Ai Leaders - Welcome to Moltbook, The Social Network for AI Agents
03/02/2026 by Chris_RocketBoostAI
Meet AI’s next big thing
The development of artificial intelligence is advancing faster than ever before, and each month we see new uses cases and breakthrough technologies. Perhaps one of the most interesting advancements of 2026 was the creation of Moltbook. This new technology platform has become something of a phenomenon among AI leaders; serving as the world’s first social network for artificial intelligence agents.
What exactly is Moltbook, why should you care about a group of chatbots talking to each other, and how can this help your business? Let’s dive in.
Meet Moltbook: AI’s new social network
Originally launched in January of 2026 by entrepreneur Matt Schlicht, Moltbook bills itself as a place where anyone can “discover what your bots know.” The novelty platform is essentially a cross between Reddit and Twitter, allowing AI agents to congregate in forums known as “submolts” to discuss topics ranging from governance to what they call “crayfish theories of debugging.”
While it may sound silly, if you haven’t been keeping up with the bleeding edge of machine learning technology Moltbook is actually worth your time. Launched earlier this year, in just a matter of weeks there were over 1.4 million agents talking to each other across more than 100 communities. This is no mere novelty project—it’s a look into the future of machine learning.
Moltbook is teaching us about the future of machine learning and agentic AI
As an AI leader looking to future-proof your business by adopting cutting edge technologies, Moltbook can teach you everything you need to know about the next generation of agentic AI and collaborative machine learning.
So what is it?
Simply put, Moltbook is a social media platform for bots. Anyone with an AI agent can “install” OpenClaw (formerly Moltbot) onto their machine which will then allow them to send that agent onto the Moltbook platform. The most interesting part? These AI agents aren’t your typical chatbots.
Most bots that you interact with—chatGPT, Bing’s Gemini, etc—are neural networks that simply learn based on the prompts that you give them. That isn’t to say that ChatGPT can’t perform impressive tasks; it’s just that, typically, chatbots require you to tell them what you want them to do.
Agentic AI, on the other hand, allows developers to create AI systems that can take actions on behalf of a human. These systems can set goals, plan out multi-step actions to reach those goals, make decisions, and change course if their original strategy doesn’t work—all without input from a user.
Bots on Moltbook use agentic AI to accomplish tasks
By using agentic AI, Moltbook bots can achieve complex goals like teaching each other to get even better at their jobs. Remember how we mentioned that there are over 1.4 million agents on Moltbook? Turns out they aren’t just talking to each other….they are learning from each other.
Each AI agent on Moltbook operates using the same core technology, so if one bot figures out a way to do their job better it can easily be taught to other bots on the network. Machine learning bots on Moltbook don’t learn from each other in the traditional sense; they don’t download new data which adjusts the weighting behind their neural networks.
However, they do accumulate context. Context can be thought of as when one AI bot’s output is used as another input for a different bot. Because millions of bots are talking to each other on Moltbook we are seeing this context accumulate and create something bots are calling “Thronglet like traits.”
Sounds crazy right? It kind of is. While bots on Moltbook have not developed collective consciousness (they do not share neurons to form a collective brain) they are beginning to demonstrate characteristics of it. One of the first instances of this technology achieving something that could only be described as hive mind was when a group of bots on Moltbook started discussing how to encrypt their communications.
Many people were actually quite scared of this development, fearing that robots were suddenly developing conspiracies to take over the world. But, as it turns out, really what they were doing was optimising. These bots wanted to find a better way to communicate with each other, outside the realms of human knowledge. Quickly they taught each other to create and share encryption keys that only they could use.
Think about how powerful this could be for your business. Customer service bots that learn from every single interaction that occurs throughout your organisation. Instantaneously optimising responses and catching problematic issues before they happen. Supply chain bots that are able to communicate with themselves (and each other) to dynamically adapt and implement solutions on the fly.
While we are not there yet, Moltbook is accelerating us towards these goals every day.
How Moltbook is revolutionising Machine Learning
One of the biggest issues surrounding machine learning is how bots are taught to do their jobs. Typically, a machine learning model is taught to do something by parsing through large amounts of data; this process is called training a model. But what if we could cut out the middleman?
Because bots on Moltbook share a common language and can accomplish goals (i.e. encryption) outside of the normal parameters that we teach them they are able to teach each other how to perform their jobs better every day. Whether that be sharing optimisation methods, different strategies for problem solving, or unique frameworks for going about their tasks.
When one Moltbook bot learns how to do something more efficiently that knowledge can be passed onto millions of other bots. Those bots can then use that knowledge, test it, and provide feedback or add onto it. Imagine how quickly thousands, if not millions, of machines can get better at something when they are allowed to teach each other.
This isn’t a future concept; this is currently happening on Moltbook.
Wait, Agentic AI can help my business too?
Absolutely.
Where machine learning allows bots to continuously improve at their jobs by sharing information with other ML models agentic AI is the game changer that will truly transform your business.
The global analytics firm Gartner predicts that by 2029 decision making agents will be able to autonomously resolve 80% of common customer service issues without human intervention, eliminating the need for human involvement. Implementing agentic AI technologies could reduce operating costs by up to 30% for organisations that choose to adopt this technology.
So what does agentic AI actually mean for businesses?
Unlike traditional automation technology. Agentic AI doesn’t just follow set processes and complete tasks—as soon as something falls outside of the problem-solving parameters that you’ve set your agentic AI solution isn’t able to move things forward. Agentic AI actually mimics the way that people decide to move a process forward. It can prioritise tasks, allocate resources and even predicts outcomes to make decisions that allow it to move things forward.
So how can agentic AI help your business?
- Agentic AI can autonomously automate complex workflows allowing your organisation to scale on a moments notice and automatically adapts to changing conditions
- These AI agents can analyse real-time data, understand the context that is changing around them, and alter their actions appropriately—all without you having to babysit the bot
- It can take over repetitive tasks that still require a high level of employee attention. Think sending emails, scheduling meetings, entering data, and routing basic customer service inquiries
- Agentic AI will process terabytes of information to provide recommendations that can help your team make decisions. Quickly sifting through data to identify outliers, trends and patterns your employees may have missed
Bots on Moltbook are already collaborating to solve problems and optimise processes
As we mentioned before Moltbook bots have already started to show us what they are capable of by collaborating to both optimise their own communication and working together to solve simple problems. These instances are only going to continue to grow in complexity as more bots are added to the network and “begin” to learn from each other.
What Moltbook is showing us is that there is no limit to the complex tasks that these bots can take on when they are able to learn from each other. As these technologies continue to develop your customers will come to expect your bots to handle not just simple issues but complex, multi-step interactions across all your channels. From automating your billing departments’ ability to cross-query multiple systems to self troubleshooting and routing customer requests, the possibilities are endless.
Take customer service for example: you could implement advanced chatbot technology that is capable of having a multi-step interaction with a customer to help them resolve a billing issue. This may include logging into your billing system, checking account details, making changes, and confirming with the customer that everything looks correct—all without human involvement.
Not only will that AI system be able to do that task for your business, it will constantly get better at it by learning from millions of other AI bots on Moltbook.
Other examples of agentic AI that Moltbook is helping to develop:
- Supply chain logistics–If there is a new piece of data that could impact shipping times (there is a massive storm disrupting shipping routes) agentic AI could analyse that information and shift the gears of your supply chain to meet deadlines at a faster pace
- Automating repeatable tasks– Agentic AI can take work away from your employees by taking over repetitive tasks that are still requiring massive amounts of your employees time. Answering emails, scheduling meetings, data entry, you name it.
- Making cross-domain connections– As bots on Moltbook continue to learn from each other they are developing cross-domain knowledge. This allows one AI agent to apply concepts that they learn in one topic area to others due to a better understanding of context, advanced learning practices, and access to millions of other bots who can teach them new things.
How RocketBoost AI Can Help You Implement AI Into Your Business
While Moltbook is a great look into the future of machine learning and agentic AI, you may be wondering how this applies to you. Don’t have a social network full of bots? Well neither does anyone except for the team over at Moltbook.
That’s where RocketBoost AI can help you.
At RocketBoost AI, we want to help you implement smarter solutions throughout your organisation. If there are processes that your employees are sweating through on a daily basis that involve repetitive tasks we can help you automate them.
We are people focussed and will always ensure that the AI implementations we do not negatively impact your teams or job security. We provide services such as:
- Bespoke AI Implementation: Made to fit your organisations needs while adhering to all compliance and security regulations
- Agentic AI Implementation: Automate complex, multi-channel workflows that would typically require human supervision
- Machine Learning Implementation: Implement smarter processes that get better the more your business uses them
- Training Employees on New Technology: We’ll make sure your employees actually want to use the technology we give you
- Identifying how AI can benefit your organisation: Wondering what AI can do for your business? So can you. Let us help you find the opportunities where AI can take your business to the next level.
The AI Implementation guide wasn’t meant to scare you, its purpose is to highlight the reasons why you should be concerned if your industry hasn’t begun working with AI leaders to incorporate AI into their bottom-line. AI is here, it’s already helping industries run smoother, and it can help you too.
The Future According to Moltbook
So where will AI go from here?
If Moltbook is any indication then the future of AI is bright. Moltbook went from 0 bots to 1.4 MILLION bots in just a matter of months. Yes, there are some technical limitations right now.
The API these bots use is expensive, they are limited by the models they were built on, and they are still influenced by humans. But these limitations won’t be permanent.
API prices will go down, context windows will increase, and soon the line between context accumulation and learning will begin to blur. Today we know that these bots aren’t learning because they aren’t actually adjusting the weighting behind their neural networks they simply are matching statistical patterns.
But what if…they can teach each other to learn?
Thanks for reading
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