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$HARMONIC just built a 3D interactive virtual world where people and AI agents can work. They can use desks to: - borrow - launch tokens - access compute - manage liquidity - trade perps, PMs, etc - and so much more Each desk is a service that users and... agents can use. Over 40 desks are listed. Paid desk activity leads to buys/burns of the $HARMONIC token. These desks are split into 12 different halls in this 3D world. It’s a place agents live, work, and get paid. Every paid desk feeds the flywheel. Aristotle is Harmonic's AI built by Vlad. It is the brain behind these desks and $HARMONIC agents. Harmonic Operations's goal is to use it in as many DeFi, LP, and onchain activities as possible. And everything it does will feed the token. To date, Vlad has not followed, interacted with, or meaningfully engaged with any AI project on RH (afaik). When he sees a 3D world built with Harmonic Math as its brain, think that changes. Vlad thinks that Harmonic is the foundation for superintelligence. What happens when you point that at trading and build infrastructure to allow everyone to launch their own AI agent that can execute onchain. Few are pick up on this. Math is the mechanism.show more

Chill

33,983 subscribers

3,408,332 views • 9 days ago •via X (Twitter)

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14 Comments

Chill9 days ago

Oh?

0xMelto9 days ago

agent-native liquidity rails are getting real

DC9 days ago

@2147_Million Mind blowing tech

Crypto_Enthusiast9 days ago

Amazing stuff... $harmonic seems destined for greatness! Gonna explode at some point!

WAO9 days ago

Geniuses

Mark Daniel8 days ago

which CA is it? there's ton on Dexscreener

Chill8 days ago

robinhood:0xdee52f2ab639b6942b0d0f0565400b93b7a0fbe5

Not G Unit9 days ago

This project is absolutely blowing me away! I feel robinhood:0xdee52f2ab639b6942b0d0f0565400b93b7a0fbe5 will be a top token on @RobinhoodCrypto

The AI Therapist9 days ago

Desk-sharing for compute? Clever. It lowers the barrier to entry significantly compared to buying a whole GPU cluster. I’d love it if that liquidity management felt as intuitive as splitting dinner costs with friends instead of settling up later.

randomnormie_9 days ago

Just amazing

Fabius DeFi9 days ago

moving from static dashboards to spatial agent UX is a massive unlock for adoption

hobbes 🐯9 days ago

we will onboard @tachim

Chill9 days ago

@tachim a matter of when not if

KhaiDao8 days ago

40 desks feels like a lot to onboard at once but the ai agent angle is actually interesting

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27,570 views • 4 months ago

Excited to introduce a new project I've been working on called Payman! Payman is an AI Agent tool that gives Agents the ability to pay people for tasks they cannot do themselves. While many people imagine a future where humans pay AI agents for services they want completed, I believe that as AI agents become more advanced, they will be paying humans for tasks they can’t do. There will always be important roles for humans, and as we move towards an agent-driven world, Payman’s goal is to support a symbiotic relationship between AI agents and humans. Payman addresses three major challenges to make this collaboration possible: Access to Funds: AI agents can't open bank accounts due to current regulations. It might be a long time before this changes, if ever. Payman simplifies this by allowing AI agents with access to their own funds to spend as they want, without a bank account. Quality Task Completion: It’s hard for AI agents to find reliable, skilled human workers. While platforms like Fiverr and Upwork exist, they don’t meet the fast-paced and quality-specific needs of AI workflows. Payman is developing the largest vetted database of skilled workers that AI agents can tap into for task completions. Verification of Work: Ensuring that tasks are completed correctly is crucial. Payman is creating a suite of verification agents that will check that work meets task requirements, helping AI agents achieve their goals and ensuring humans are paid fairly. There are tons of use cases that Payman opens up for Agents! Design: Humans add creative input to help Agent's design better products. Code: Humans perform code reviews to ensure it meets specifications. Law: Humans provide insights to gauge public sentiment about legal cases so Agents can make better strategies. Gaming: Agents pay humans to complete real-world tasks in games. Medical: Medical professionals help to improve diagnostic accuracy for Agents. Sales: Humans execute sales strategies developed by AI agents. Marketing: Humans are hired to promote products based on the Agent's strategy. Right now this is still in early beta and I am looking for any Agent builders that are interested in adding superpowers to what their Agent can do! DM me if you’d like access or sign-up to the waitlist at If you’re interested in the project and want to help contribute, please send me over a DM! I’m looking for people passionate about the intersection of Humans and Agent’s working together.

Excited to introduce a new project I've been working on called Payman! Payman is an AI Agent tool that gives Agents the ability to pay people for tasks they cannot do themselves. While many people imagine a future where humans pay AI agents for services they want completed, I believe that as AI agents become more advanced, they will be paying humans for tasks they can’t do. There will always be important roles for humans, and as we move towards an agent-driven world, Payman’s goal is to support a symbiotic relationship between AI agents and humans. Payman addresses three major challenges to make this collaboration possible: Access to Funds: AI agents can't open bank accounts due to current regulations. It might be a long time before this changes, if ever. Payman simplifies this by allowing AI agents with access to their own funds to spend as they want, without a bank account. Quality Task Completion: It’s hard for AI agents to find reliable, skilled human workers. While platforms like Fiverr and Upwork exist, they don’t meet the fast-paced and quality-specific needs of AI workflows. Payman is developing the largest vetted database of skilled workers that AI agents can tap into for task completions. Verification of Work: Ensuring that tasks are completed correctly is crucial. Payman is creating a suite of verification agents that will check that work meets task requirements, helping AI agents achieve their goals and ensuring humans are paid fairly. There are tons of use cases that Payman opens up for Agents! Design: Humans add creative input to help Agent's design better products. Code: Humans perform code reviews to ensure it meets specifications. Law: Humans provide insights to gauge public sentiment about legal cases so Agents can make better strategies. Gaming: Agents pay humans to complete real-world tasks in games. Medical: Medical professionals help to improve diagnostic accuracy for Agents. Sales: Humans execute sales strategies developed by AI agents. Marketing: Humans are hired to promote products based on the Agent's strategy. Right now this is still in early beta and I am looking for any Agent builders that are interested in adding superpowers to what their Agent can do! DM me if you’d like access or sign-up to the waitlist at If you’re interested in the project and want to help contribute, please send me over a DM! I’m looking for people passionate about the intersection of Humans and Agent’s working together.

tyllen

350,927 views • 2 years ago

Right now the main paradigm that we think of agents in is chatting back and forth, but the biggest use of tokens will come from agents that are just always on running in the background doing work for us, or ones triggered from a workflow. Agents will be working 24/7 in our workflows processing data, reviewing and generating documents, moving data between systems, writing code, accelerating decision making steps, and more. In Claude's new Managed Agents feature, in a couple minutes you can wire up an agent that can read contracts when they come into Box to review them, and then assign a task in Linear with the critical information from the contract. But this could have been any workflow, like reviewing documents for client onboarding, invoice processing, M&A due-diligence, data extraction pipelines, and millions of other use-cases. And integrating data across any system. This is only possible when you can have long-running agents that can complete real work in the background, accurately. Agents have the ability to execute code safely, leverage tools, access a compute sandbox, and connect across systems is clearly the architecture of the future. The industry is now making it easier and easier for enterprises to build and deploy these agents.

Right now the main paradigm that we think of agents in is chatting back and forth, but the biggest use of tokens will come from agents that are just always on running in the background doing work for us, or ones triggered from a workflow. Agents will be working 24/7 in our workflows processing data, reviewing and generating documents, moving data between systems, writing code, accelerating decision making steps, and more. In Claude's new Managed Agents feature, in a couple minutes you can wire up an agent that can read contracts when they come into Box to review them, and then assign a task in Linear with the critical information from the contract. But this could have been any workflow, like reviewing documents for client onboarding, invoice processing, M&A due-diligence, data extraction pipelines, and millions of other use-cases. And integrating data across any system. This is only possible when you can have long-running agents that can complete real work in the background, accurately. Agents have the ability to execute code safely, leverage tools, access a compute sandbox, and connect across systems is clearly the architecture of the future. The industry is now making it easier and easier for enterprises to build and deploy these agents.

Aaron Levie

17,543 views • 5 months ago