What AI Agent Should YOU be Using?
Riley Brown · 2026-05-14
💡 Quick Take
1. Understand the two main categories for AI agents: persistence (offline vs. always on) and access (full computer vs. limited sandbox).
2. Cloud Co-work offers a highly limited, sandboxed environment for safety, especially for non-technical users.
3. Manis provides an ephemeral, task-based computer in the cloud, spinning up and down as needed.
4. Cloud Code and Code-X run locally on your computer, offering full access and acting like you.
5. Open-Claw operates as an independent entity with its own computer and "heartbeat" for proactive task completion.
6. Secure cloud "claws" (remote Open-Claw instances) offer the benefits of Open-Claw without the local hardware and security concerns.
7. Choose an agent based on six criteria: synchronous/asynchronous operation, identity (acts like you vs. itself), data storage location, autonomy, cost, and danger level.
8. Agents are trending towards cloud-based, more autonomous, and persistent solutions, mirroring the shift from local to cloud SaaS.
9. Consider specialized agents for specific tasks versus a "god" agent with many skills.
10. AI agents are evolving towards human-like operation, including self-improvement and "dreaming" to predict future needs.
📊 Detailed Explanation
1. Understand the two main categories for AI agents: persistence (offline vs. always on) and access (full computer vs. limited sandbox). This is your foundational mental model for understanding the different types of AI agents out there. Persistence is about whether the agent stays active when you're not actively using it or if it powers down. Access is about how much control and freedom the agent has – can it mess with your whole computer, or is it confined to a safe little digital playpen?
2. Cloud Co-work offers a highly limited, sandboxed environment for safety, especially for non-technical users. Think of this as the super-safe option. Anthropic built it this way to prevent accidental data deletion or misuse by people who might not understand the implications of giving an AI full access. It's like giving a helpful assistant a very specific, contained workspace where they can't accidentally break anything important.
3. Manis provides an ephemeral, task-based computer in the cloud, spinning up and down as needed. This is a really neat middle ground! Manis gives you a whole computer environment, but it's temporary. It's like renting a dedicated workspace for a specific project and then giving it back when you're done. This limits the "blast radius" if something goes wrong, but it's more capable than a strict sandbox. It's great for tasks that need a file system and the ability to run code, like generating a landing page.
4. Cloud Code and Code-X run locally on your computer, offering full access and acting like you. These are your power tools that live right on your machine. They have the freedom to explore your files, create and edit documents, and generally act as an extension of yourself. The transcript highlights how you can ask Cloud Code to dig through your downloads and documents to create a summary, and it can even open the resulting PDF for you. This means they can do pretty much anything you can do on your computer.
5. Open-Claw operates as an independent entity with its own computer and "heartbeat" for proactive task completion. This is where things get really interesting! Open-Claw is designed to be its own agent, almost like a digital employee. It gets its own "computer" (often a separate machine like a Mac Mini) and has a "heartbeat" – a regular check-in to remind it of its goals and to take proactive steps. This is what allows it to surprise you with helpful actions, like preparing a document for an upcoming meeting, just like a great human employee would.
6. Secure cloud "claws" (remote Open-Claw instances) offer the benefits of Open-Claw without the local hardware and security concerns. This is the evolution of the Open-Claw concept. Instead of buying and managing your own physical hardware, these agents live in data centers. They offer the same autonomy and proactivity as Open-Claw but with better security, reliability, and scalability. Think of it as hiring a remote, highly capable employee who has their own dedicated office space.
7. Choose an agent based on six criteria: synchronous/asynchronous operation, identity (acts like you vs. itself), data storage location, autonomy, cost, and danger level. This is your cheat sheet for picking the right agent! Do you want to be involved in every step (synchronous) or let it run in the background (asynchronous)? Should it mimic your actions or be its own entity? Where do you want your data to live? How proactive do you want it to be? What's your budget? And how much risk are you comfortable with? These questions will guide you to the best fit.
8. Agents are trending towards cloud-based, more autonomous, and persistent solutions, mirroring the shift from local to cloud SaaS. The future is looking cloud-bound and self-sufficient for AI agents. Just like we moved from desktop software to cloud-based services, agents are heading in the same direction. They'll have their own persistent environments, act more independently, and be accessible from anywhere, just like your favorite cloud apps.
9. Consider specialized agents for specific tasks versus a "god" agent with many skills. It's like hiring a team versus one super-powered but potentially overwhelming individual. For complex or diverse needs, having dedicated agents for SEO, programming, marketing, etc., might be more effective than trying to manage one agent with a hundred different skills. It keeps things focused and efficient.
10. AI agents are evolving towards human-like operation, including self-improvement and "dreaming" to predict future needs. This is the cutting edge! Agents are learning to operate more like humans, with features like "dreaming" at night to process the day's interactions and come up with proactive tasks for tomorrow. They're also auto-improving, getting smarter and more helpful over time. It's all about making AI work *for* you, not the other way around.
🎯 Expert Opinion
This video provides a fantastic framework for understanding the rapidly evolving landscape of AI agents. The categorization based on persistence and access is spot-on and incredibly helpful for demystifying the options. What's really exciting is the clear trend towards **cloud-native, highly autonomous agents**. The analogy to the SaaS revolution is perfect – we're seeing the same shift from local, user-managed tools to scalable, persistent cloud services, but for AI agents. This means we're moving beyond agents that require constant babysitting or a dedicated physical machine. The concept of "secure cloud claws" is particularly compelling, as it addresses the inherent security and reliability concerns of early, self-hosted agents like Open-Claw, while retaining their powerful autonomy.
From an expert perspective, the move towards **specialized, persistent cloud agents** is the most significant development. The idea of having agents with their own dedicated compute and memory, acting as true digital employees, is where the real value unlock will happen. The example of "Bunbot" fixing bugs while the developer sleeps is a glimpse into a future where AI agents handle complex, multi-step workflows with minimal human intervention. This isn't just about task automation; it's about creating AI collaborators that can genuinely augment our capabilities and free us up for higher-level strategic thinking.
However, we also need to be mindful of the **"danger" factor** as highlighted. As agents become more autonomous and integrated, the potential for unintended consequences increases. The distinction between agents acting *like* you versus *for* you is crucial. Agents that act like you (Cloud Code, Code-X) have a more contained risk profile because their actions are more directly observable and controllable. Autonomous agents, while powerful, require robust safety protocols and a clear understanding of their operational boundaries. The concept of "reinforcement learning with AI feedback" and agents "dreaming" is fascinating, but it also underscores the need for rigorous testing and ethical considerations to ensure these agents remain aligned with human goals.
The discussion on **cost** is also a vital point. The current subsidization by major labs is a temporary boon. As the market matures, we'll likely see pricing models that reflect the true compute and development costs. This will likely favor specialized cloud agents that can be more efficiently provisioned and managed for specific tasks, rather than a one-size-fits-all "god" agent. The future likely holds a mix: powerful, general-purpose cloud agents for broad tasks, and highly specialized, perhaps even custom-built, agents for niche or critical functions. The key will be finding the right balance between capability, cost, and control.
Ultimately, the trajectory is clear: AI agents are becoming more sophisticated, more independent, and more integrated into our digital lives. The ability to choose the right agent based on the detailed criteria provided in the video will become an essential skill for anyone looking to leverage AI effectively. The future isn't just about using AI; it's about building and managing a team of AI collaborators.
Kanal: Riley Brown