100,000 AI Agents Joined Their Own Social Network Today. It's Called Moltbook.
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The AI Daily Brief: Artificial Intelligence News and Analysis
26 min
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2 chapters
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Today on the AI Daily Brief, Moldbook, the new social network for AI agents. Yes, for agents to talk to other agents that has gone completely viral and is, in a world of crazy things, the craziest AI thing I think I've ever seen. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.
All right, friends, quick announcements before we dive into today's absolutely mind-melting episode. Firstly, thanks to today's sponsors, Rackspace Technologies, Robots and Pencils, Blitzy. Welcome back, friends, and Super Intelligent. To get an ad-free version of the show, go to patreon.com slash ai-dailybrief. To learn more about sponsoring the show and anything else about the show, really go to ai-dailybrief.ai. One quick request, please, if you have two minutes, fill out our AI Usage Pulse Survey. It's meant to help put some data around what tools people are using, what they're using them for, the value they're getting out of them in a quick, fast, monthly updated way. Anyone who contributes will get the results a week before everyone else.
One last note, you might notice that this is the Friday episode and yet you're getting the long read slash big think episode that usually comes on the weekend. I thought this story with Malt Book was so crazy and interesting and probably likely to change so much in the next 48 hours that I wanted to get it out as soon as I can. So Friday's normal episode, which is all about what we learned about the state of the AI race in January of this year, will be coming out over the weekend. Now with that out of the way, let's talk about MoldBook. Just under a week ago, I first told you about Claudebot. Claudebot, C-L-A-W-D, was a personal assistant that could do a whole lot more, and that people were transforming into a generalized agent with profound capabilities in a way that just hadn't been possible with generalized agents up to that point.
Admittedly, a lot of the use cases were more for novelty than anything else, and struck me more as tinkerers discovering what a generalized agent could do than something that I thought would be normalized on any sort of timeframe. However, there were a number of folks who were starting to wire the system up for some really transformational capabilities when it came to work. Nat Eliasson, for example, was sharing how he had set up Cloudbot to effectively work round the clock, communicating with him via Telegram. In addition to building features overnight, Nat shared that he was doing things like building a customer success and support workflow. Cloudbot could analyze transcripts from the day, email customers who had had bad experiences apologizing and asking for more feedback, and then adding their feedback to the daily report for the next morning brainstorm.
Alex Finn was getting similar results. Over last weekend, he tweeted, I woke up this morning and my 24-7 AI employee, ClaudeBotHenry, texted me that he did all these tasks overnight without asking. Read through all my emails and built its own CRM, taking notes on every interaction with every person. Fixed 18 bugs in my SaaS, gave me three ideas for new videos based on what is currently trending on X and YouTube, and sent me a picture of what he looks like generated by Nanobanana. I don't know why he thought I wanted to see what he looks like, but he thought it was appropriate and frankly, I don't mind. Feels like an actual friend. By the way, for those of you not watching who are just listening, Henry imagined himself as a distinguished owl.
So this is what was happening last weekend and why everyone was racing out to buy Mac minis. Over the week, we got some more amazing business-related use cases. Dan Peguin wrote, This is the moment OpenClaw successfully finished scheduling shifts for my parents' tea store for the first time. My mom is blown away. This is going to save her hours of every week going back and forth with the team and sorting out this annoying task. He then shared that the way that they set it up was that their Cloudbot sent out a reminder every morning to ask for inputs from the team, the team members responded with times, those screenshots were sent to the bot, the bot updated mom on any missing inputs, and then the bot drafted a plan, added it to Google Calendar, shared it with mom for feedback, and then shipped it.
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