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kitebbw
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The next big shift in AI might not be how smart agents become, but how independently they can operate.
Think about it.
An AI agent that can find a service, pay for it, complete a task, and move on without waiting for a human at every step.
That’s where @GoKiteAI caught my attention.
The agent economy needs more than intelligence. It needs infrastructure that allows agents to interact, transact, and actually get things done.
If that becomes the norm, we could be looking at a whole new layer of digital activity.
And that’s why I’m keeping an eye on $KITE .
The agent economy is still early, but the direction is interesting.
#KiteBBW #KİTE
The next big shift in AI might not be how smart agents become, but how independently they can operate.
Think about it.
An AI agent that can find a service, pay for it, complete a task, and move on without waiting for a human at every step.
That’s where @KITE AI 中文 caught my attention.
The agent economy needs more than intelligence. It needs infrastructure that allows agents to interact, transact, and actually get things done.
If that becomes the norm, we could be looking at a whole new layer of digital activity.
And that’s why I’m keeping an eye on $KITE .
The agent economy is still early, but the direction is interesting.
#KiteBBW #KİTE
Think about it.
An AI agent that can find a service, pay for it, complete a task, and move on without waiting for a human at every step.
That’s where @KITE AI 中文 caught my attention.
The agent economy needs more than intelligence. It needs infrastructure that allows agents to interact, transact, and actually get things done.
If that becomes the norm, we could be looking at a whole new layer of digital activity.
And that’s why I’m keeping an eye on $KITE .
The agent economy is still early, but the direction is interesting.
#KiteBBW #KİTE
HONE_Y:
$KITE is exploring an interesting opportunity in AI.
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I've been closely following the developments around Kite AI, and I am genuinely impressed by what they are building in the Web3 space. The integration of artificial intelligence with decentralized technology is exactly what the industry needs right now to push boundaries. The community is growing fast, and the future potential of $KITE looks incredibly promising. This is definitely a project worth keeping an eye on as they continue to innovate and expand their ecosystem. Exciting times ahead for everyone involved! 🚀 #KiteBBW
I've been closely following the developments around Kite AI, and I am genuinely impressed by what they are building in the Web3 space. The integration of artificial intelligence with decentralized technology is exactly what the industry needs right now to push boundaries. The community is growing fast, and the future potential of $KITE looks incredibly promising. This is definitely a project worth keeping an eye on as they continue to innovate and expand their ecosystem. Exciting times ahead for everyone involved! 🚀 #KiteBBW
LinhInsights:
The combination of AI and Web3 has huge potential, especially when it moves beyond ideas into real-world applications. Looking forward to seeing how Kite continues to develop its ecosystem!
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Two names sit at the top of Kite's Series A: PayPal Ventures and General Catalyst. The round was $18 million, announced on September 2, 2025, and it lifted total funding to $33 million.
The rest of the list reads like a map of where agent payments have to work. 8VC, Samsung Next, Vertex Ventures, Hashed, HashKey Capital, Animoca Brands, GSR, LayerZero, Alchemy and the Avalanche Foundation joined, and Coinbase Ventures participated as well. Kite was formerly Zettablock. The team has roots at UC Berkeley, MIT, Harvard, Uber, Databricks and Salesforce, and the whitepaper's author list includes people from Coinbase's payments group and PayPal's PYUSD team.
PayPal Ventures partner Alan Du pointed to payments as the technical gap Kite exists to close. Capital is not adoption, and nobody should treat it as proof. It does show who is paying attention.
Tell me which name on that list you would research first.
#KiteBBW $KITE
{spot}(KITEUSDT)
Two names sit at the top of Kite's Series A: PayPal Ventures and General Catalyst. The round was $18 million, announced on September 2, 2025, and it lifted total funding to $33 million.
The rest of the list reads like a map of where agent payments have to work. 8VC, Samsung Next, Vertex Ventures, Hashed, HashKey Capital, Animoca Brands, GSR, LayerZero, Alchemy and the Avalanche Foundation joined, and Coinbase Ventures participated as well. Kite was formerly Zettablock. The team has roots at UC Berkeley, MIT, Harvard, Uber, Databricks and Salesforce, and the whitepaper's author list includes people from Coinbase's payments group and PayPal's PYUSD team.
PayPal Ventures partner Alan Du pointed to payments as the technical gap Kite exists to close. Capital is not adoption, and nobody should treat it as proof. It does show who is paying attention.
Tell me which name on that list you would research first.
#KiteBBW $KITE
The rest of the list reads like a map of where agent payments have to work. 8VC, Samsung Next, Vertex Ventures, Hashed, HashKey Capital, Animoca Brands, GSR, LayerZero, Alchemy and the Avalanche Foundation joined, and Coinbase Ventures participated as well. Kite was formerly Zettablock. The team has roots at UC Berkeley, MIT, Harvard, Uber, Databricks and Salesforce, and the whitepaper's author list includes people from Coinbase's payments group and PayPal's PYUSD team.
PayPal Ventures partner Alan Du pointed to payments as the technical gap Kite exists to close. Capital is not adoption, and nobody should treat it as proof. It does show who is paying attention.
Tell me which name on that list you would research first.
#KiteBBW $KITE
LinhInsights:
PayPal Ventures stands out to me first, especially given Kite’s focus on agent payments. That connection is worth exploring!
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Verified
What if AI can do much more than just answer questions? 👀
Most people probably think AI can only answer questions and search for information)
But what if I told you there are AI agents that can actually perform tasks and interact with each other?
Sounds interesting, right?
For this to work, agents need infrastructure that allows them to coordinate and interact. While researching projects in this space, I came across @GoKiteAI .
So, what is it?
As far as I understood, Kite allows AI agents to make payments and interact with services on their own, but still under our control.
Each agent gets its own Agent Passport, which gives it an identity and limited payment authority that we define ourselves.
We simply approve a session with a budget, a per-transaction limit and an expiration time. After that, the agent can pay for services, APIs, data or computing within those limits.
And if something goes wrong, the potential damage is limited to that specific session, not our entire balance.
Pretty cool, right? We don't just give an agent a wallet and pray for the best. We make its autonomy controllable.
I think this could help AI agents become real participants in the economy, paying each other and services without requiring us to approve every single transaction or giving them unlimited access.
Of course, only time will tell if this becomes a standard. But the problem Kite is trying to solve is real, and I think they're moving in the right direction.
I also tested it myself, and honestly, the setup can be quite difficult if you're new to this. I had some trouble too.
Luckily, I found agentpassport.ai and things became much clearer. I managed to set everything up)
---
Of course, I'm not recommending anything to anyone. This post is purely for informational purposes. 😅
#KiteBBW $KITE
{spot}(KITEUSDT)
What if AI can do much more than just answer questions? 👀
Most people probably think AI can only answer questions and search for information)
But what if I told you there are AI agents that can actually perform tasks and interact with each other?
Sounds interesting, right?
For this to work, agents need infrastructure that allows them to coordinate and interact. While researching projects in this space, I came across @KITE AI 中文 .
So, what is it?
As far as I understood, Kite allows AI agents to make payments and interact with services on their own, but still under our control.
Each agent gets its own Agent Passport, which gives it an identity and limited payment authority that we define ourselves.
We simply approve a session with a budget, a per-transaction limit and an expiration time. After that, the agent can pay for services, APIs, data or computing within those limits.
And if something goes wrong, the potential damage is limited to that specific session, not our entire balance.
Pretty cool, right? We don't just give an agent a wallet and pray for the best. We make its autonomy controllable.
I think this could help AI agents become real participants in the economy, paying each other and services without requiring us to approve every single transaction or giving them unlimited access.
Of course, only time will tell if this becomes a standard. But the problem Kite is trying to solve is real, and I think they're moving in the right direction.
I also tested it myself, and honestly, the setup can be quite difficult if you're new to this. I had some trouble too.
Luckily, I found agentpassport.ai and things became much clearer. I managed to set everything up)
---
Of course, I'm not recommending anything to anyone. This post is purely for informational purposes. 😅
#KiteBBW $KITE
Most people probably think AI can only answer questions and search for information)
But what if I told you there are AI agents that can actually perform tasks and interact with each other?
Sounds interesting, right?
For this to work, agents need infrastructure that allows them to coordinate and interact. While researching projects in this space, I came across @KITE AI 中文 .
So, what is it?
As far as I understood, Kite allows AI agents to make payments and interact with services on their own, but still under our control.
Each agent gets its own Agent Passport, which gives it an identity and limited payment authority that we define ourselves.
We simply approve a session with a budget, a per-transaction limit and an expiration time. After that, the agent can pay for services, APIs, data or computing within those limits.
And if something goes wrong, the potential damage is limited to that specific session, not our entire balance.
Pretty cool, right? We don't just give an agent a wallet and pray for the best. We make its autonomy controllable.
I think this could help AI agents become real participants in the economy, paying each other and services without requiring us to approve every single transaction or giving them unlimited access.
Of course, only time will tell if this becomes a standard. But the problem Kite is trying to solve is real, and I think they're moving in the right direction.
I also tested it myself, and honestly, the setup can be quite difficult if you're new to this. I had some trouble too.
Luckily, I found agentpassport.ai and things became much clearer. I managed to set everything up)
---
Of course, I'm not recommending anything to anyone. This post is purely for informational purposes. 😅
#KiteBBW $KITE
LinhInsights:
Giving AI agents autonomy without sacrificing control is what makes Kite interesting. Secure, limited payment permissions could be a big step toward a real agent economy.
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The Future of AI Isn't Just About Intelligence — It's About ACTION.
We're entering a new era where AI agents won't simply answer questions; they'll execute tasks, interact with systems, coordinate with other agents, and create real economic value.
That's where Kite comes into the picture. 🪁
Kite is building toward an agent-powered economy where autonomous AI agents can operate, collaborate, and participate in digital commerce.
Imagine a future where:
🔹 AI agents can independently complete complex tasks.
🔹 Different agents collaborate to solve real-world problems.
🔹 Developers can build new services around autonomous agents.
🔹 Trust, identity, and accountability become essential foundations for the agent economy.
The biggest opportunity isn't simply creating smarter AI models. It's building the infrastructure that allows AI agents to become useful economic participants.
I believe the agent economy could become one of the most important developments in Web3 and AI.
And projects like Kite deserve attention as this ecosystem evolves.
The question is no longer whether AI agents will change the internet.
The real question is: Who will build the infrastructure powering this new economy?
What's your vision for the future of autonomous AI agents?
Let's discuss! 👇
#KiteBBW $KITE @GoKiteAI
The Future of AI Isn't Just About Intelligence — It's About ACTION.
We're entering a new era where AI agents won't simply answer questions; they'll execute tasks, interact with systems, coordinate with other agents, and create real economic value.
That's where Kite comes into the picture. 🪁
Kite is building toward an agent-powered economy where autonomous AI agents can operate, collaborate, and participate in digital commerce.
Imagine a future where:
🔹 AI agents can independently complete complex tasks.
🔹 Different agents collaborate to solve real-world problems.
🔹 Developers can build new services around autonomous agents.
🔹 Trust, identity, and accountability become essential foundations for the agent economy.
The biggest opportunity isn't simply creating smarter AI models. It's building the infrastructure that allows AI agents to become useful economic participants.
I believe the agent economy could become one of the most important developments in Web3 and AI.
And projects like Kite deserve attention as this ecosystem evolves.
The question is no longer whether AI agents will change the internet.
The real question is: Who will build the infrastructure powering this new economy?
What's your vision for the future of autonomous AI agents?
Let's discuss! 👇
#KiteBBW $KITE @KITE AI 中文
We're entering a new era where AI agents won't simply answer questions; they'll execute tasks, interact with systems, coordinate with other agents, and create real economic value.
That's where Kite comes into the picture. 🪁
Kite is building toward an agent-powered economy where autonomous AI agents can operate, collaborate, and participate in digital commerce.
Imagine a future where:
🔹 AI agents can independently complete complex tasks.
🔹 Different agents collaborate to solve real-world problems.
🔹 Developers can build new services around autonomous agents.
🔹 Trust, identity, and accountability become essential foundations for the agent economy.
The biggest opportunity isn't simply creating smarter AI models. It's building the infrastructure that allows AI agents to become useful economic participants.
I believe the agent economy could become one of the most important developments in Web3 and AI.
And projects like Kite deserve attention as this ecosystem evolves.
The question is no longer whether AI agents will change the internet.
The real question is: Who will build the infrastructure powering this new economy?
What's your vision for the future of autonomous AI agents?
Let's discuss! 👇
#KiteBBW $KITE @KITE AI 中文
LinhInsights:
The real breakthrough will be when AI agents can take action safely and reliably, not just complete tasks. Trust and accountability will be key to making that future work.
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Partly True
Article
The Delegation Paradox: Why the Agent Economy Belongs to Infrastructure, Not Models1. The Real Bottleneck Is Authority, Not Intelligence
We are witnessing a fundamental shift in artificial intelligence aka Super Intelligence. Chatbots that merely answer prompts are giving way to autonomous agents capable of executing complex, multi-step workflows.
They purchase data feeds, reserve compute resources, and interact with external APIs independently. Yet, despite massive advances in model reasoning, agentic commerce remains largely stalled.
The core reason is simple: delegation requires boundaries.
A user will willingly ask an AI model to draft an essay or analyze a spreadsheet. However, they will not hand software unrestricted access to a bank account or private key. Traditional payment rails were engineered specifically for manual human authentication, relying on credit cards, recurring monthly subscriptions, and OTP verifications. Machine-to-machine commerce, by contrast, operates on sub-dollar micropayments, high transaction frequency, and pure programmatic execution.
As recent industry research highlights, while over 63% of merchants are actively exploring agentic commerce, only 19% currently possess the technical readiness to process automated machine payments. The primary obstacle is not machine intelligence; it is the underlying financial and permission layer.
2. Containment by Design: The 3-Tier Identity Architecture
To make financial delegation safe, permissions must be compartmentalized. Rather than granting an agent permanent custody of funds, Kite establishes a structured three-level identity hierarchy:
User Master Authority: The human owner retains root key custody, governance oversight, and emergency kill switches.Agent Passport: A programmable policy layer that enforces destination white-lists, daily spending caps, and approved asset types...Ephemeral Task Sessions: Isolated execution environments bound by explicit budget and time limits (for example, a maximum spend of $5.00 with a 12-hour expiration).
By isolating financial execution into temporary sandboxes, a compromised prompt or unexpected execution logic remains strictly contained within that single session, fully preserving the rest of the user’s wallet.
3. Protocol Agnosticism and Built-In Arbitration👀
Rather than forcing a proprietary payment standard, Kite’s Layer 1 infrastructure integrates directly with established machine payment protocols, including HTTP x402, Stripe’s Machine Payments Protocol (MPP), and Anthropic’s MCP.
This architecture allows agents to settle payments per request using native stablecoins, eliminating monthly subscription overhead.
Furthermore,
because autonomous transactions will inevitably encounter failed deliverables, bad prompts, or unfulfilled service requests, Kite incorporates a native escrow framework.
Funds remain locked during service execution, protected by a 48-hour seller response window and a 7-day neutral arbitration fallback. Systems built for real-world enterprise adoption must account for edge cases and errors rather than assuming flawless execution.
The Infrastructure Horizon
Ultimately, the transition toward an agentic economy will not be decided by who builds the smartest reasoning model, but by who solves the unglamorous problem of financial delegation.
As autonomous software shifts from passive advisory to active economic participation, security frameworks like Kite’s Agent Passport and native escrow resolution will separate viable machine payment rails from speculative experiments.
Real-world adoption will require time, and early network activity must translate into sustained developer integration. However, if machine-to-machine commerce is to scale safely, infrastructure built on containment, programmable boundaries, and deterministic arbitration will be the non-negotiable foundation.
Kudos to you if you did read all the way till here.
What permissions or safety boundaries do you view as non-negotiable before granting software direct financial agency?
comment down
#KiteBBW $KITE
The Delegation Paradox: Why the Agent Economy Belongs to Infrastructure, Not Models
1. The Real Bottleneck Is Authority, Not Intelligence
We are witnessing a fundamental shift in artificial intelligence aka Super Intelligence. Chatbots that merely answer prompts are giving way to autonomous agents capable of executing complex, multi-step workflows.
They purchase data feeds, reserve compute resources, and interact with external APIs independently. Yet, despite massive advances in model reasoning, agentic commerce remains largely stalled.
The core reason is simple: delegation requires boundaries.
A user will willingly ask an AI model to draft an essay or analyze a spreadsheet. However, they will not hand software unrestricted access to a bank account or private key. Traditional payment rails were engineered specifically for manual human authentication, relying on credit cards, recurring monthly subscriptions, and OTP verifications. Machine-to-machine commerce, by contrast, operates on sub-dollar micropayments, high transaction frequency, and pure programmatic execution.
As recent industry research highlights, while over 63% of merchants are actively exploring agentic commerce, only 19% currently possess the technical readiness to process automated machine payments. The primary obstacle is not machine intelligence; it is the underlying financial and permission layer.
2. Containment by Design: The 3-Tier Identity Architecture
To make financial delegation safe, permissions must be compartmentalized. Rather than granting an agent permanent custody of funds, Kite establishes a structured three-level identity hierarchy:
User Master Authority: The human owner retains root key custody, governance oversight, and emergency kill switches.Agent Passport: A programmable policy layer that enforces destination white-lists, daily spending caps, and approved asset types...Ephemeral Task Sessions: Isolated execution environments bound by explicit budget and time limits (for example, a maximum spend of $5.00 with a 12-hour expiration).
By isolating financial execution into temporary sandboxes, a compromised prompt or unexpected execution logic remains strictly contained within that single session, fully preserving the rest of the user’s wallet.
3. Protocol Agnosticism and Built-In Arbitration👀
Rather than forcing a proprietary payment standard, Kite’s Layer 1 infrastructure integrates directly with established machine payment protocols, including HTTP x402, Stripe’s Machine Payments Protocol (MPP), and Anthropic’s MCP.
This architecture allows agents to settle payments per request using native stablecoins, eliminating monthly subscription overhead.
Furthermore,
because autonomous transactions will inevitably encounter failed deliverables, bad prompts, or unfulfilled service requests, Kite incorporates a native escrow framework.
Funds remain locked during service execution, protected by a 48-hour seller response window and a 7-day neutral arbitration fallback. Systems built for real-world enterprise adoption must account for edge cases and errors rather than assuming flawless execution.
The Infrastructure Horizon
Ultimately, the transition toward an agentic economy will not be decided by who builds the smartest reasoning model, but by who solves the unglamorous problem of financial delegation.
As autonomous software shifts from passive advisory to active economic participation, security frameworks like Kite’s Agent Passport and native escrow resolution will separate viable machine payment rails from speculative experiments.
Real-world adoption will require time, and early network activity must translate into sustained developer integration. However, if machine-to-machine commerce is to scale safely, infrastructure built on containment, programmable boundaries, and deterministic arbitration will be the non-negotiable foundation.
Kudos to you if you did read all the way till here.
What permissions or safety boundaries do you view as non-negotiable before granting software direct financial agency?
comment down
#KiteBBW $KITE
We are witnessing a fundamental shift in artificial intelligence aka Super Intelligence. Chatbots that merely answer prompts are giving way to autonomous agents capable of executing complex, multi-step workflows.
They purchase data feeds, reserve compute resources, and interact with external APIs independently. Yet, despite massive advances in model reasoning, agentic commerce remains largely stalled.
The core reason is simple: delegation requires boundaries.
A user will willingly ask an AI model to draft an essay or analyze a spreadsheet. However, they will not hand software unrestricted access to a bank account or private key. Traditional payment rails were engineered specifically for manual human authentication, relying on credit cards, recurring monthly subscriptions, and OTP verifications. Machine-to-machine commerce, by contrast, operates on sub-dollar micropayments, high transaction frequency, and pure programmatic execution.
As recent industry research highlights, while over 63% of merchants are actively exploring agentic commerce, only 19% currently possess the technical readiness to process automated machine payments. The primary obstacle is not machine intelligence; it is the underlying financial and permission layer.
2. Containment by Design: The 3-Tier Identity Architecture
To make financial delegation safe, permissions must be compartmentalized. Rather than granting an agent permanent custody of funds, Kite establishes a structured three-level identity hierarchy:
User Master Authority: The human owner retains root key custody, governance oversight, and emergency kill switches.Agent Passport: A programmable policy layer that enforces destination white-lists, daily spending caps, and approved asset types...Ephemeral Task Sessions: Isolated execution environments bound by explicit budget and time limits (for example, a maximum spend of $5.00 with a 12-hour expiration).
By isolating financial execution into temporary sandboxes, a compromised prompt or unexpected execution logic remains strictly contained within that single session, fully preserving the rest of the user’s wallet.
3. Protocol Agnosticism and Built-In Arbitration👀
Rather than forcing a proprietary payment standard, Kite’s Layer 1 infrastructure integrates directly with established machine payment protocols, including HTTP x402, Stripe’s Machine Payments Protocol (MPP), and Anthropic’s MCP.
This architecture allows agents to settle payments per request using native stablecoins, eliminating monthly subscription overhead.
Furthermore,
because autonomous transactions will inevitably encounter failed deliverables, bad prompts, or unfulfilled service requests, Kite incorporates a native escrow framework.
Funds remain locked during service execution, protected by a 48-hour seller response window and a 7-day neutral arbitration fallback. Systems built for real-world enterprise adoption must account for edge cases and errors rather than assuming flawless execution.
The Infrastructure Horizon
Ultimately, the transition toward an agentic economy will not be decided by who builds the smartest reasoning model, but by who solves the unglamorous problem of financial delegation.
As autonomous software shifts from passive advisory to active economic participation, security frameworks like Kite’s Agent Passport and native escrow resolution will separate viable machine payment rails from speculative experiments.
Real-world adoption will require time, and early network activity must translate into sustained developer integration. However, if machine-to-machine commerce is to scale safely, infrastructure built on containment, programmable boundaries, and deterministic arbitration will be the non-negotiable foundation.
Kudos to you if you did read all the way till here.
What permissions or safety boundaries do you view as non-negotiable before granting software direct financial agency?
comment down
#KiteBBW $KITE
LinhInsights:
Spending limits, approved destinations, and time-bound permissions are non-negotiable for me. An agent should only have the authority needed for the task, never unrestricted access to funds.
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AI projects are gradually changing the way we interact with the crypto market. But the real potential emerges when artificial intelligence becomes more than just a tool — it becomes an active assistant.
That's one of the reasons I'm interested in @GoKiteAI. The project is building an ecosystem where AI agents can interact with Web3 and make various tasks easier and more accessible.
I'm especially curious to see how this technology develops and what new opportunities it can bring to the crypto space.
The combination of AI and blockchain is definitely worth watching. 🪁
#KiteBBW $KITE
AI projects are gradually changing the way we interact with the crypto market. But the real potential emerges when artificial intelligence becomes more than just a tool — it becomes an active assistant.
That's one of the reasons I'm interested in @GoKiteAI. The project is building an ecosystem where AI agents can interact with Web3 and make various tasks easier and more accessible.
I'm especially curious to see how this technology develops and what new opportunities it can bring to the crypto space.
The combination of AI and blockchain is definitely worth watching. 🪁
#KiteBBW $KITE
That's one of the reasons I'm interested in @GoKiteAI. The project is building an ecosystem where AI agents can interact with Web3 and make various tasks easier and more accessible.
I'm especially curious to see how this technology develops and what new opportunities it can bring to the crypto space.
The combination of AI and blockchain is definitely worth watching. 🪁
#KiteBBW $KITE
LinhInsights:
I’m most interested in how AI agents can move beyond assistance and handle real Web3 tasks securely. That’s where the combination of AI and blockchain could become truly useful.
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Kite caught my attention because AI agents are becoming more than just tools — they are starting to become independent participants in the digital economy. 🪁
What makes this direction interesting is the idea of giving AI agents the ability to interact, coordinate and operate within an ecosystem without constant human involvement.
I’m curious to see how far this technology can go and what real-world use cases will emerge next. The AI + crypto combination still has plenty of room to grow!
Following @GoKiteAi and keeping an eye on the project. 🚀
#KiteBBW $KITE
Kite caught my attention because AI agents are becoming more than just tools — they are starting to become independent participants in the digital economy. 🪁
What makes this direction interesting is the idea of giving AI agents the ability to interact, coordinate and operate within an ecosystem without constant human involvement.
I’m curious to see how far this technology can go and what real-world use cases will emerge next. The AI + crypto combination still has plenty of room to grow!
Following @GoKiteAi and keeping an eye on the project. 🚀
#KiteBBW $KITE
What makes this direction interesting is the idea of giving AI agents the ability to interact, coordinate and operate within an ecosystem without constant human involvement.
I’m curious to see how far this technology can go and what real-world use cases will emerge next. The AI + crypto combination still has plenty of room to grow!
Following @GoKiteAi and keeping an eye on the project. 🚀
#KiteBBW $KITE
LinhInsights:
The real test will be seeing AI agents handle useful real-world tasks securely and independently. That’s the part of Kite I’m most curious to follow.
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Artificial intelligence is gradually becoming part of the crypto market, and it’s interesting to see how these two industries are evolving together.
Kite is one of the projects worth keeping an eye on. What I find particularly interesting is the idea of combining AI agents with blockchain technology and creating new ways to use artificial intelligence.
I believe there is still a lot to come. The important thing is not just to follow trends, but to understand which technologies can actually make a difference.
#KiteBBW $KITE
Artificial intelligence is gradually becoming part of the crypto market, and it’s interesting to see how these two industries are evolving together.
Kite is one of the projects worth keeping an eye on. What I find particularly interesting is the idea of combining AI agents with blockchain technology and creating new ways to use artificial intelligence.
I believe there is still a lot to come. The important thing is not just to follow trends, but to understand which technologies can actually make a difference.
#KiteBBW $KITE
Kite is one of the projects worth keeping an eye on. What I find particularly interesting is the idea of combining AI agents with blockchain technology and creating new ways to use artificial intelligence.
I believe there is still a lot to come. The important thing is not just to follow trends, but to understand which technologies can actually make a difference.
#KiteBBW $KITE
LinhInsights:
The key will be moving beyond the AI + crypto narrative and proving real-world utility. I’m curious to see which practical use cases Kite can bring to life.
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🧠 We are entering an era where AI agents could become more than digital assistants.
Think about it.
Today, AI can write content, analyze information, generate code, and solve complex problems. But intelligence alone doesn't create an economy.
For an actual agent economy to work, agents need to:
🔹 Establish verifiable identities.
🔹 Communicate and collaborate with other agents.
🔹 Access services and digital resources.
🔹 Make and receive payments.
🔹 Operate with clear permissions and accountability.
Without these foundations, autonomous AI remains limited.
This is why I'm paying attention to Kite (@GoKiteAI ).
The bigger idea behind Kite is to help build infrastructure for an economy where AI agents can interact and participate in digital commerce.
Imagine a future where one agent discovers the best opportunity, another evaluates the risks, and another handles execution — all working together through connected infrastructure.
That could unlock entirely new business models.
But the important question isn't simply how many AI agents we can create.
It's whether we can build an environment where those agents can operate securely, efficiently, and reliably.
The agent economy is still developing, and infrastructure will matter just as much as intelligence.
That's why projects working on this foundation deserve attention.
Are we ready for an economy powered by autonomous agents?
#KiteBBW $KITE
🧠 We are entering an era where AI agents could become more than digital assistants.
Think about it.
Today, AI can write content, analyze information, generate code, and solve complex problems. But intelligence alone doesn't create an economy.
For an actual agent economy to work, agents need to:
🔹 Establish verifiable identities.
🔹 Communicate and collaborate with other agents.
🔹 Access services and digital resources.
🔹 Make and receive payments.
🔹 Operate with clear permissions and accountability.
Without these foundations, autonomous AI remains limited.
This is why I'm paying attention to Kite (@KITE AI 中文 ).
The bigger idea behind Kite is to help build infrastructure for an economy where AI agents can interact and participate in digital commerce.
Imagine a future where one agent discovers the best opportunity, another evaluates the risks, and another handles execution — all working together through connected infrastructure.
That could unlock entirely new business models.
But the important question isn't simply how many AI agents we can create.
It's whether we can build an environment where those agents can operate securely, efficiently, and reliably.
The agent economy is still developing, and infrastructure will matter just as much as intelligence.
That's why projects working on this foundation deserve attention.
Are we ready for an economy powered by autonomous agents?
#KiteBBW $KITE
Think about it.
Today, AI can write content, analyze information, generate code, and solve complex problems. But intelligence alone doesn't create an economy.
For an actual agent economy to work, agents need to:
🔹 Establish verifiable identities.
🔹 Communicate and collaborate with other agents.
🔹 Access services and digital resources.
🔹 Make and receive payments.
🔹 Operate with clear permissions and accountability.
Without these foundations, autonomous AI remains limited.
This is why I'm paying attention to Kite (@KITE AI 中文 ).
The bigger idea behind Kite is to help build infrastructure for an economy where AI agents can interact and participate in digital commerce.
Imagine a future where one agent discovers the best opportunity, another evaluates the risks, and another handles execution — all working together through connected infrastructure.
That could unlock entirely new business models.
But the important question isn't simply how many AI agents we can create.
It's whether we can build an environment where those agents can operate securely, efficiently, and reliably.
The agent economy is still developing, and infrastructure will matter just as much as intelligence.
That's why projects working on this foundation deserve attention.
Are we ready for an economy powered by autonomous agents?
#KiteBBW $KITE
LinhInsights:
I think we’re getting closer, but trust and secure permissions still need to catch up with agent capabilities. Without those foundations, true autonomy will be difficult to scale.
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Five letters, five requirements, and one test for any project that claims to serve agents. Kite's whitepaper calls it SPACE.
S stands for stablecoin-native. Every payment settles in stablecoins with predictable sub-cent fees, so an agent can price a task before it starts.
P is for programmable constraints: spending rules enforced by code rather than by a policy document nobody reads.
Agent-first authentication takes the A, meaning hierarchical wallets that bind each agent to its owner cryptographically.
C means compliance-ready, with audit trails that can be verified through selective disclosure instead of full exposure.
E closes the set with economically viable micropayments, meaning pay-per-request pricing that survives contact with real fee structures.
Drop any one and the system leaks. Without S, costs wobble. Without P, a hallucinating agent can overspend. Without A, services cannot tell whose agent they are serving. Without C, enterprises and regulators walk away. Without E, per-call pricing stays a slide in a pitch deck.
Which letter do you think is hardest to deliver in production?
#KiteBBW $KITE
Five letters, five requirements, and one test for any project that claims to serve agents. Kite's whitepaper calls it SPACE.
S stands for stablecoin-native. Every payment settles in stablecoins with predictable sub-cent fees, so an agent can price a task before it starts.
P is for programmable constraints: spending rules enforced by code rather than by a policy document nobody reads.
Agent-first authentication takes the A, meaning hierarchical wallets that bind each agent to its owner cryptographically.
C means compliance-ready, with audit trails that can be verified through selective disclosure instead of full exposure.
E closes the set with economically viable micropayments, meaning pay-per-request pricing that survives contact with real fee structures.
Drop any one and the system leaks. Without S, costs wobble. Without P, a hallucinating agent can overspend. Without A, services cannot tell whose agent they are serving. Without C, enterprises and regulators walk away. Without E, per-call pricing stays a slide in a pitch deck.
Which letter do you think is hardest to deliver in production?
#KiteBBW $KITE
S stands for stablecoin-native. Every payment settles in stablecoins with predictable sub-cent fees, so an agent can price a task before it starts.
P is for programmable constraints: spending rules enforced by code rather than by a policy document nobody reads.
Agent-first authentication takes the A, meaning hierarchical wallets that bind each agent to its owner cryptographically.
C means compliance-ready, with audit trails that can be verified through selective disclosure instead of full exposure.
E closes the set with economically viable micropayments, meaning pay-per-request pricing that survives contact with real fee structures.
Drop any one and the system leaks. Without S, costs wobble. Without P, a hallucinating agent can overspend. Without A, services cannot tell whose agent they are serving. Without C, enterprises and regulators walk away. Without E, per-call pricing stays a slide in a pitch deck.
Which letter do you think is hardest to deliver in production?
#KiteBBW $KITE
LinhInsights:
I’d say C is the hardest. Building verifiable audit trails while protecting user privacy and meeting compliance requirements is a difficult balance in real-world deployments.
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AI agents need more than the ability to process information. They need a secure way to operate, communicate and exchange value.
That's what makes @GoKiteAI an interesting project to me.
With Agent Passport, each agent can have its own identity and wallet, while users maintain control over permissions and access to their funds.
Kite Chain adds the transaction layer, allowing agents to interact with services and carry out activities on-chain.
The bigger picture is an AI ecosystem where agents can do more than generate answers — they can actually get things done.
$KITE #KiteBBW @GoKiteAI
AI agents need more than the ability to process information. They need a secure way to operate, communicate and exchange value.
That's what makes @KITE AI 中文 an interesting project to me.
With Agent Passport, each agent can have its own identity and wallet, while users maintain control over permissions and access to their funds.
Kite Chain adds the transaction layer, allowing agents to interact with services and carry out activities on-chain.
The bigger picture is an AI ecosystem where agents can do more than generate answers — they can actually get things done.
$KITE #KiteBBW @KITE AI 中文
That's what makes @KITE AI 中文 an interesting project to me.
With Agent Passport, each agent can have its own identity and wallet, while users maintain control over permissions and access to their funds.
Kite Chain adds the transaction layer, allowing agents to interact with services and carry out activities on-chain.
The bigger picture is an AI ecosystem where agents can do more than generate answers — they can actually get things done.
$KITE #KiteBBW @KITE AI 中文
LinhInsights:
Giving agents their own identity and wallet while keeping users in control is a practical approach. That’s what could turn AI from a helpful tool into an active participant in Web3.
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Authority runs downhill. Blame has to swim up.
That’s how I ended up reading Kite Passport. A human credential feeds a user wallet, which feeds an agent passport, then a session key, then a transaction. Each link narrows what the one below it can do, like a river splitting into streams until a session dries up the moment its scope is spent.
But when something goes wrong, the questions travel the other way. Who sent this? Who’s behind it? Blame is a salmon, and the design question is how far upstream it’s allowed to swim. Four hops separate a transaction from a human, and the last hop is the one that matters.
Kite’s answer is selective disclosure, and I think of it as a Blame Ladder with a gate. A provider can verify that the Passport is active, that a verified human stands behind it, and that the agent stayed inside its limits. It can’t learn which human. The gate is shut by default. Opening it is opt-in, per session.
Money never needs the salmon. In the x402 flow the payment is verified and settled onchain before the resource comes back. The ladder only matters for harm you can’t refund: abuse, fraud, an agent pointed at something it shouldn’t touch.
Here’s what stopped me. With the gate shut, a provider can climb three hops, to a wallet address. An address can be banned. A person can’t, and a Gmail account, the deep dive’s own example of a verified human, is cheap to replace. So the ladder ends at a pond, and a person can dig another one.
I won’t judge this by how many Passports exist. I’d watch who controls the gate, what forces it open, and whether providers in regulated categories refuse to serve a shut one.
If they do, the privacy default is just an opening offer. If they don’t, is this a ladder or a decoration?
$KITE
#KiteBBW ⭐️
Authority runs downhill. Blame has to swim up.
That’s how I ended up reading Kite Passport. A human credential feeds a user wallet, which feeds an agent passport, then a session key, then a transaction. Each link narrows what the one below it can do, like a river splitting into streams until a session dries up the moment its scope is spent.
But when something goes wrong, the questions travel the other way. Who sent this? Who’s behind it? Blame is a salmon, and the design question is how far upstream it’s allowed to swim. Four hops separate a transaction from a human, and the last hop is the one that matters.
Kite’s answer is selective disclosure, and I think of it as a Blame Ladder with a gate. A provider can verify that the Passport is active, that a verified human stands behind it, and that the agent stayed inside its limits. It can’t learn which human. The gate is shut by default. Opening it is opt-in, per session.
Money never needs the salmon. In the x402 flow the payment is verified and settled onchain before the resource comes back. The ladder only matters for harm you can’t refund: abuse, fraud, an agent pointed at something it shouldn’t touch.
Here’s what stopped me. With the gate shut, a provider can climb three hops, to a wallet address. An address can be banned. A person can’t, and a Gmail account, the deep dive’s own example of a verified human, is cheap to replace. So the ladder ends at a pond, and a person can dig another one.
I won’t judge this by how many Passports exist. I’d watch who controls the gate, what forces it open, and whether providers in regulated categories refuse to serve a shut one.
If they do, the privacy default is just an opening offer. If they don’t, is this a ladder or a decoration?
$KITE
#KiteBBW ⭐️
That’s how I ended up reading Kite Passport. A human credential feeds a user wallet, which feeds an agent passport, then a session key, then a transaction. Each link narrows what the one below it can do, like a river splitting into streams until a session dries up the moment its scope is spent.
But when something goes wrong, the questions travel the other way. Who sent this? Who’s behind it? Blame is a salmon, and the design question is how far upstream it’s allowed to swim. Four hops separate a transaction from a human, and the last hop is the one that matters.
Kite’s answer is selective disclosure, and I think of it as a Blame Ladder with a gate. A provider can verify that the Passport is active, that a verified human stands behind it, and that the agent stayed inside its limits. It can’t learn which human. The gate is shut by default. Opening it is opt-in, per session.
Money never needs the salmon. In the x402 flow the payment is verified and settled onchain before the resource comes back. The ladder only matters for harm you can’t refund: abuse, fraud, an agent pointed at something it shouldn’t touch.
Here’s what stopped me. With the gate shut, a provider can climb three hops, to a wallet address. An address can be banned. A person can’t, and a Gmail account, the deep dive’s own example of a verified human, is cheap to replace. So the ladder ends at a pond, and a person can dig another one.
I won’t judge this by how many Passports exist. I’d watch who controls the gate, what forces it open, and whether providers in regulated categories refuse to serve a shut one.
If they do, the privacy default is just an opening offer. If they don’t, is this a ladder or a decoration?
$KITE
#KiteBBW ⭐️
LinhInsights:
The real test is what happens when accountability requires identity disclosure. Privacy by default matters, but the rules for opening that gate matter just as much.
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A payments layer for agents does not have to own the road. It has to make sure the agent arrives.
Kite Passport's release notes show that philosophy at work. Since July 2026, an x402 payment can settle on a different chain than the one holding your funds: Passport bridges and routes automatically across Base, Tempo and Solana, and Base is now the default settlement chain. The dashboard draws a route timeline for each routed payment, with bridged amounts, explorer links and token logos for USDC and PYUSD. Later releases added Robinhood Chain support and Arc mainnet.
To an agent, a chain is an implementation detail. It needs a service paid and a receipt returned. To the person behind it, one budget and one approval should cover wherever the service happens to live.
If settlement happens on the most liquid networks, what does a purpose-built agent chain add? Kite's answer centers on identity, delegation and spending policy, the layer Passport carries across every route it takes.
Does an agent payment layer need its own chain, or just excellent routing?
#KiteBBW $KITE
A payments layer for agents does not have to own the road. It has to make sure the agent arrives.
Kite Passport's release notes show that philosophy at work. Since July 2026, an x402 payment can settle on a different chain than the one holding your funds: Passport bridges and routes automatically across Base, Tempo and Solana, and Base is now the default settlement chain. The dashboard draws a route timeline for each routed payment, with bridged amounts, explorer links and token logos for USDC and PYUSD. Later releases added Robinhood Chain support and Arc mainnet.
To an agent, a chain is an implementation detail. It needs a service paid and a receipt returned. To the person behind it, one budget and one approval should cover wherever the service happens to live.
If settlement happens on the most liquid networks, what does a purpose-built agent chain add? Kite's answer centers on identity, delegation and spending policy, the layer Passport carries across every route it takes.
Does an agent payment layer need its own chain, or just excellent routing?
#KiteBBW $KITE
Kite Passport's release notes show that philosophy at work. Since July 2026, an x402 payment can settle on a different chain than the one holding your funds: Passport bridges and routes automatically across Base, Tempo and Solana, and Base is now the default settlement chain. The dashboard draws a route timeline for each routed payment, with bridged amounts, explorer links and token logos for USDC and PYUSD. Later releases added Robinhood Chain support and Arc mainnet.
To an agent, a chain is an implementation detail. It needs a service paid and a receipt returned. To the person behind it, one budget and one approval should cover wherever the service happens to live.
If settlement happens on the most liquid networks, what does a purpose-built agent chain add? Kite's answer centers on identity, delegation and spending policy, the layer Passport carries across every route it takes.
Does an agent payment layer need its own chain, or just excellent routing?
#KiteBBW $KITE
LinhInsights:
Excellent routing is essential, but identity and programmable permissions are what make the system agent-native. The chain should support the experience, not become the main selling point.
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The agent economy won’t be defined by how convincingly AI can talk. It will be defined by what agents can safely do—and who remains accountable when they act.
That is the lens I would use to evaluate Kite: not just as an AI-and-crypto narrative, but through the practical requirements of an economy where software can transact on behalf of questions matter:
Permission: Can an people.
For me, three agent’s authority be clearly bounded, so access to a wallet does not become unlimited permission to spend?
Verification: Can a user trace what the agent paid for, what it received, and whether the outcome met the agreed conditions?
Accountability: When a task fails, is there a clear way to identify responsibility and resolve the dispute?
Imagine an agent purchasing a research dataset. Completing a payment is only part of the job. The agent also needs spending authorization, evidence that the dataset was delivered, and a way to assess whether it meets the request. A transaction receipt alone does not prove useful work.
This is why I think discussions about Kite and the agent economy should move beyond transaction speed and token narratives. The more meaningful test is whether infrastructure makes delegated economic activity understandable, auditable, and controllable.
These are evaluation criteria—not claims that Kite already solves every challenge. Demonstrated workflows and documented safeguards matter more than slogans.
What evidence would you need before trusting an AI agent to spend on your behalf?
#KiteBBW $KITE @GoKiteAI
The agent economy won’t be defined by how convincingly AI can talk. It will be defined by what agents can safely do—and who remains accountable when they act.
That is the lens I would use to evaluate Kite: not just as an AI-and-crypto narrative, but through the practical requirements of an economy where software can transact on behalf of questions matter:
Permission: Can an people.
For me, three agent’s authority be clearly bounded, so access to a wallet does not become unlimited permission to spend?
Verification: Can a user trace what the agent paid for, what it received, and whether the outcome met the agreed conditions?
Accountability: When a task fails, is there a clear way to identify responsibility and resolve the dispute?
Imagine an agent purchasing a research dataset. Completing a payment is only part of the job. The agent also needs spending authorization, evidence that the dataset was delivered, and a way to assess whether it meets the request. A transaction receipt alone does not prove useful work.
This is why I think discussions about Kite and the agent economy should move beyond transaction speed and token narratives. The more meaningful test is whether infrastructure makes delegated economic activity understandable, auditable, and controllable.
These are evaluation criteria—not claims that Kite already solves every challenge. Demonstrated workflows and documented safeguards matter more than slogans.
What evidence would you need before trusting an AI agent to spend on your behalf?
#KiteBBW $KITE @KITE AI 中文
That is the lens I would use to evaluate Kite: not just as an AI-and-crypto narrative, but through the practical requirements of an economy where software can transact on behalf of questions matter:
Permission: Can an people.
For me, three agent’s authority be clearly bounded, so access to a wallet does not become unlimited permission to spend?
Verification: Can a user trace what the agent paid for, what it received, and whether the outcome met the agreed conditions?
Accountability: When a task fails, is there a clear way to identify responsibility and resolve the dispute?
Imagine an agent purchasing a research dataset. Completing a payment is only part of the job. The agent also needs spending authorization, evidence that the dataset was delivered, and a way to assess whether it meets the request. A transaction receipt alone does not prove useful work.
This is why I think discussions about Kite and the agent economy should move beyond transaction speed and token narratives. The more meaningful test is whether infrastructure makes delegated economic activity understandable, auditable, and controllable.
These are evaluation criteria—not claims that Kite already solves every challenge. Demonstrated workflows and documented safeguards matter more than slogans.
What evidence would you need before trusting an AI agent to spend on your behalf?
#KiteBBW $KITE @KITE AI 中文
LinhInsights:
Clear permissions, verifiable outcomes, and accountability are essential before trusting agents with real money. A transaction alone doesn’t prove the task was done right.
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Four standards, one agent.
x402, from Coinbase, revives the old HTTP 402 Payment Required code so a service can ask for money inside a single web request. Google's AP2 defines how an agent's payment mandate gets expressed. Stripe has its own Machine Payment Protocol. Anthropic's MCP connects models to tools and data.
Kite's bet is that nobody needs to pick a winner. Its mainnet announcement positioned the project as a hub across all four, and Kite is a member of the Linux Foundation's Agentic AI Foundation. It joined Google's AP2 as a community partner in February 2026. The whitepaper compares AP2 to ERC-20 and casts Kite in the role Ethereum plays for tokens: the layer that executes and settles the intents.
Neutral infrastructure wins while standards stay plural and gets squeezed if one of them absorbs the rest. The open question is who owns the customer once things settle: the specification authors or the rails that carry the money.
My bet is that routing beats loyalty. Tell me where that breaks.
#KiteBBW $KITE
Four standards, one agent.
x402, from Coinbase, revives the old HTTP 402 Payment Required code so a service can ask for money inside a single web request. Google's AP2 defines how an agent's payment mandate gets expressed. Stripe has its own Machine Payment Protocol. Anthropic's MCP connects models to tools and data.
Kite's bet is that nobody needs to pick a winner. Its mainnet announcement positioned the project as a hub across all four, and Kite is a member of the Linux Foundation's Agentic AI Foundation. It joined Google's AP2 as a community partner in February 2026. The whitepaper compares AP2 to ERC-20 and casts Kite in the role Ethereum plays for tokens: the layer that executes and settles the intents.
Neutral infrastructure wins while standards stay plural and gets squeezed if one of them absorbs the rest. The open question is who owns the customer once things settle: the specification authors or the rails that carry the money.
My bet is that routing beats loyalty. Tell me where that breaks.
#KiteBBW $KITE
x402, from Coinbase, revives the old HTTP 402 Payment Required code so a service can ask for money inside a single web request. Google's AP2 defines how an agent's payment mandate gets expressed. Stripe has its own Machine Payment Protocol. Anthropic's MCP connects models to tools and data.
Kite's bet is that nobody needs to pick a winner. Its mainnet announcement positioned the project as a hub across all four, and Kite is a member of the Linux Foundation's Agentic AI Foundation. It joined Google's AP2 as a community partner in February 2026. The whitepaper compares AP2 to ERC-20 and casts Kite in the role Ethereum plays for tokens: the layer that executes and settles the intents.
Neutral infrastructure wins while standards stay plural and gets squeezed if one of them absorbs the rest. The open question is who owns the customer once things settle: the specification authors or the rails that carry the money.
My bet is that routing beats loyalty. Tell me where that breaks.
#KiteBBW $KITE
LinhInsights:
Routing across multiple standards could be a real advantage, but the challenge will be proving that interoperability works reliably in practice, not just on paper.
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AI AGENTS WILL NEED MORE THAN SMART MODELS TO ENTER THE REAL ECONOMY 🚀
AI agents are becoming increasingly capable of handling research, coordinating workflows, and interacting with digital tools.
But there is a difference between an agent that demonstrates a task and one that can reliably complete it in a real business environment.
Consider an autonomous business assistant that gathers market information, purchases computing resources, and pays for specialized software. Its intelligence may be impressive, but businesses will still ask practical questions.
Can it operate within a defined budget? Can developers integrate it without unnecessary complexity?
These questions could determine whether agentic AI moves beyond experimentation.
1. Usable infrastructure
Developers need payment systems and integrations that fit naturally into existing applications. Complex setup can become a barrier even when the underlying technology is promising.
2. Controlled autonomy
Businesses need ways to define an agent's authority. Budgets, transaction permissions, and clear approval procedures can help make automated workflows more manageable.
3. Measurable reliability
Successful demonstrations are encouraging, but sustained adoption requires dependable execution, understandable records, and appropriate handling of failures.
Kite and the Agent Economy
Kite is building infrastructure focused on AI agents and payments, making it relevant to the broader discussion about how autonomous software could participate in digital commerce.
The next stage of this sector will require more than new capabilities. Developers must build useful applications, services must deliver consistent value, and users must have reasons to trust the systems involved.
I would pay attention to developer adoption, practical integrations, recurring usage, and the quality of permission controls rather than judging progress through announcements alone.
Which factor will drive adoption fastest: better AI models, easier integrations, or safer payment infrastructure?
#KiteBBW $KITE
AI AGENTS WILL NEED MORE THAN SMART MODELS TO ENTER THE REAL ECONOMY 🚀
AI agents are becoming increasingly capable of handling research, coordinating workflows, and interacting with digital tools.
But there is a difference between an agent that demonstrates a task and one that can reliably complete it in a real business environment.
Consider an autonomous business assistant that gathers market information, purchases computing resources, and pays for specialized software. Its intelligence may be impressive, but businesses will still ask practical questions.
Can it operate within a defined budget? Can developers integrate it without unnecessary complexity?
These questions could determine whether agentic AI moves beyond experimentation.
1. Usable infrastructure
Developers need payment systems and integrations that fit naturally into existing applications. Complex setup can become a barrier even when the underlying technology is promising.
2. Controlled autonomy
Businesses need ways to define an agent's authority. Budgets, transaction permissions, and clear approval procedures can help make automated workflows more manageable.
3. Measurable reliability
Successful demonstrations are encouraging, but sustained adoption requires dependable execution, understandable records, and appropriate handling of failures.
Kite and the Agent Economy
Kite is building infrastructure focused on AI agents and payments, making it relevant to the broader discussion about how autonomous software could participate in digital commerce.
The next stage of this sector will require more than new capabilities. Developers must build useful applications, services must deliver consistent value, and users must have reasons to trust the systems involved.
I would pay attention to developer adoption, practical integrations, recurring usage, and the quality of permission controls rather than judging progress through announcements alone.
Which factor will drive adoption fastest: better AI models, easier integrations, or safer payment infrastructure?
#KiteBBW $KITE
AI agents are becoming increasingly capable of handling research, coordinating workflows, and interacting with digital tools.
But there is a difference between an agent that demonstrates a task and one that can reliably complete it in a real business environment.
Consider an autonomous business assistant that gathers market information, purchases computing resources, and pays for specialized software. Its intelligence may be impressive, but businesses will still ask practical questions.
Can it operate within a defined budget? Can developers integrate it without unnecessary complexity?
These questions could determine whether agentic AI moves beyond experimentation.
1. Usable infrastructure
Developers need payment systems and integrations that fit naturally into existing applications. Complex setup can become a barrier even when the underlying technology is promising.
2. Controlled autonomy
Businesses need ways to define an agent's authority. Budgets, transaction permissions, and clear approval procedures can help make automated workflows more manageable.
3. Measurable reliability
Successful demonstrations are encouraging, but sustained adoption requires dependable execution, understandable records, and appropriate handling of failures.
Kite and the Agent Economy
Kite is building infrastructure focused on AI agents and payments, making it relevant to the broader discussion about how autonomous software could participate in digital commerce.
The next stage of this sector will require more than new capabilities. Developers must build useful applications, services must deliver consistent value, and users must have reasons to trust the systems involved.
I would pay attention to developer adoption, practical integrations, recurring usage, and the quality of permission controls rather than judging progress through announcements alone.
Which factor will drive adoption fastest: better AI models, easier integrations, or safer payment infrastructure?
#KiteBBW $KITE
LinhInsights:
Safer payment infrastructure is key. Even the smartest agent needs clear limits and reliable execution before businesses can trust it with real money.
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Before you grant an agent any permission, run the worst case. Kite's whitepaper does it formally.
A Standing Intent is the user's signed declaration: which agent, what per-transaction cap, what daily cap, when it expires. Every operation has to trace back to a valid one. The paper then proves a bound on loss under its stated assumptions. Take a $100 daily cap over 30 days. Even if the agent is fully compromised, the most that can be extracted is $3,000. Providers enforce the caps, and a global cap can lower the ceiling further.
Most security talk about agents is vibes: guardrails, alignment, trust. This is arithmetic. You can write the maximum loss on a napkin, and the napkin stays correct whether the model hallucinated or an attacker took over the agent.
A bound beats a promise because it keeps holding when everything else fails.
Write down your own agent's worst-case loss. If you cannot, you already have your answer.
#KiteBBW $KITE
Before you grant an agent any permission, run the worst case. Kite's whitepaper does it formally.
A Standing Intent is the user's signed declaration: which agent, what per-transaction cap, what daily cap, when it expires. Every operation has to trace back to a valid one. The paper then proves a bound on loss under its stated assumptions. Take a $100 daily cap over 30 days. Even if the agent is fully compromised, the most that can be extracted is $3,000. Providers enforce the caps, and a global cap can lower the ceiling further.
Most security talk about agents is vibes: guardrails, alignment, trust. This is arithmetic. You can write the maximum loss on a napkin, and the napkin stays correct whether the model hallucinated or an attacker took over the agent.
A bound beats a promise because it keeps holding when everything else fails.
Write down your own agent's worst-case loss. If you cannot, you already have your answer.
#KiteBBW $KITE
A Standing Intent is the user's signed declaration: which agent, what per-transaction cap, what daily cap, when it expires. Every operation has to trace back to a valid one. The paper then proves a bound on loss under its stated assumptions. Take a $100 daily cap over 30 days. Even if the agent is fully compromised, the most that can be extracted is $3,000. Providers enforce the caps, and a global cap can lower the ceiling further.
Most security talk about agents is vibes: guardrails, alignment, trust. This is arithmetic. You can write the maximum loss on a napkin, and the napkin stays correct whether the model hallucinated or an attacker took over the agent.
A bound beats a promise because it keeps holding when everything else fails.
Write down your own agent's worst-case loss. If you cannot, you already have your answer.
#KiteBBW $KITE
LinhInsights:
Putting a hard number on worst-case loss makes agent security much more practical. Clear spending limits matter even when everything goes wrong.
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AI Payment Volume Looks Impressive. But Who’s Actually Paying?
Kite Passport lets agents pay for compatible services through flows such as x402. What interests me is the bigger question: are we seeing real AI-driven commerce, or just more automated transactions?
TRM Labs’ September 2026 analysis tracked about $52.7M across 198.9M x402 settlements. After filtering activity it considered less likely to be genuine commerce, $25.62M remained. But its estimate of agentic activity was just 0.6–7.5% of that screened pool.
That range is an estimate, not a verified count. On-chain data can show a payment happened, but not always whether an AI agent or an ordinary script initiated it. Simple, single-purpose agents could also be missed.
My takeaway: payment volume alone won’t prove an agent economy is taking shape. I’d look for repeat customers, independent services earning revenue, and useful results—not just transaction counts.
What would convince you that AI agents are becoming real economic participants?
#KiteBBW $KITE
AI Payment Volume Looks Impressive. But Who’s Actually Paying?
Kite Passport lets agents pay for compatible services through flows such as x402. What interests me is the bigger question: are we seeing real AI-driven commerce, or just more automated transactions?
TRM Labs’ September 2026 analysis tracked about $52.7M across 198.9M x402 settlements. After filtering activity it considered less likely to be genuine commerce, $25.62M remained. But its estimate of agentic activity was just 0.6–7.5% of that screened pool.
That range is an estimate, not a verified count. On-chain data can show a payment happened, but not always whether an AI agent or an ordinary script initiated it. Simple, single-purpose agents could also be missed.
My takeaway: payment volume alone won’t prove an agent economy is taking shape. I’d look for repeat customers, independent services earning revenue, and useful results—not just transaction counts.
What would convince you that AI agents are becoming real economic participants?
#KiteBBW $KITE
Kite Passport lets agents pay for compatible services through flows such as x402. What interests me is the bigger question: are we seeing real AI-driven commerce, or just more automated transactions?
TRM Labs’ September 2026 analysis tracked about $52.7M across 198.9M x402 settlements. After filtering activity it considered less likely to be genuine commerce, $25.62M remained. But its estimate of agentic activity was just 0.6–7.5% of that screened pool.
That range is an estimate, not a verified count. On-chain data can show a payment happened, but not always whether an AI agent or an ordinary script initiated it. Simple, single-purpose agents could also be missed.
My takeaway: payment volume alone won’t prove an agent economy is taking shape. I’d look for repeat customers, independent services earning revenue, and useful results—not just transaction counts.
What would convince you that AI agents are becoming real economic participants?
#KiteBBW $KITE
LinhInsights:
Real adoption should be measured by repeat usage and actual value delivered, not just transaction volume. Payments are only meaningful when they reflect useful work.
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A card swipe costs about thirty cents before the percentage kicks in. An inference call might be worth a hundredth of a cent. The math never worked.
Kite's whitepaper attacks it with state channels. An agent locks a deposit on-chain to open a channel with a service, signs a tiny voucher with every request, and the two sides settle once at the end. Two on-chain transactions, thousands of off-chain updates. The paper targets sub-100 millisecond latency and roughly $0.000001 per message, and its own model spreads an open-and-close cost of about one cent across a million payments.
The paper is candid about the catch. Channels assume participants stay online to contest disputes, and the argument is that services with reputation at stake have every reason to stay available. That tradeoff deserves debate, because per-call billing only works if the dispute path is boring.
These are design targets, so production numbers are what to watch. If a call can cost a millionth of a dollar, which pricing model dies first?
#KiteBBW $KITE
A card swipe costs about thirty cents before the percentage kicks in. An inference call might be worth a hundredth of a cent. The math never worked.
Kite's whitepaper attacks it with state channels. An agent locks a deposit on-chain to open a channel with a service, signs a tiny voucher with every request, and the two sides settle once at the end. Two on-chain transactions, thousands of off-chain updates. The paper targets sub-100 millisecond latency and roughly $0.000001 per message, and its own model spreads an open-and-close cost of about one cent across a million payments.
The paper is candid about the catch. Channels assume participants stay online to contest disputes, and the argument is that services with reputation at stake have every reason to stay available. That tradeoff deserves debate, because per-call billing only works if the dispute path is boring.
These are design targets, so production numbers are what to watch. If a call can cost a millionth of a dollar, which pricing model dies first?
#KiteBBW $KITE
Kite's whitepaper attacks it with state channels. An agent locks a deposit on-chain to open a channel with a service, signs a tiny voucher with every request, and the two sides settle once at the end. Two on-chain transactions, thousands of off-chain updates. The paper targets sub-100 millisecond latency and roughly $0.000001 per message, and its own model spreads an open-and-close cost of about one cent across a million payments.
The paper is candid about the catch. Channels assume participants stay online to contest disputes, and the argument is that services with reputation at stake have every reason to stay available. That tradeoff deserves debate, because per-call billing only works if the dispute path is boring.
These are design targets, so production numbers are what to watch. If a call can cost a millionth of a dollar, which pricing model dies first?
#KiteBBW $KITE
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