dots for them. It is why a feature that used to take a week now takes a month. It is why every change risks breaking something unrelated, so nothing ships without a nervous weekend. It is why new hires take half a year to become productive in a codebase that only its veterans can navigate. None of that reads as "debt" on any report, but it is the compounding cost of shortcuts taken long ago, paid daily by everyone who touches the system. Framed that way, the conversation finally changes. I stop asking for permission to clean things up and start presenting a financial choice. We can keep paying this interest indefinitely and watch our delivery speed keep bleeding out, or we can pay down some principal now and get that velocity back. Sometimes the honest answer is to keep carrying the debt, and that is fine. What is not fine is carrying

The company will give select partners early access to its Astra AI model—so they have time to shore up their defenses.

The multitrillion-dollar home of the iPhone, Mac, and so many other tech gadgets has a new leaader, as Tim Cook has been replaced as CEO as of September 1st by former hardware boss John Ternus. How will we look back on Cook’s legacy, and what will Apple look like under the leadership of Ternus and […]

The email arrives. "Mercury will not be able to support your business at this time. We will not be able to provide additional details about this decision." You spend the next two weeks building an appeal: residence permit, business plan, tax registration, customer contracts, the whole file. You attach a polite cover letter explaining that you are not in Russia, not a sanctioned individual, fully compliant. Mercury either does not respond or sends the same boilerplate back. By week three you have decided you did something wrong, that your business is somehow tainted, that you will never get a US bank account. None of that is true. The reject was a system response, and once you can see the arithmetic driving it, the next move gets obvious and the spiral stops. The math behind an auto-decline OFAC violation penalties start at roughly $1 million per transaction. The annual revenue from a single diaspora-founder account at Mercury sits somewhere between $50 and $500. On top of that sits reputational risk: one Bloomberg story about "the fintech serving sanctioned Russians" damages the next funding round, strains banking partner relationships, and invites regulatory attention. Run those numbers and an auto-decline on an RU or BY passport signal becomes the rational move for the fintech, even when the overwhelming majority of flagged applications are perfectly legal. The downside of a single miss outweighs the upside of correctly clearing every legal applicant. What you are looking at is a company optimising against an asymmetry: maximum downside, minimal upside, per application. There is no judgement of you anywhere in that calculation. How the decline actually happens A KYC submission includes a passport scan, residence permit, and business documents. The decisioning system flags an RU or BY passport regardless of where you live, how the company is structured, or where the revenue comes from. Human review exists, but it triggers only when the signal-to-noise ratio is exce

The FTC and 22 state attorneys general are suing Amazon for allegedly using a "secret ad surcharge" to drive up prices for ads on its website and app. FTC chairman Andrew Ferguson claims in a blog post on the lawsuit that the higher advertising prices "were largely passed on to American consumers." According to the […]