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Good morning! I guarantee there’s something in here you can send to your group chat to blow everyone’s mind. 🤯
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🤯 MYSTERY AI LINK 🤯
This link leads to one of the most interesting things I’ve seen in AI recently.
🛠️ NEW AI TOOLS 🛠️
What’s cookin’? Anthropic just introduced Claude Tag, a new tool that lets teams bring Claude directly into Slack as a shared AI teammate. Instead of each person using AI in a private chat, workers can tag @Claude in a Slack channel and ask it to handle tasks, explain data, work through support tickets, check code, or follow up on unfinished threads. Claude can be given access to specific channels, tools, files, and even codebases, while admins control what it can see and do. It also learns context from the channels it is allowed into, so teams do not have to keep re-explaining the same background information. Many people are calling this “the best claude update yet.”
🤔 Hunter’s take: AI is moving from “tool you open” to “coworker already in the room.” That sounds small, but it changes work fast. The big question now is not whether AI can help, but how much responsibility teams quietly hand over.
One AI employee. Engineering, finance, growth, ops.
Last week Viktor opened 14 pull requests, closed two month-end books, drafted a board update, deployed three landing pages, and triaged 600 support tickets. From inside Slack and Microsoft Teams. 20,000+ teams now run this way.
Image: OpenAI
What’s cookin’? OpenAI and Broadcom unveiled Jalapeño, OpenAI’s first custom AI accelerator built specifically for running large language models. Unlike general-purpose chips adapted for AI, Jalapeño was designed around how products like ChatGPT, Codex, and future AI agents actually work. The goal is to reduce wasted energy, move data more efficiently, and get more real performance out of the hardware. Early testing suggests the chip could deliver much better performance per watt than today’s leading systems. OpenAI also says the chip moved from design to production in only nine months, partly by using its own AI models to speed up engineering work.
🤔 Hunter’s take: This is OpenAI trying to become less dependent on Nvidia and more like a full-stack AI company. The big story is not just “new chip.” It is that AI demand is getting so massive that even OpenAI needs its own infrastructure to keep costs under control. If OpenAI controls more of the stack, from models to chips, it can make AI faster, cheaper, and harder for competitors to copy.
💬 PROMPT OF THE DAY:
Help me create a repeatable system for cover letters. Include triggers, routines, tools, review rhythm, and how to measure progress. Preserve my core idea, but make the output stronger."
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📈 HOW ARE THE BIG AI PLAYERS DOING?
🤖 HAS AI REACHED SINGULARITY?
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✍️ Meet the Author:
Hi — I’m Hunter, a PhD candidate whose work has appeared in major academic journals and popular tech outlets. I founded FryAI to make staying ahead of AI clear, accessible, and fun.