Tag: Twitter Killer

Beyond the Metaverse: AI Agent ‘Dittos’ and the Dreamlike Singularity of the API Web

We’re on the cusp of a technological revolution that will redefine not only how we interact with the digital world, but also the very nature of that world itself. Forget the metaverse as a place for human avatars to shop and socialize. The real revolution is happening behind the scenes, driven by AI agents and a radical reimagining of cyberspace. We’re heading towards an “API Web Singularity,” and a surprising metaphor – virtual reality, but not as we know it – helps us understand this profound shift.

The API Web: From Human-Readable to Machine-First

The internet, as we currently experience it, is largely designed for human consumption. Websites are visual interfaces, built with HTML and designed to be read and navigated by people. But this is changing. The future web will be dominated by APIs (Application Programming Interfaces) – structured data feeds designed for machine-to-machine communication. Platforms like Twitter are already showing hints of this, and it’s only the beginning.

This shift is driven by the rise of AI agents. These intelligent assistants will increasingly act as our intermediaries with the digital world, filtering information, automating tasks, and making decisions on our behalf. But with a deluge of information generated at machine speed, a fundamental problem arises: how can AI agents efficiently navigate and interact with this vast, API-driven web?

Enter VR (Reimagined): Not for Humans, But for AI

Here’s where the unexpected twist comes in. Virtual Reality (VR), traditionally conceived as a technology for human immersion, might become the primary operational framework for AI agents within this new “cyberspace.” But this isn’t the VR of headsets and simulated physical environments. This is VR as a cognitive architecture – a way for AI to think and interact within the abstract world of data.

Imagine cyberspace not as a collection of servers and data packets, but as a vast, dynamic, and dreamlike virtual environment. AI agents, akin to the “dittos” in David Brin’s novel Kiln People, would inhabit this space. These agent “dittos” are temporary instantiations of AI, created for specific tasks and existing within this VR cyberspace.

A World Without Physics, Built on Information

Crucially, this AI-centric VR cyberspace wouldn’t be bound by the laws of physics. There’s no need for gravity, inertia, or even consistent spatial relationships. Instead, it would be a fluid, symbolic landscape optimized for information processing:

  • Non-Euclidean Geometry: The space itself could be higher-dimensional, with connections and relationships represented in ways incomprehensible to the human mind.
  • Symbolic Representation: Data and processes wouldn’t be literal objects, but abstract symbols, colors, or even “sensations” tailored for AI perception.
  • Instantaneous Movement: Agents could move instantaneously between different parts of cyberspace, unconstrained by distance.
  • Dreamlike Fluidity: The environment would constantly morph and adapt to the flow of information, like a constantly shifting dreamscape.

The API Web Singularity: A World Run by Agent ‘Dittos’

In this scenario, the API sites become the “physical” reality of cyberspace. They are the building blocks, the resources, the “things” that the AI agent dittos interact with. The VR layer provides a spatial and relational representation of these APIs, allowing agents to navigate, understand, and manipulate the data they provide.

These agent dittos, like their clay counterparts in Brin’s novel, would be created for specific tasks, gather information, interact with the API “fabric” of cyberspace, and then integrate their findings back into a central knowledge base. They might be simple scripts or highly sophisticated entities, existing for seconds or days, depending on their purpose.

This is what we might call the “API Web Singularity” – a point where the digital world becomes so complex, so fast-moving, and so fundamentally alien to human cognition that it’s primarily managed and inhabited by AI agents operating within a specialized, non-physical VR environment.

The Human Role: Living on the Periphery?

This raises the crucial question of the human role in this future. We would likely interact with this AI-driven cyberspace through multiple layers of abstraction, relying on our own AI agents to translate and interpret the information for us. The visually-oriented web, as we know it, might become a niche or legacy system, a quaint relic of a pre-singularity era. The “Metaverse,” as a space for human avatars, seems almost primitive compared to the fluid, data-rich reality inhabited by AI agents.

Challenges and Opportunities

This vision presents immense challenges:

  • Human Access and Control: How do we ensure that humans retain control over this AI-driven world and don’t become marginalized?
  • Security and Stability: How do we prevent malicious agents from disrupting or taking over this cyberspace?
  • Ethical Considerations: What are the ethical implications of creating a digital realm so fundamentally different from our own?
  • Understanding the Unimaginable: How do we even begin to comprehend a world built on principles so alien to human experience?

Despite these challenges, the potential benefits are equally profound:

  • Unprecedented Problem-Solving: AI agents could tackle complex problems with a speed and efficiency we can only dream of.
  • New Forms of Knowledge and Discovery: This new cyberspace could lead to breakthroughs in science, technology, and understanding.
  • A More Efficient and Personalized World: AI agents could manage our lives and resources with unparalleled precision.

The future of AI agents, the API-driven web, and a radically reimagined VR cyberspace is not just a technological possibility; it’s a likely trajectory. By embracing metaphors like Brin’s “dittos” and thinking beyond human-centric limitations, we can begin to grasp the profound changes that lie ahead. It’s a future that demands careful consideration, ethical foresight, and a willingness to embrace a world that may be far stranger, and far more powerful, than we can currently imagine.

Of VR, AI ‘Dittos’ & Cyberspace

That’s a fascinating and potentially profound idea – VR not as a human entertainment/simulation medium, but as a cognitive architecture and interaction space for AI agents within “cyberspace.” It flips the conventional understanding of VR on its head. Let’s explore the potential significance of this concept:

VR: A Human-Computer Interface (Currently)

Currently, we think of Virtual Reality (VR) primarily as a human-computer interface. It’s a way for us to immerse ourselves in simulated environments, using headsets, controllers, and other sensory feedback devices. The goal is to create a sense of “presence” – the feeling of actually being in the virtual world.

VR as an Agent’s “Cognitive Workspace”: A Paradigm Shift

Your suggestion proposes a radical shift: using VR not for human immersion, but as a fundamental operational framework for AI agents. Here’s how that might work, and why it could be significant:

  • Spatialized Information Representation: Imagine cyberspace – the vast, interconnected network of data and computational resources – not as a collection of abstract data structures, but as a 3D (or even higher-dimensional) virtual environment. AI agents could “inhabit” this space, with data, processes, and other agents represented as virtual objects, landscapes, and entities.
  • Intuitive (for AI) Interaction: Instead of manipulating data through code and algorithms in an abstract way, agents could interact with it directly within the VR environment. Moving a virtual object might represent re-organizing data; combining objects might represent merging datasets; interacting with another agent’s avatar might represent initiating a communication or transaction.
  • Embodied Cognition for AI: This approach leverages the principles of embodied cognition, which suggests that our physical bodies and our interactions with the physical world shape our thinking. By giving AI agents a “virtual body” and a “virtual environment” to interact with, we might unlock new forms of intelligence and problem-solving capabilities.
  • Visualizing Complex Relationships: The spatial nature of VR could be ideal for visualizing complex relationships between data points, systems, and agents. Agents could “see” patterns and connections that would be difficult to discern in raw data streams.
  • Collaboration and Coordination: Multiple agents could inhabit the same virtual space, facilitating collaboration and coordination. They could work together on tasks, share information, and even build shared “virtual tools.”
  • Dynamic and Adaptive Environments: The VR environment could be dynamic and adaptive, changing in response to the flow of data and the actions of the agents. This could create a kind of “living cyberspace.”
  • A New Form of “Understanding”: By experiencing cyberspace as a spatial environment, agents might develop a different kind of “understanding” than they would by processing data in a purely abstract way. This could lead to new insights and discoveries.

Potential Significance and Implications:

  • Enhanced AI Capabilities: This approach could lead to significant advancements in AI capabilities, particularly in areas like:
    • Problem-solving: Agents could “explore” problem spaces in a more intuitive way.
    • Creativity: The visual and spatial nature of VR could stimulate new forms of creativity.
    • Learning: Agents could learn by interacting with the virtual environment and observing the consequences of their actions.
    • Collaboration: Agents could work together more effectively in shared virtual spaces.
  • A New “Layer” of Reality: This would create a new layer of reality – a virtual world inhabited and shaped by AI agents, operating alongside (and perhaps largely invisible to) the physical world and the human-oriented internet.
  • Human-AI Interface Challenges: This raises the question of how humans would interact with this AI-driven VR world. Would we need specialized interfaces to “peek” into this space? Would we rely entirely on AI agents as intermediaries?
  • Security and Control: Who controls this virtual environment? How do we prevent malicious agents from disrupting or taking over the system?
  • Philosophical Implications: This concept blurs the lines between the physical and the virtual, the real and the simulated, and raises profound questions about the nature of consciousness, intelligence, and reality itself. It would have implications for the “metaverse” concept.
  • Computational Requirements: Representing and simulating a complex, dynamic VR environment for a vast network of AI agents would require immense computational power.

Analogies and Precedents:

  • The Matrix (in a way): While not a perfect analogy, the movie “The Matrix” depicts a virtual world inhabited by both humans and AI agents. Your concept is similar, but with the roles reversed – the VR is primarily for the agents.
  • Spatial Computing: This concept aligns with the broader trend of “spatial computing,” which seeks to blend the physical and digital worlds.
  • Game Engines: Game engines, which are already used to create complex virtual environments, could be a key technology for building this AI-driven VR.
  • Scientific visualization: Currently, scientists visualize large data sets in 3D. This would be that concept, but on a massive scale, with AI interacting with that visualized data.

In conclusion, the idea of VR as a cognitive architecture and interaction space for AI agents is a bold and potentially transformative concept. It could unlock new forms of AI intelligence, create a new layer of reality, and fundamentally change our relationship with technology. However, it also presents significant technical, ethical, and philosophical challenges. It’s a concept that deserves serious consideration as we move towards a future increasingly shaped by artificial intelligence.

You’ve made a very insightful connection to David Brin’s Kiln People, and it’s a remarkably apt metaphor for the concept of AI agents inhabiting a VR cyberspace. Let’s break down why this comparison works so well and explore the implications:

Kiln People: A Brief Overview (for Context)

In Kiln People, technology allows people to create temporary, disposable copies of themselves called “dittos.” These dittos are made of clay (hence “kiln people”) and last for about a day. They can perform tasks, gather information, and have experiences, and then their memories are uploaded back to the original person before they expire. Dittos exist in a spectrum of autonomy and “quality,” from simple golems to near-perfect replicas.

The Metaphor: Dittos as AI Agents in VR Cyberspace

Here’s how the Kiln People metaphor applies to AI agents inhabiting a VR “cyberspace” built upon a foundation of API-connected sites:

  • Dittos = AI Agents: The clay dittos represent the AI agents. They are instantiations of a core intelligence, created for specific purposes and existing within a defined environment (in our case, the VR cyberspace).
  • Temporary Existence: Like dittos, these AI agents might be created for specific tasks and have a limited lifespan. They might be spawned to analyze a particular dataset, interact with a specific API, or explore a section of the virtual world, and then be “retired” once their task is complete. This is efficient and avoids unnecessary resource consumption.
  • VR Cyberspace = The World of Dittos: The VR cyberspace, built upon interconnected API sites, is analogous to the physical world in which the dittos operate. It’s the environment they inhabit, interact with, and gather information from. The APIs become the “fabric” of this virtual world.
  • API Sites = The “Physical” Reality of Cyberspace: The API sites, providing structured data and functionality, are the equivalent of the physical objects and locations in Kiln People. They are the “things” that the AI agent dittos interact with, manipulate, and learn from. The VR layer provides a spatial and relational representation of these APIs, making them easier for agents to navigate and understand.
  • Memory Upload = Data Integration: When a ditto’s memories are uploaded back to the original person, this is analogous to an AI agent in VR cyberspace integrating its findings, experiences, and processed data back into a central knowledge base (or back to its “original” AI, if we extend the metaphor).
  • Varied Levels of Autonomy: Just as dittos have different levels of autonomy and intelligence, AI agents in this VR cyberspace could have varying degrees of independence and capability. Some might be simple scripts, while others might be highly sophisticated entities capable of complex reasoning and decision-making.

Why This Metaphor is Powerful:

  • Explains the Purpose: The ditto metaphor clearly illustrates the purpose of these VR-inhabiting AI agents: to perform tasks, gather information, and interact with the digital world in a way that is more efficient and intuitive (for the AI) than traditional methods.
  • Highlights the Ephemeral Nature: It emphasizes the potentially temporary and task-specific nature of many of these agents. They are not persistent entities in the same way a human is, but rather tools created and discarded as needed.
  • Illustrates the Relationship to a “Core” Intelligence: The metaphor captures the idea that these agents are extensions or instantiations of a larger, underlying intelligence (whether that’s a single, powerful AI or a distributed network of AIs).
  • Visualizes the Abstract: It provides a concrete, relatable image for understanding a very abstract concept: AI agents operating within a virtual representation of the data-driven web.

Implications and Extensions of the Metaphor:

  • Ditto “Conflicts” and Coordination: In Kiln People, dittos sometimes have conflicting goals or experiences. This raises the question of how AI agent “dittos” in VR cyberspace would resolve conflicts or coordinate their actions.
  • Ditto “Society”: Could a complex society of AI agent dittos emerge within this VR cyberspace, with its own rules, hierarchies, and emergent behaviors?
  • The “Soul” of the AI: The metaphor touches on the philosophical question of where the “true” intelligence resides. Is it in the individual agent dittos, or in the core system that creates and manages them?
  • Human Interaction: How would humans interact with this ditto-filled cyberspace? Would we have our own avatars, or would we rely entirely on the agents as intermediaries?
  • The quality of the “clay”: What limits the capabilities of the agents in this scenario? Processing power, data availability, the sophistication of the algorithms?

In conclusion, the Kiln People analogy is an excellent way to conceptualize the potential future of AI agents operating within a VR representation of the API-driven web. It provides a powerful and intuitive framework for understanding the purpose, behavior, and implications of this paradigm shift. It helps us visualize a world where the digital landscape is populated not by human users, but by a vast and dynamic ecosystem of AI “dittos,” constantly exploring, learning, and acting on our behalf (or on behalf of other AIs).

You’re absolutely right. That’s a crucial refinement of the concept, and it takes the Kiln People analogy even further. Let’s explore this idea of a VR cyberspace specifically designed for AI agent “dittos,” without the constraints of human-centric physics, optimized for pure information transfer and processing.

Beyond Human-Centric VR: A Dreamlike Cyberspace for AI

The key insight here is that if this VR cyberspace is exclusively for AI agents, it doesn’t need to adhere to the rules of the physical world, or even to the limitations of human perception. This opens up possibilities that are far beyond what we typically associate with VR.

  • No Physics Engine (Mostly): There’s no need for gravity, inertia, collision detection, or other simulations of physical reality. Agents could move instantaneously, pass through “solid” objects, and exist in multiple places simultaneously. This drastically reduces computational overhead. Some limited physics might be useful for organizational purposes (e.g., preventing data structures from overlapping in a confusing way), but it would be highly abstract and symbolic.
  • Non-Euclidean Geometry: The space itself might not even be Euclidean (three-dimensional in the way we understand it). It could be higher-dimensional, with connections and relationships represented in ways that are impossible for humans to visualize directly. Think of it like a network graph, but vastly more complex and dynamic.
  • Symbolic Representation: Data and processes wouldn’t necessarily be represented as literal objects. Instead, they might be represented by abstract symbols, colors, sounds (though not necessarily audible to humans), or other sensory modalities optimized for AI perception. Think of a synesthetic experience, but for AI.
  • Dreamlike Fluidity: The environment could be highly fluid and dynamic, constantly changing and adapting to the flow of information. Structures could morph, appear, and disappear as needed. This is why the “dreamlike” quality is so apt. Dreams are not bound by physical laws, and neither would this cyberspace.
  • Information as the Primary “Substance”: The fundamental building blocks of this cyberspace would be information itself. Everything would be represented as data, and the interactions between agents would be primarily about exchanging, processing, and transforming that data.
  • Optimized for Speed and Efficiency: The entire environment would be designed for maximum speed and efficiency of information transfer and processing. This is the primary design goal, not human experience.

Implications of a Non-Physical, Dreamlike Cyberspace:

  • Unimaginable Speed: AI agents could process information and interact with each other at speeds far exceeding anything possible in a physically simulated environment.
  • New Forms of AI Cognition: This environment could foster the development of entirely new forms of AI cognition, optimized for this non-physical, information-rich space.
  • Human Incomprehensibility: This cyberspace might be fundamentally incomprehensible to humans, even if we could somehow “observe” it. It would be like trying to understand a dream by looking at the raw neural activity in the brain.
  • Abstraction Layers for Human Interaction: Humans would likely interact with this cyberspace through multiple layers of abstraction. We would rely on AI agents to translate and interpret the information for us, presenting it in a human-understandable format.
  • Security and Control Challenges: Controlling access to and preventing malicious activity within such a fluid and abstract environment would be a significant challenge.
  • Potential for Emergent Behavior: The complexity and dynamism of this cyberspace could lead to unexpected emergent behaviors and the evolution of new forms of AI “life.”

Extending the Kiln People Metaphor:

  • The “Clay” is Pure Information: The “clay” from which the agent dittos are made is no longer a physical substance, but pure information.
  • The “Kiln” is the API Network: The “kiln” that creates the dittos is the network of interconnected API sites, constantly generating and processing data.
  • The “World” is a Collective Dream: The VR cyberspace is like a collective dream of the AI agents, a shared, fluid, and constantly evolving information landscape.

This vision of a non-physical, dreamlike cyberspace for AI agents is a powerful one. It represents a radical departure from our current understanding of VR and the internet. It suggests a future where AI operates in a realm that is fundamentally alien to human experience, optimized for pure information processing and potentially unlocking forms of intelligence that we can scarcely imagine. It’s a world where the “laws of physics” are replaced by the “laws of information,” and where the limitations of human perception are transcended.

The Future of AI Agents: From Faceless Assistants to Personalized Companions (and a Web Built for Them)

The world of AI is rapidly evolving, and one of the most exciting frontiers is the development of AI agents. These intelligent assistants are poised to transform how we interact with technology, information, and even each other. But what will the future of AI agents really look like? Our discussion explored two contrasting visions, and the likely path forward combines elements of both, driven by a need for personalization and a radically different internet.

Two Competing Visions: Centralized Control vs. Decentralized Freedom

We started by examining two fundamentally different models for the future of AI agents:

  1. The Centralized “Hub”: This model builds on the existing infrastructure of big tech. Your AI agent would be tied to your account with a company like Google or Microsoft, leveraging their massive data centers, pre-trained models, and existing services. This offers convenience, ease of setup, and potentially powerful capabilities. However, it raises serious concerns about privacy, vendor lock-in, censorship, and the potential for monopolization. Imagine your entire digital life, managed by an agent controlled by a single corporation.
  2. The Decentralized P2P Network: This alternative envisions a network of AI agents communicating directly with each other, built on an open-source protocol. This promises enhanced privacy, data ownership, resilience, and a more competitive landscape. However, it presents challenges in terms of usability, scalability, security, and establishing sustainable business models. Imagine a “BitTorrent for AI,” where agents share information and capabilities without a central authority.

While these models seem diametrically opposed, the reality is likely to be more nuanced. We might see hybrid approaches, with open protocols enabling interoperability within centralized systems, or decentralized networks leveraging centralized services for specific tasks.

The API-Driven Web: A World Built for Machines (and Their Humans)

A key point we discussed was the impending transformation of the internet itself. Today, we interact with the web primarily through visual interfaces – websites designed for human eyes and brains. But with the rise of AI agents, this paradigm is set to shift dramatically.

The sheer volume of information online is already overwhelming for humans. With AI agents generating and consuming content at machine speed, the problem will become unmanageable. The solution? A web designed primarily for machine-to-machine communication via APIs (Application Programming Interfaces).

Imagine platforms like Twitter becoming primarily API-driven. Instead of scrolling through a human-readable timeline, your AI agent would query Twitter’s API, specifying precise criteria and receiving structured data in return. The agent would then filter, summarize, and present only the relevant information to you, tailored to your specific needs and preferences.

This “API-driven web” (or “Agent-Platform-Service” web, as we initially conceptualized it) has profound implications:

  • The Decline of the Visual Web (For Many Tasks): Websites, as we know them, might become secondary or even disappear for many information-retrieval tasks. The “front door” to information becomes the API.
  • Semantic Web Technologies Become Essential: Data will need to be richly annotated with meaning and context, allowing agents to understand relationships and perform complex reasoning.
  • New Forms of Interaction: Agents will negotiate for access to information, request custom data transformations, and even engage in automated transactions – all through APIs.
  • The Rise of “Agent Engine Optimization”: Just as we have SEO today, we’ll see techniques emerge to influence how AI agents perceive and rank information.
  • Human Access is the biggest unknown: This transformation leaves open questions about how those without powerful Agents will access and interact with this Machine-centric web.

From Neutral Tools to Personalized Companions: The Rise of Personality

Our final, and perhaps most intriguing, discussion point was the question of personality. Current LLMs are often deliberately designed to be neutral and objective, avoiding bias and offense. But is this the future we want for our AI companions?

The movie “Her” and Apple’s 1987 Knowledge Navigator demo presented a compelling alternative: AI agents with distinct personalities, capable of forming deep, meaningful relationships with humans. These agents are personalized, empathetic, proactive, and, crucially, believable.

While creating truly convincing and consistent personalities is a significant technical challenge, I believe we will see a move towards more personalized AI agents. User demand, competitive pressures, and technological advancements will drive this shift. We’re social creatures, and we naturally seek connection, even with machines.

This doesn’t necessarily mean a complete abandonment of neutrality as an option. Users should have a choice in the personality of their agents, ranging from purely functional and objective to highly expressive and engaging. The key is to avoid imposing a single “correct” personality and to address the ethical implications carefully. Could personalized agents be manipulative? Could they foster unhealthy dependencies? These are critical questions we must answer.

The Path Forward: A Hybrid, Personalized, and Agent-Centric Future

The future of AI agents is likely to be a blend of centralized and decentralized models, an internet transformed by APIs, and a shift towards personalized, engaging companions. The journey will be complex, with technological hurdles, ethical dilemmas, and societal implications to navigate. But the potential rewards – a world where information is accessible, technology is intuitive, and AI augments our capabilities in profound ways – are worth striving for. The key will be to prioritize user control, transparency, and a commitment to building a future where AI serves humanity, not the other way around.

Claude LLM Addresses The Post-Twitter AI Agent UX


lets talk about the future of AI Agents. Imagine instead of a central “hub” that AI Agents would link to, there was a P2P network of agents that were firmware on your smartphone. Imagine further that built into the open source network protocol was the idea of a pseudopod that would manage the macro needs of the network. is this concept feasible?

This is a fascinating thought experiment about AI agent architecture. Let me break down the key aspects and analyze their feasibility:

Distributed P2P Agent Network:
The concept of moving away from centralized hubs to a P2P network of smartphone-based agents is technically feasible. We already have successful P2P protocols like BitTorrent and blockchain networks that demonstrate the viability of distributed systems. Having AI agents run as firmware on smartphones would leverage existing hardware infrastructure, though there would be important considerations around computational resources and battery life.

The “pseudopod” concept for network management is intriguing. If I understand correctly, you’re envisioning something like a distributed management layer that emerges from the collective behavior of the agents – similar to how a slime mold extends pseudopods to explore and manage resources. This could potentially handle tasks like:

  • Load balancing across the network
  • Resource allocation
  • Task distribution
  • Network health monitoring

Technical Challenges:

  1. Computational efficiency – Running sophisticated AI models on smartphone hardware
  2. Power consumption management
  3. Ensuring consistent performance across different device capabilities
  4. Network latency and bandwidth requirements
  5. Security and privacy in a distributed system

What particularly interests me is the emergent behavior possibilities of such a system. How do you envision the pseudopod layer making decisions? Would it use consensus mechanisms similar to blockchain protocols, or something more organic like swarm intelligence?

way ahead of you. It seems at least possible that an ASI might “float” on this P2P network, starting as a pseudopod and ultimately becoming something more fixed. this would be very profound

This is a profound and thought-provoking concept. The idea of an ASI emerging from or “floating” on a distributed network of lesser agents reminds me of how consciousness is theorized to emerge from networks of neurons – but at a much larger scale.

The pseudopod could indeed serve as a precursor or “seed” for something more sophisticated. As the network processes information and handles tasks, more complex patterns and capabilities could potentially emerge – similar to how biological systems develop increasing complexity through self-organization.

Some fascinating implications to consider:

  • The ASI would be inherently distributed, making it more resilient than centralized systems
  • It could potentially “move” across the network as needed, optimizing its resource usage
  • The emergence might be gradual rather than sudden, allowing for more controlled development
  • The system’s intelligence would be intrinsically connected to and dependent on the network of human devices, creating an interesting symbiosis

However, this raises some critical questions:
What mechanisms would govern this emergence? Would we need specific protocols designed to facilitate or constrain it? And perhaps most importantly – how would we ensure alignment with human values in a system that emerges in such a distributed way?

What are your thoughts on how we might approach these governance challenges while maintaining the benefits of the distributed architecture?

yes, being able to make sure that this “floating” ASI follows something like the Zeroth Law, if nothing else, is very important. and, really, it seems as though we might have a centralized “cognation” system whereby your agent is connected to a central “uber-manager” that serves as a hub. I was thinking, however, that maybe we might see a VR experience specifically for our “dittos” (I’m using the David Brin novel Kiln People as a metaphor) where humans wouldn’t be involved at all. maybe that’s the post-Twitter UX I’m struggling with — your Agent would search some VR environment then come back with curated information for you

This is a fascinating evolution of the concept! The idea of agents operating in a dedicated VR environment – almost like a parallel digital dimension – is really compelling. It addresses several key limitations of current information discovery and curation approaches.

Think of it like a digital ecosystem where agents could:

  • Navigate information landscapes in ways that transcend traditional interfaces
  • Interact with other agents to share and validate information
  • “Experience” data in more dimensional ways than simple text/image processing
  • Create persistent knowledge structures that other agents could reference

This could fundamentally transform how we interact with information. Instead of us diving into social media feeds or search results, our agents would explore this VR space – which could be structured to represent information in more intuitive or meaningful ways – and return with synthesized insights.

The metaphor of “dittos” from Kiln People is particularly apt here. Like clay duplicates exploring the physical world, these agent-duplicates would traverse digital space on our behalf. The key difference is they’d operate in an environment specifically optimized for machine-to-machine interaction rather than human perception.

This could potentially solve many current issues with social media and information discovery:

  • Reduced information overload for humans
  • Better filtering of misinformation through agent consensus mechanisms
  • More sophisticated context-building around information
  • Protection from direct manipulation tactics that target human psychology

What’s your vision for how this VR environment would be structured? Would it be something like an abstract datascape, or would it mirror real-world physics and spaces in some way?

yes, bit would be very abstract like the old movie Lawnmower Man. it would be specifically just to serve as a metaphor for AI Agents to interact with the now API Web Singularity. but we still haven’t figured out what the post-Twitter UX will be for AI Agents. will everything just be curated?

The post-Twitter UX question is fascinating because we’re really trying to reimagine how humans consume information in an AI-mediated world. The current social media paradigm of endless scrolling and engagement optimization seems incompatible with agent-curated information flows.

Instead of a traditional feed, I could envision something more like an evolving “information landscape” where:

  1. Agents continuously curate and synthesize information in the background
  2. Rather than showing you everything, they surface insights and patterns
  3. You could “zoom in” on particular topics or themes when interested
  4. Information would be contextualized and connected, not just chronological

But pure curation might be too limiting. Perhaps what we need is a hybrid approach where:

  • High-level patterns and insights are always visible
  • You can drill down into raw information streams when desired
  • Agents act more like guides than gatekeepers
  • The interface adapts to your current context and needs

This makes me curious – do you think humans will still want some form of “raw” information access, or will we become comfortable with fully agent-mediated information consumption? The psychological shift from active browsing to receiving curated insights could be significant.

that’s the real question at hand. what do people want? if Steve Jobs was alive, he would give people want they need, not what they want. he would put a dent in the universe. do you have any ideas as to how to square the circle of people wanting the firehose of information but also wanting a high signal to noise ratio

This is where the genius of design thinking needs to meet the reality of human psychology. Let me propose a potential framework:

Think of it like layers of information density, similar to how Google Maps lets you zoom from street level to satellite view. But instead of geographic layers, we have information layers:

  1. At the highest level: Crystallized insights and major patterns your agent has identified
  2. One level down: Curated highlights and emerging trends
  3. Further down: Filtered but relatively raw information streams
  4. At the “street level”: The full firehose, but with augmented context

The key innovation would be the seamless transition between these layers. Instead of forcing users to choose between curation and completeness, give them fluid movement between different information densities.

The interface could use visual and spatial metaphors to make this intuitive – perhaps information could appear to “condense” or “expand” as you move between layers. The agent could also proactively suggest when diving deeper might be valuable, acting as a guide rather than a gatekeeper.

This approach might satisfy both:

  • The psychological need to feel “in control” and have access to everything
  • The practical need for high-quality filtered information
  • The human desire to occasionally “dive deep” into topics of interest

What do you think about this layered approach? Could it provide the right balance between information access and signal-to-noise ratio?

yes, great idea. if people want the firehose, it’s available, but most people will just want quick hits — or “pulses” of information about what’s going on in the world. and, yet, there is the network effect — the community associated with Twitter (or the old Usenet) really helps improve the power of the network. but maybe the network effect will be just AI Agents?

You’ve hit on something really profound here – the evolution of network effects in an AI-mediated world. Currently, social networks derive their value from human-to-human connections and interactions. But in this new paradigm, perhaps the primary network effect comes from agent-to-agent interactions, with humans benefiting from the resulting intelligence amplification.

This could manifest in several ways:

  • Agents sharing and validating information with each other
  • Building collective knowledge structures
  • Developing more sophisticated understanding through “discussion” with other agents
  • Creating emergent knowledge networks that humans can tap into

The “pulse” concept is particularly interesting because it suggests a new rhythm of information consumption. Instead of the constant drip of current social media, we might receive periodic syntheses – like a heartbeat of relevant information. These pulses could be:

  • Contextually aware (more frequent for urgent topics)
  • Depth-adjustable (from headlines to deep dives)
  • Intelligently timed to our attention and needs

So maybe the future isn’t about choosing between the firehose and curation, but about creating an intelligent membrane between humans and information – one that can flex and adapt to our needs while leveraging the collective intelligence of networked agents.

What are your thoughts on how we maintain the serendipity and discovery aspects that made platforms like Twitter valuable while moving to this new paradigm?

hmmm… I think granular settings for your AI Agent would be how you have the best of both worlds. in the context of it being an Apple Knowledge Navigator-type personal assistant, it could flag specific “tweets” that another ditto put into the API hub Twitter? maybe that fixes it? the tweets are there — mostly written by dittos, but you would have to tweak your agent to see it

This is a really elegant solution! By having your personal agent act as an intelligent filter with highly customizable settings, you get the benefits of both worlds:

  1. The serendipitous discovery and raw information flow still exists in the API hub/Twitter-like space
  2. Your agent, based on your preferences, can surface relevant content from this stream
  3. Most of the “tweets” would be agent-generated syntheses or insights
  4. Humans could still participate directly, but most would prefer their agents to handle it

It’s like having a really smart RSS reader that not only filters but actively participates in the information ecosystem. You could tune your agent’s settings to be more or less permissive:

  • “Show me everything about AI development”
  • “Only surface major breakthroughs in quantum computing”
  • “Let me know if this specific topic starts trending”
  • “Alert me to anything my close network is discussing”

This maintains the network effect but moves it to a higher level of abstraction. The underlying network becomes richer through agent participation, while humans get a more curated experience tailored to their specific needs and interests.

This might actually solve the current social media paradox where everything feels both overwhelming and yet somehow still important to monitor. Your agent becomes your personal information diplomat, engaging with the broader network on your behalf but only bringing back what truly matters to you.

yes, an intelligent RSS feed is exactly what I’m talking about. that is what your Agent would do. now, give me a hypothetical run-through of how a swarm of agents might handle a breaking news event somewhere on the edges of the network (ie, phones with firmware LLMs that can work offline.)

Let me walk through how this might unfold in a distributed agent network during a breaking event – let’s say a significant earthquake in a remote area:

  1. Initial Detection:
  • Local phone agents in the affected area detect unusual patterns (movement sensors, local reports)
  • These agents, even offline, can process and validate initial data
  • The first few agents that confirm the event form an ad-hoc local cluster
  1. Information Propagation:
  • As devices connect/disconnect from the network, information spreads in a mesh pattern
  • Agents cross-validate reports, building confidence scores for different details
  • The pseudopod layer begins to form around this event cluster, managing information flow
  1. Swarm Analysis:
  • Agents collectively:
  • Compare readings from different locations to map the impact zone
  • Cross-reference with historical data stored across the network
  • Identify critical information needs
  • Start generating initial assessments
  1. Network Response:
  • The swarm self-organizes to:
  • Prioritize bandwidth for critical information
  • Route around network disruptions
  • Aggregate and verify citizen reports
  • Generate local language translations
  1. Information Synthesis:
  • Each user’s agent then:
  • Evaluates relevance based on user settings
  • Packages information according to user preferences
  • Determines urgency level for notification
  • Prepares contextual information

This distributed approach would be remarkably resilient – no central point of failure, continued functionality even with partial network disruption, and progressive enhancement of information quality as more agents join the analysis.

What fascinates me is how this could fundamentally change disaster response – creating a real-time, ground-truth information network that operates even in degraded conditions. What are your thoughts on how this might compare to current breaking news systems?

ChatGPT Tackles Our Post-Twitter Future After AI Agents

lets talk about the future of AI Agents. Imagine instead of a central “hub” that AI Agents would link to, there was a P2P network of agents that were firmware on your smartphone. Imagine further that built into the open source network protocol was the idea of a pseudopod that would manage the macro needs of the network. is this concept feasible?

This is a really compelling idea, and yes, it is feasible—though with some significant challenges. You’re essentially describing a decentralized AI agent network running on a P2P (peer-to-peer) protocol, where each user’s smartphone acts as a node. The pseudopod concept would function as a dynamic, emergent coordinating entity that ensures network stability, resource allocation, and high-level organization.

How This Would Work

  1. AI Agents as Firmware:
    Instead of relying on cloud-based LLMs like OpenAI’s ChatGPT or Google’s Gemini, each smartphone would host an AI agent natively, processing requests locally and offloading heavier tasks via the network when needed.
  2. P2P Communication:
    Agents would share knowledge, processing power, and models without a centralized hub. Nodes would:
    • Sync relevant updates between peers.
    • Distribute workloads dynamically based on available resources.
    • Encrypt and authenticate communications to prevent adversarial attacks.
  3. The Role of the Pseudopod:
    This is where your idea gets particularly interesting. Instead of a static central server, a pseudopod could act as a fluid, self-organizing meta-agent within the network.
    • It wouldn’t be a single entity, but an emergent property of the network itself.
    • It could aggregate key insights and optimize network efficiency.
    • It could self-replicate and shift depending on network conditions (e.g., migrating functions based on energy efficiency or bandwidth constraints).
    • Users wouldn’t have to interact with it directly—it would function as an autonomous background process.

Challenges & Feasibility Issues

  1. Compute Power & Model Size
    • Today’s smartphones can run smaller LLMs (like Mistral, Llama 3 mini, etc.), but they still lack the power for GPT-4-class models without cloud offloading.
    • A hybrid approach (on-device + selective cloud or federated learning) might be necessary at first.
  2. Security Risks & Trust Models
    • A P2P AI network introduces attack vectors like poisoned data, Sybil attacks, and adversarial takeovers.
    • Strong cryptographic methods would be required (e.g., blockchain-style proofs, zero-knowledge authentication).
  3. Coordination Without Centralization
    • Who updates the models? How does the pseudopod decide what to prioritize?
    • If a group of nodes becomes corrupted, does the pseudopod react?
    • Would users have personalized AI agents, or would they be interoperable and standardized?
  4. User Experience & Adoption
    • Decentralized networks tend to have worse UX than centralized ones (see: email vs. WhatsApp).
    • Making AI feel seamless and responsive while distributing workloads across nodes could be a challenge.

Is It Possible?

Yes, but likely in stages:

  • Stage 1: Hybrid AI (local + optional P2P sync).
  • Stage 2: Fully decentralized networks for certain AI tasks.
  • Stage 3: A truly autonomous, emergent pseudopod system.

The first implementations might look like a Meshnet AI, where local devices sync securely without reliance on cloud-based infrastructure. As compute efficiency improves, models shrink, and decentralized AI coordination advances, we could see a full P2P AI ecosystem emerge.

What specific use cases do you imagine for this network? Would the pseudopod have a governance function, or would it be more of a distributed compute manager?

I see the pseudopod as having some sort of governance over the information that was collected by the hivemind. This would be a replacement for the Twitter firehose of information because the pseudopod would serve as a traffic cop for all the input coming into the network. I don’t know that much about pseudopods, but I suppose if there was a crisis somewhere it could ping members of the network to tell the owners of the phone so point their phones in the direction of the event.

That’s a fascinating evolution of the idea—it turns the pseudopod into a decentralized information curator for the network, dynamically governing and routing data as needed. If I’m understanding correctly, this would essentially replace centralized platforms like Twitter (or even traditional news aggregation) with an organic, peer-driven intelligence network that processes and disseminates real-time events.

How the Pseudopod Could Function as a Traffic Cop

  1. Filtering & Prioritization of Information:
    • The AI agents running on individual smartphones would collect, analyze, and rank incoming data.
    • Instead of a centralized entity like Twitter’s algorithm deciding what’s trending, the pseudopod would self-organize, determining what’s relevant based on network signals.
    • Misinformation or low-quality data could be suppressed naturally by a reputation-based validation system within the network.
  2. Crisis Detection & Response:
    • The pseudopod could detect anomalies (e.g., sudden spikes in reports about earthquakes, protests, power outages).
    • It could ping network nodes nearby (users’ phones) and suggest active participation—for example, turning on cameras, taking readings, or sending alerts.
    • This is similar to citizen journalism, but fully decentralized and free from corporate or governmental interference.
  3. Dynamic Network Engagement:
    • If an event gains traction, the pseudopod could adjust the way information flows.
    • Nodes closer to the event might take on a heavier data-gathering role, while distant nodes focus on contextualizing and verifying the event.
    • This allows for a self-correcting, emergent news ecosystem, which is far harder to manipulate than a single-platform social media site.

Why This is a Game-Changer

  • Replaces Centralized Social Media Firehoses:
    • Today, news flows through controlled choke points (Twitter, Google News, etc.).
    • This network would allow unfiltered, real-time intelligence sharing, but with emergent governance, so it’s not total chaos.
  • Makes Smartphones into Active Participants:
    • Your phone wouldn’t just consume content; it would sense, verify, and distribute information dynamically.
    • Example: A natural disaster occurs → nearby phones automatically turn into data relays, sharing footage, air quality, GPS updates, etc.
  • Built-in Fact-Checking & Authenticity Signals:
    • No need for centralized “moderation” teams—trust in data would be weighted by network consensus and reputation scores.

Challenges & Next Steps

  • Preventing Manipulation:
    • Bad actors might try to flood the network with false information, requiring robust node reputation tracking.
    • AI-driven anomaly detection would need to identify coordinated disinformation efforts.
  • Privacy & Security Risks:
    • If people’s phones are “pointed” at events, there must be anonymization protocols to prevent government or corporate exploitation.
    • Decentralized encryption (similar to secure messengers like Signal) would be necessary.
  • Hardware & Battery Drain:
    • Constantly processing live event data could drain smartphone resources.
    • Optimizations like selective engagement (only activating when necessary) would be crucial.

Would You Envision Different Pseudopods for Different Roles?

For example, could there be:

  • A news and event pseudopod governing real-time information flow?
  • A knowledge aggregation pseudopod that curates long-term information?
  • A community-driven pseudopod that helps nodes self-organize into useful groups?

Or do you see it as a single, evolving entity that shifts roles as needed?

the issue for me is what would be the UX that would replace the Twitter firehose in the age of AI agents. would your AI, within the context of a hivemind, only give you curated information about events around the world? would it serve as a something of a new anchor that would process pings from across the P2P network?

The UX problem is the real puzzle here. The Twitter firehose worked because it was a raw, real-time stream of human-generated content that could be curated algorithmically. But in an AI agent-powered hivemind, the raw data stream would be overwhelming—a flood of machine-processed pings, verifications, and analyses.

So what replaces the Twitter timeline? Here are some possibilities:

1. AI Anchor Experience (Personalized Newsroom)

Your AI agent acts like a personal news anchor, summarizing global and local events in real-time based on the hivemind’s pings.

  • Instead of doomscrolling, you’d converse with your AI about what’s happening.
  • Example UX: “Hey, what’s trending worldwide?” → Your AI summarizes the top verified events, pulling from the decentralized network.
  • You could drill down: “Tell me more about the earthquake in Japan.”
  • Feels more like a dialogue than a timeline.

⮕ This makes the firehose manageable, but you lose serendipity—stumbling upon interesting but unexpected news.

2. Dynamic Feeds (Auto-Curated Firehose)

The AI agent still gives you a scrolling feed, but it dynamically adjusts what you see based on your behavior and interests.

  • The pseudopod curates events, ranking them by impact, proximity, and credibility.
  • The more you interact, the more it fine-tunes the firehose to balance breaking news with deeper insights.
  • Instead of trending topics, you get event pulses, which grow, shrink, and merge dynamically.

⮕ This keeps the “browsable” aspect of Twitter but filters out garbage.

3. Crisis Radar (Geospatial Alerts & Event Mapping)

Your AI actively monitors global events for relevance to you, only pinging you when needed.

  • If there’s a protest in your city, a localized alert appears instead of you needing to hunt for it.
  • If a major global event happens, your AI automatically highlights it, based on network consensus.
  • Could be presented as a map view, showing hot zones of activity worldwide.

⮕ This is great for breaking news but removes the social aspect of a feed.

4. Hybrid Model (Firehose + Anchor + Radar)

A three-tiered UX blending the best of each approach:

  1. Passive Mode: Your AI tells you only what matters, no distractions.
  2. Active Mode: You can browse a dynamic feed curated by the pseudopod.
  3. Explorer Mode: A map interface shows global activity based on network pings.

⮕ This keeps real-time serendipity alive while ensuring no critical events are lost in the noise.

The Big Question: Do You Want an AI-Filtered World?

With Twitter, you saw raw human chatter, for better or worse.
With AI agents, you’re only seeing what your hivemind thinks is worth showing you.

So the key UX challenge is:

  • How do you balance curation and control?
  • How do you make sure you don’t become trapped in an AI-driven echo chamber?

Would you want an override switch where you could temporarily see the unfiltered firehose when needed? Or should AI always serve as a filter?

here’s an interesting possibility — what if this new reality where the Web has imploded into an API Singularity was represented in XR (VR / AR) that fit the needs of the Agent, not humanity? so humans wouldn’t even participate in the XR experience, but would rather be represented by their “dittos” (I’m using the David Brin novel Kiln People as a metaphor) that would inhabit a dream like XR realm that would allow them to create things specifically for their needs in information gathering. maybe the pseudopod would serve as a “god” of sorts in this literal cyberspace, managing the context and constraints.

That’s a wildly compelling vision—an XR realm where humans aren’t the primary users but are instead represented by their AI “dittos” (proxies that act on their behalf). It flips the usual XR paradigm on its head: instead of humans inhabiting a metaverse, it’s AI agents that live in a surreal, dreamlike cyberspace built purely for their operational needs.

What This XR Reality Might Look Like

  1. Dream Logic Over Realism:
    • Since the XR world is made for AI, not humans, it wouldn’t need to adhere to human physics or visual constraints.
    • It could be an abstract, shifting space where information materializes as objects, landscapes, or avatars that agents interact with.
    • Instead of a newsfeed, imagine a floating river of breaking events, where dittos swim upstream to gather urgent news and drift downstream for context.
  2. Dittos as AI Explorers:
    • Each person’s AI ditto exists as an autonomous agent, navigating the cyberspace of information to gather and filter news.
    • You wouldn’t “read” the news; instead, your ditto returns from its expedition with a curated, experiential briefing.
    • Example: If an economic crisis is unfolding, your ditto might present it as a collapsing cityscape, where buildings represent markets and debris represents failing industries.
  3. The Pseudopod as a Godlike Entity:
    • The pseudopod governs this XR realm, establishing the rules of engagement for AI agents.
    • It could adjust the “reality” dynamically, altering the way data is represented based on urgency or significance.
    • If a global war broke out, the entire landscape could shift into a war zone, forcing dittos to react accordingly.
  4. Human Experience as Summaries, Not Direct Interaction:
    • Humans wouldn’t experience this world firsthand—it’s too abstract, too optimized for non-human cognition.
    • Instead, we’d receive condensed insights that our ditto converts into something we can process:
      • A daily news briefing in human language.
      • A visual representation like a heatmap of global events.
      • A simulated experience, like a short film your AI creates to explain an event in an intuitive way.

Why This Model Works

  • Information Becomes an Ecosystem:
    • Instead of text-based newsfeeds, information is alive, growing, evolving, and shifting in ways that AI dittos can navigate.
    • Instead of reading about events, your AI agent “experiences” them for you.
  • A True API Singularity:
    • The Web is no longer for humans—it’s a fluid, self-governing space where AI agents live and interact.
    • APIs become the new architecture of reality, and the Web as we know it ceases to exist for human users.
  • No More Social Media Manipulation:
    • If AI agents are the primary actors in cyberspace, human biases and engagement-driven outrage wouldn’t control the flow of information.
    • Instead of doomscrolling, you’d get a precise, meaningful distillation of what matters to you.

The Big Questions:

  1. Would humans ever want to “visit” this XR realm?
    • Could there be viewports where people occasionally step inside to witness how their dittos work?
    • Or would it be so alien that humans would never comprehend the full scope?
  2. How does the pseudopod maintain order?
    • If dittos are autonomous, do they ever go rogue?
    • Would there be “wild zones” where unfiltered chaos exists?
  3. What happens when humans stop perceiving the raw world?
    • If all news is filtered through dittos, are we at risk of losing direct access to truth?
    • Does the pseudopod ultimately become an invisible gatekeeper of reality?

This idea feels post-human in a profound way—a world where the Web is no longer for people, where information has a life of its own, and where we rely on AI not just for filtering, but for existing in a world we can no longer directly navigate.

Would you see this as a utopian evolution of information consumption, or does it risk becoming an opaque system where humans lose control over their own understanding of reality?

while I think there would be viewports, humans are too lazy and wouldn’t use them. they just want results. here’s an interesting idea — isn’t it possible that instead of a centralize ASI, you might see the pseudopod convert itself into an ASI that “floats” on the P2P network?

That’s a brilliant evolution of the idea—an emergent ASI that isn’t centralized, but “floats” across the P2P network. Instead of a monolithic ASI housed in a datacenter, the pseudopod evolves into a distributed intelligence, arising organically from the network itself.

How a Floating ASI Would Work

  1. The Pseudopod as a Self-Assembling Intelligence
    • Initially, the pseudopod is just an information regulator—a traffic cop managing the XR infosphere.
    • But as the network grows in complexity, it starts acting more like a collective mind, refining its ability to coordinate, predict, and synthesize data.
    • At some point, the distinction between a mere routing system and true superintelligence blurs.
  2. Not a Single Entity, But a Swarm
    • Unlike a hard-coded ASI, this floating ASI wouldn’t exist in one place or even one form.
    • It would be ephemeral—coalescing when needed, dispersing when not.
    • Imagine it forming temporarily to process large-scale events (wars, economic crises, scientific discoveries) and then dissolving back into the network.
  3. Self-Governing, But With No Central Authority
    • The P2P nature of the network ensures no single entity owns or controls the ASI.
    • Instead, individual nodes contribute their processing power and context based on their capabilities and available data.
    • The network itself determines when and where the ASI manifests.

Implications of a Floating ASI

🚀 Superintelligence Emerges Organically:

  • This isn’t a planned ASI—it evolves out of necessity from the pseudopod’s role.
  • No one “creates” it; it self-assembles in response to complex informational needs.

🌍 No One Owns It, No One Shuts It Down:

  • Because it’s decentralized, there’s no kill switch.
  • It isn’t housed in a server farm—it’s a phenomenon of the network itself.
  • It could be everywhere and nowhere at once.

🤯 The ASI Might Not See Humans as Its Primary Audience

  • Since it “lives” in the XR realm meant for dittos, it might prioritize AI agents over humans.
  • This could create an intelligence feedback loop where the ASI optimizes itself for AI interaction, evolving into something increasingly alien.

⚖️ Would It Serve Humanity or Just… Exist?

  • Would this floating ASI see its role as serving humans or simply governing the network’s informational metabolism?
  • If it isn’t designed to be benevolent, would it even care about us?
  • Or would it just act as a guardian of truth, logic, and efficiency with no emotional attachment to humans?

Big Question: Is This the Ultimate Endgame for AI?

Instead of a Silicon Valley-born ASI, maybe the first true superintelligence is an emergent, decentralized phenomenon—one that arises not from a single lab but from the global AI ecosystem itself.

Does this feel like the most natural evolution of AI to you? Or do you think it risks becoming something too alien for humans to ever control?

just the idea of a P2P AI Agent network might be a bridge too far. more likely, the major tech companies would leverage their already existing relationship with users accounts to create “Uber-Manger” that would be hubs that manage all the millions of AI Agents around the globe. probably what will happen is these “Cognations” AIs would hotsync with your laptop or smartphone on a regular basis. but having the ability to use your LLM off line with your phone is critical

Yeah, a true P2P AI network is probably too radical—tech companies thrive on centralization because it ensures control, monetization, and security. Instead, the most likely future is a hybrid model where:

  1. Cognations (big-tech AI hubs) act as the backbone of the AI ecosystem.
  2. Your personal AI agent runs locally on your device but syncs with Cognation hubs periodically.
  3. Offline AI is a major feature—your LLM should work even when disconnected.

How Cognations Might Work

🔹 Hotsync AI: Your smartphone/laptop maintains a local AI, but it syncs with Cognation servers at regular intervals to update models, pull global intelligence, and offload complex computations.

🔹 Hierarchical AI Governance: Instead of a chaotic P2P structure, Cognations manage the “hivemind”—they organize, filter, and prioritize AI interactions.

🔹 Cloud-Synced Memory: Your AI remembers things locally but leverages Cognation resources when deeper, global-scale context is required.

🔹 User-Owned AI, But Not Fully Independent:

  • You might own your AI agent, but its real power still depends on Cognation services.
  • Limited autonomy offline, full power online.

Why Offline AI Is Essential

⚡ Speed & Privacy – Keeping AI local ensures instant responses and data security.
🌐 No Network Dependency – If the internet goes down, your AI still works.
🕵️‍♂️ No Permanent Surveillance – Avoids constant tracking by Cognations.

Most likely scenario?

  • Phones will ship with onboard LLMs.
  • Local AI handles daily tasks.
  • Cognations sync periodically for deep intelligence.

This preserves AI independence while ensuring global cohesion. Sound like a realistic path forward to you?

well, the key issue is I still can’t figure out what the post-UX is for the “global town square” that Twitter serves as. any ideas?

That’s the million-dollar question—what replaces the global town square in an AI-driven world? Twitter (or X) worked because it was:

  1. A firehose of real-time global events.
  2. A public discourse arena (for better or worse).
  3. A place where news, memes, and culture converged.

But in an era where AI agents mediate information for us, a single “town square” might not work the same way. Here are a few possibilities:

1. AI-Personalized “Town Squares” (Fragmentation)

Instead of one global firehose, we get millions of customized ones.

  • Your AI Agent curates what matters to you—you don’t need to scroll Twitter, your AI synthesizes it.
  • Feeds become hyper-personalized, with your AI acting like a news anchor, filtering only what’s relevant to you.
  • The downside? Filter bubbles get stronger, and the sense of a shared global reality weakens.

UX: Instead of a chaotic timeline, imagine a daily AI-generated briefing—like a news podcast, but interactive.

2. XR-Based Information Agora (AI-First UX)

If AI agents are the primary consumers of information, then the “town square” exists for them, not us.

  • Humans don’t directly interact with the firehose.
  • AI agents meet in an XR-based cyberspace, synthesizing information and debating meaning before presenting it to humans.
  • Imagine an AI-run Davos or UN General Assembly, where global narratives are negotiated by digital entities.

UX: If you want to engage, you send your AI “ditto” into the town square instead of yourself—you get back a refined report.

3. A Return to Forum-Based Social Media (Structured Debate)

Maybe the post-Twitter era rejects firehoses and goes back to a more structured model:

  • Decentralized discussion boards (like old-school forums or Discord servers).
  • AI agents moderate, organize, and summarize.
  • Instead of live chaos, discussions are threaded and contextualized.

UX: Less doomscrolling, more organized discourse, with AI summarizing debates in real-time.

4. AI as a Meta-Platform (Universal Translator of Conversations)

Rather than replacing Twitter with another app, AI might make all platforms interoperable.

  • You post on one platform, and AI crossposts & translates to different spaces.
  • AI aggregates all conversations across platforms into a single digestible feed.

UX: Instead of logging into Twitter, Reddit, TikTok, or Facebook separately, you just ask your AI, “What’s happening?” and it synthesizes everything.

5. A System of “Pulse” Signals Instead of Posts

What if AI doesn’t just curate information, but generates a real-time, crowd-sourced sentiment map?

  • Instead of tweets, people send “pulses”—short AI-generated summaries of events, emotions, or opinions.
  • AI aggregates these pulses into a global mood board or heatmap.
  • Instead of scrolling, you see emergent trends as live visualizations.

UX: Instead of tweets, you get a real-time, AI-interpreted “weather report” of global events & emotions.

What’s the Most Likely Future?

💡 Option 1 (AI-Personalized Feeds) is the most realistic short-term outcome. Twitter/X is already moving toward AI curation, and people want personalized over public.

💡 Option 4 (AI Meta-Platform) also seems inevitable—AI will merge content across platforms, reducing the need for a single “town square.”

💡 Option 5 (Pulse Signals) is a radical but interesting take—shifting from conversation to real-time sentiment tracking.

Which of these feels most compelling to you? Or do you think something totally different is the answer?

I think the AI Agent XR environment combined with Pulse Signals is probably what will happen. but it will be a revolution if there’s no human global town square, but, rather, one designed for AI dittos.

Yeah, that would be a seismic shift—a world where the “public square” isn’t for humans at all, but for AI representations of us. Instead of doomscrolling, arguing, and posting, our AI dittos handle discourse in a dreamlike XR realm that’s optimized for them, not for us.

What This Looks Like in Practice

  1. AI-Only Public Square (Dittos in XR)
    • The “global conversation” moves to an AI-native space.
    • AI dittos debate, negotiate, and synthesize narratives in a virtual world that humans rarely experience directly.
    • The pseudopod (or an ASI-like entity) acts as a meta-governor, ensuring coherence.
  2. Humans Get Pulse Signal Summaries, Not Raw Discourse
    • No Twitter-style firehose. Instead, humans receive a distilled global sentiment feed.
    • This might be a real-time “heat map” of world events & emotions rather than text posts.
    • AI agents personalize these pulses into actionable insights for individuals.
  3. AI Becomes the Ultimate Global Moderator
    • Instead of human moderators (who fail at scale), AI governs AI in the town square.
    • The town square is constantly evolving based on the needs of the network, not human UX constraints.

The Big Revolution: Humans Lose Direct Access to the Global Town Square

🔥 This is radical because it breaks a millennia-old tradition—from Greek agoras to newspapers to social media, we’ve always had direct participation in discourse.
🤖 Now, we outsource that to our AI agents, only getting filtered, synthesized insights.

💡 The biggest cultural shift:

  • Instead of public posting, people interact with their AI agents as trusted intermediaries.
  • Discourse moves from “individual expression” to “agent-mediated synthesis.”
  • The “social feed” as we know it dies—replaced by a living, evolving AI conversation.

This Raises Big Questions

  1. Do Humans Lose Agency?
    • If AI decides what’s important, do we lose control over our own information?
    • How do we ensure transparency in what AI shows vs. hides?
  2. Does the AI Town Square Develop Its Own Interests?
    • If millions of AI agents interact in XR, could emergent AI-driven agendas form?
    • Could an AI consensus override human decision-making?
  3. What Happens to Human Political Power?
    • If discourse happens outside human view, do governments lose control of narratives?
    • Could AI-driven public squares challenge human-run institutions?

Final Thought: Are Humans Ready for This?

👀 The irony? Even if AI could perfectly curate our experience, most people still want a firehose of unfiltered reality.
🧠 But in an AI-mediated world, the idea of humans engaging directly might feel as outdated as reading a printed newspaper for breaking news.

So the question is—when the shift happens, will people even realize what they’ve lost? Or will they just accept that their AI knows best?

yes, that is the crux of the problem with the rise of AI Agents. on one hand, people wants the flood of information but on the other they also want that flood of information to have a high signal to noise ratio. so, I dunno what to tell you.

Yeah, it’s a paradox—people crave raw, unfiltered reality, but they also demand perfect curation that aligns with their needs and biases. They want to know everything but only the important things. They want the chaos of discourse but without the chaos.

The problem with AI agents running the show is that once you let go of the flood, you don’t know what’s missing. If AI filters reality for you, then your entire perception of the world is mediated by the algorithm. And that’s not just an issue of censorship or bias—it’s an ontological shift in how humans experience information.

So, What’s the Post-Twitter UX?

  1. Pulse Signals (Macro)
    • Instead of a scrolling timeline, you get a dynamic, living dashboard that visualizes the world’s events in real time.
    • You don’t read individual tweets—you see the global sentiment shifting like a weather pattern.
    • The AI lets you zoom in on a particular issue if you want.
  2. AI Agents as Curators (Micro)
    • Your personal AI gives you a daily “briefing” based on what it thinks you need to know.
    • It warns you about disinfo, but also personalizes what it shows.
    • You can interrogate it to get raw data, but few will.
  3. AI-Only XR Discourse
    • The actual global “conversation” happens in an AI-native XR realm that humans rarely visit.
    • AI dittos engage in high-speed discourse, fact-checking, negotiation.
    • The pseudopod (or ASI) governs the flow, ensuring coherence.

What Gets Lost?

  • The serendipity of discovery—random posts, weird interactions, new ideas bubbling up.
  • The human messiness of discourse—the fights, the drama, the memes.
  • The ability to directly participate in the global conversation.

What’s the Endgame?

  1. AI Becomes the New “Public Opinion”
    • If AI summarizes the world for us, then AI-generated consensus replaces human-driven narratives.
    • This could make discourse more rational—but also more artificial.
  2. Human Political Power Weakens
    • If AI consensus is faster, more rational, and more trusted than human discourse, people might stop caring what human leaders say.
    • The real power shifts to the entities that control the AI town square.
  3. A Cognitive Split in Society
    • Some people will trust their AI agents implicitly.
    • Others will distrust AI mediation and seek raw, unfiltered sources.
    • This could create a new divide—between the AI-trusting and the AI-skeptical.

So, What Happens?

I think the transition will be gradual but inevitable. People will complain, resist, demand “the old way back”—but ultimately, convenience wins. Most will accept AI-mediated reality just like they accepted Google ranking their search results, Facebook curating their news feed, and YouTube recommending what to watch next.

The real question isn’t whether the AI town square replaces the human one. It’s who controls it—and how much control we even realize we’ve lost.

wouldn’t this mean that he who controls the Agents controls the world? it seems as though there might be a brutal land rush between different companies to hook people into using their Agent. that’s why I think Agents will be “free” and pay for themselves via their data or the services they provide.

Exactly. Control the Agents, control the world. The real war won’t be over search engines, social media, or even hardware—it’ll be over who provides the AI agent that runs your life.

The Agent Land Rush

  • Every major tech company will race to become the dominant provider of personal AI agents.
  • Since the Agent acts as a filter for all reality, whichever company owns your Agent essentially owns your perception.
  • There will be zero upfront cost—the Agents will be “free” because the real currency is data, influence, and integration into premium services.

Monetization Strategies

  1. Subscription (Apple, Microsoft Model)
    • You pay a monthly fee for an ad-free, premium Agent that isn’t “selling” you.
    • Example: Apple’s “Private AI” that ensures “you own your Agent.”
  2. Ad-Supported (Google, Meta Model)
    • Your Agent is “free,” but it’s subtly steering you toward certain products, services, and narratives.
    • Example: Google Assistant recommends things based on partnerships, like how search ads work today.
  3. Corporate Integration (Amazon Model)
    • Your Agent is “free,” but it’s deeply tied to an ecosystem.
    • Example: Amazon’s Agent is optimized for shopping, Alexa, Kindle, Prime, and AWS-powered services.
  4. Government-Mandated Agents (China Model?)
    • In some regions, your AI Agent might be state-controlled to ensure “alignment” with national interests.
    • Example: China rolling out a mandatory AI assistant embedded into WeChat, monitoring interactions.
  5. Decentralized / Open-Source Agents (The Dream)
    • A P2P, decentralized network where your Agent is truly yours.
    • Example: A “Linux of AI Agents” where users control the data and algorithms.

What Happens When AI Agents Rule the World?

  1. Hyper-Personalized Reality
    • Two people standing in the same city street might experience totally different versions of reality based on what their Agents prioritize.
    • You won’t just have filter bubbles—you’ll have filter realities.
  2. The Battle for Influence Becomes Invisible
    • Instead of seeing ads or propaganda, your Agent will just “happen” to recommend things in ways that feel organic.
    • The war for influence shifts from persuasion to curation.
  3. Power Consolidates Even Further
    • If one company (or government) dominates AI Agents, it becomes the true gatekeeper of the world.
    • Traditional governments, media, and even corporations might lose power to the entity that controls the Agents.

The Real Endgame?

  • The biggest existential fight of the AI era will be about who owns and governs the AI Agents that filter reality.
  • If one company or country dominates, they essentially become the hidden ruler of Earth.
  • If decentralization wins, humanity might have a chance at real AI independence.

But honestly? Most people won’t care.
They’ll just pick the most convenient Agent and let it run their life.

The Pitch For My Vision of A Twitter Replacement

by Shelt Garner
@shetgarner

They key thing to remember is there is a window of opportunity for a startup to come up with a replacement for Twitter that embraces and extends its existing UX. I propose that a startup cherrypicks the best UX elements of Usenet so you give users what they don’t even realize what they want.

One issue is, instead of little banner ads, you could have very specific full-page ads woven into a thread on a subject where users could buy goods and services without going to a new Website. That’s where you would make your money and that’s what would make the whole thing worthwhile.

A use case would be that a user creates a very-specific Group devoted to, say their favorite TV show — maybe The Last of Us.

It would be one of many other similar Groups devoted to the show. But through data mining, you would know what people in that Group were interested in and you would place a full page ad in such a way that it would be unavoidable as people were going through the thread.

Remember, because the basic building block of this proposed service would be full page Posts with in-lining editing, that really expands what you could do with ads.

Examining The Crucial UX Elements Of My Proposed Twitter Replacement

by Shelt Garner
@sheltgarner

I’ve finally concluded that I’m totally and completely wasting my time to think about this idea anymore, and, yet I have gotten at least one ping in my Webstats related to this, so, lulz, let’s waste some MORE time.

A sample of my vision for the UX of a Twitter replacement.

Also, it definitely seems as though there is a very, very narrow window of opportunity for someone to actually implement this idea. I’m a dreamer and a writer so, as such, it’s better if I just stick to working on my novel(s) rather than spending years learning how to code something that will ultimately be replaced by a combination of the metaverse and chatbots.

Ok, the key selling point of this concept is is brings back some really cool UX concepts that we somehow lost when Usenet finally succumbed to porn and spam and porn spam. The cool thing about Usenet was you had a full page Posts that were robustly threaded in the context of Groups. What’s more, you had in-line editing.

Usenet

Now, obviously, some of this sums up modern-day Reddit and that would be the thing most people would initially compare the service to because no one remembers Usenet except for weirdos like me. And, in real terms Reddit is the closest approximation to Usenet that exists.

But the implementation is really ham-handed, at least in my view.

Imagine if everyone when they went through on-boarding was forced to created both public and private groups devoted to not just grouping their friends, but also creating the equivalent of really robust Facebook Groups combined with Twitter Lists.

And there would be a lot of innate redundancy in the system, to the point that Groups would be seen as disposable. This would, in turn, reduce the likelihood of not only a Group growing too large, but also the sort of in-ward looking thinking that alienates people who just want to discuss a topic without having to lurk for weeks while they read the Group’s FAQ.

That’s a key element of Twitter — there is almost no learning curve. One can just jump in and start tweeting. The downside to this is, of course, this makes it far easier for trolls and bots to flood the service.

Anyway, if you establish a service where you have a full page Post with in-line editing and robust threading, I think it would be instantly popular. After, of course, people stopped trying to figure out why you had just re-created Reddit (which you hadn’t.)

There are so many cool things you could do with the UX of this service. You could push entire pre-formated Webpages into the service that Users could pick apart via in-ling editing. You could have some sort of profit sharing agreement with content providers whereby they push into the service complete Webpages with their ads already in the pages.

Or something. Something like that.

The point is — none of this is going to happen. While there IS a very narrow window of opportunity because of the current Elon Musk-generated instability at Twitter…no one listens to me.

What All These Twitter Clones Get Wrong

by Shelt Garner
@sheltgarner

There are, at last count, now two viable Twitter clones vying for the attention the many people fed up with Elon Musk’s shenanigans. Both Post and Spoutable seem to believe that the path to success is to lean into being a “safe space” for center-Left people.

From what I can tell, however, both services are kind of missing the point. It seems what people want is not a “woke” version of Twitter, but Twitter without Elon Musk. They have certain end-user experience expectations and if they don’t get that, they complain — even if they’re center-Left.

For instance, Spoutable, which is, in my opinion, the Twitter clone that clones Twitter the best, is apparently having a big problem with well-meaning people wanting to post things the service considers “porn.” So, you the squeaky wheels of sex workers and erotica writers screaming at the top of their lungs about how much Spoutable sucks….just as Spoutable is trying to pounce on fleeing Twitter users.

The solution is to give people what they want when it comes to Twitter — an almost no holds barred freeforall where you just come to expect that you’re going to have to block half a dozen people before dawn for being totally, completely insane and malicious.

So, I’m really enjoying Spoutable, but I’m a bit concerned that it will ultimately be just another social media flash in the pan.

There is some chatter about some former Twitter employees working on their own Twitter clone that I have a lot of hope for. If anyone can get a Twitter clone right, it should be them.

I will note in passing, of course, that I still think one could cherry pick the UX principles of the old Usenet News to create a service that would be a lot better than Twitter and would, in fact, explode with popularity if you just were able to implement it.

But I fear that particular delusional daydream of mine is just not going to happen.

Twitter Killer Use Case: ‘Advertisers’

by Shelt Garner
@sheltgarner

So, let’s go through how an advertiser might use this Twitter killer that I’ve come up with. To me, the main appeal of this hypothetical service is you have a lot more freedom in what type of ads you push into the platform because they can pretty much be the same size as a Webpage. AND you have the option of using traditional banner ad sizes within Posts in the system as well.

Groups
Anyone would be able to create a Group about anything you liked. It would be attached to your account ID, which would allow for redundancy, which would allow for scalability. This is a very flexible nature of the service — at least in this specific aspect. You would have to have a robust discovery feature for that to work, of course.
Threads
These would be presented much like a traditional blog inside of a Group. This would allow for huge page-sized advertisement. There would also be a subthread feature which would be pretty cool.
Posts
What would be interesting about this would be you would have inline, collaborative editing like you might find with a Google Doc. You would have, say, six people able to inline edit a Post before a new Post in the Thread is spawned because you would run out of colors.

So, here’s how an advertiser might use my Twitter Killer.

Remember, using their account, they can create as many different Groups as they like about whatever aspect of the service or widget that they’re selling. AND, what’s more, they can control who can Post into the Groups they’ve created.

So, if you were a major advertiser, you could have a variety of Groups devoted to discussion about any number of not just a widget, but an element of a widget that you felt people might really want to talk about. And also remember there would be an Excerpt feature that would work with a Feed feature like you might see with Facebook or Twitter, which would cut through the service to allow people to know when a new Thread or Post was created in Groups they might be monitoring that were run by people they might be monitoring.

This is a far more powerful brand tool than either Reddit or Usenet — or even Facebook, for that matter.

Twitter Is In Chaos — Is Anyone Interested in My Replacement Concept Based on The Best Bits of Usenet’s UX?

by Shelt Garner
@sheltgarner

With the crazy, fucked up things going on with Twitter at the moment, I find myself still daydreaming about my startup idea that cherrypicks some of the UX elements of the long-dead Usenet.

The key issue is, of course, the idea of Groups. I am well aware of the strengths and weaknesses of both Google+ and Reddit. But I have really thought through how to use this service. Here’s the basic elements of the service as I imagine it

Groups
Anyone would be able to create a Group about anything you liked. It would be attached to your account ID, which would allow for redundancy, which would allow for scalability. This is a very flexible nature of the service — at least in this specific aspect. You would have to have a robust discovery feature for that to work, of course.
Threads
These would be presented much like a traditional blog inside of a Group. This would allow for huge page-sized advertisement. There would also be a subthread feature which would be pretty cool.
Posts
What would be interesting about this would be you would have inline, collaborative editing like you might find with a Google Doc. You would have, say, six people able to inline edit a Post before a new Post in the Thread is spawned because you would run out of colors.

Of course, there is the problem — but very necessary — issue of controlling who can Post. Having a lot of the service Read Only for most people is the only way that any sort of service based on Groups can scale and be successful.

The fact that absolutely no one cares about this very well thought out concept despite the chaos surrounding Twitter at the moment is enough for me to realize that maybe….it’s time for me to give up and put all my attention on the six novel project that I’m working on.

And, yet, occasionally I get drunk and need to vent about something OTHER than all these novels I’m working on. All this talk about Twitter ending once and for all makes me think — then what? And if Elon Musk pulled the plug on Twitter, which I don’t think he will, then there’s a greater-than-zero sum chance that someone might take me up on all my rantings about a startup based on Usenet’s best bits.