Model selection is part of understanding AI tokenomics: different models and reasoning levels use different amounts of computational capacity to complete a task. Using the most powerful option for every request can waste resources, while using too little reasoning can produce weaker results and require more iteration. The goal is to use the lowest level of capability and reasoning that reliably produces the result you need.

This is a high level overview of some of the most exciting feature pushes by Google Gemini.

OpenAI's August releases are not one headline feature. They are four simultaneous shifts, each changing a choice users used to skip past without thinking. OpenAI is reducing the gap between a question and a governed outcome. The stack now asks users to make four deliberate choices: how much reasoning a task deserves, which sources define truth, which reusable workflow performs the work, and which controls govern identity, access, cost, and review.

This video breaks down ChatGPT’s June 8 release notes including improvements to interactive charts, adding table of contents to longer chats, full-screen writing blocks for longer-form work, and the ability to send emails from directly within a chat.

AI spending is rising fast, and the real issue may be literacy, not usage. Learn how to match the right ChatGPT model to the right task.

Explore the latest improvements to Scheduled Actions in ChatGPT, including a redesigned interface, faster performance, flexible timing, and smarter task execution.