The AI-first GTM strategist: agents, workflows, and knowing when to stop
Most GTM teams deploy AI where it's most visible. The question worth asking first: is that actually where it's most ready?
InfoWorld AI·
The first mobile application user interfaces were often scaled-down versions of what was already available on the web. Then, user experience (UX) designers recognized that the different smartphone form factor created new business opportunities and greater utility compared to what people were doing on their desktops. UX designers created mobile-first experiences tailored to the job to be done and other design thinking principles. The underlying agile development practices, along with the emergence of app stores, paved the way for explosive growth in smartphones and mobile applications. Today’s AI experiences seem to be following a similar path, with basic, sometimes bolted-on user experiences. First-gen chatbots appeared as pop-ups with text entry-and-response user interfaces (UIs) overlaid on the application’s screens. The primary UI for large language models (LLMs) is often a text box that accepts a prompt followed by a response that includes text and other media. Early AI agents were
Read full articleMost GTM teams deploy AI where it's most visible. The question worth asking first: is that actually where it's most ready?
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Most of us work with Word, Excel, PowerPoint, and other Microsoft 365 apps primarily on a computer, via the desktop or web apps. While you’re on the go, the mobile versions of these apps are handy for reviewing documents, spreadsheets, presentations, or other Office files, and you can use them to do minor editing. But the mobile apps also have specific functions designed for your smartphone’s smaller screen and touch interface that can help you do more in-depth work. In this guide, we’ll explain what these mobile-first features are and how to use them. Note: This guide refers to the individual Word, Excel, Outlook, OneNote, and PowerPoint mobile apps for Android and iOS. There’s also a general Microsoft 365 app (which Microsoft confusingly renamed “Microsoft 365 Copilot”) for both platforms that includes versions of Excel, PowerPoint, and Word built into it. But some of the features covered in this guide are not available in these apps within the M365 Copilot app, so we prefer to use t
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An image generated by ChatGPT Images 2.0. | Image: OpenAI OpenAI is rolling out the latest version of its AI-powered image generator with new "thinking capabilities," allowing it to search the web to help it create multiple images from a single prompt. In a blog post, OpenAI says ChatGPT Images 2.0 can now create more "sophisticated" images, with improvements to its ability to follow instructions, preserve details of your choosing, and generate text. It's powered by OpenAI's new GPT Image 2 model, with new thinking capabilities available to ChatGPT Plus, Pro, Business, and Enterprise subscribers. When a thinking model is selected, the chatbot's image generator can pull information from the web, cr … Read the full story at The Verge.
As companies move from experimenting with AI agents to deploying them in production, one pattern becomes clear: capability without control is a liability. Agents operate in long-running, stateful environments. They browse the web, read repositories, execute shell commands, call APIs and interact with internal systems. That power is transformative — and it meaningfully expands the attack surface. In a recent interview, Jonathan Wall, CEO of Runloop, summarized the shift: “By default, agents should have access to very little. They need to do real work, but capabilities have to be layered on in a controlled way.” That framing reflects a broader industry reality: agent infrastructure must be designed around least privilege, explicit isolation and observable execution. What follows is a practical control architecture for production agents. The layered control model A resilient agent deployment combines six explicit layers: Strong runtime isolation with a microVM Restrictive network policy w