What is an AI Agent?
Not just a chatbot — it's a system that autonomously plans, calls tools, and completes multi-step tasks.
From checking the weather to executing trades, agents move AI from "answering" to "doing."
The 2026 mainstream trend is already here.
What's the first
— PAN (@Pan_Ecosystem)
Jul 20, 2026
Not just a chatbot — it's a system that autonomously plans, calls tools, and completes multi-step tasks.
From checking the weather to executing trades, agents move AI from "answering" to "doing."
The 2026 mainstream trend is already here.
What's the first
— PAN (@Pan_Ecosystem)
Jul 20, 2026
X (formerly Twitter)
PAN (@Pan_Ecosystem) on X
What is an AI Agent?
Not just a chatbot — it's a system that autonomously plans, calls tools, and completes multi-step tasks.
From checking the weather to executing trades, agents move AI from "answering" to "doing."
The 2026 mainstream trend is already here.…
Not just a chatbot — it's a system that autonomously plans, calls tools, and completes multi-step tasks.
From checking the weather to executing trades, agents move AI from "answering" to "doing."
The 2026 mainstream trend is already here.…
“Real” is the right word.
Qwen-Image-3.0 shows that image generation is moving beyond aesthetics into real workflows: design, education, content, UI, e-commerce and scientific production.
Real workflows create real compute demand.
As AI agents begin to generate, revise and https://t.co/oGhPzpqCEv
— PAN (@Pan_Ecosystem)
Jul 23, 2026
Qwen-Image-3.0 shows that image generation is moving beyond aesthetics into real workflows: design, education, content, UI, e-commerce and scientific production.
Real workflows create real compute demand.
As AI agents begin to generate, revise and https://t.co/oGhPzpqCEv
— PAN (@Pan_Ecosystem)
Jul 23, 2026
X (formerly Twitter)
Qwen (@Alibaba_Qwen) on X
🎨 Meet Qwen-Image-3.0 — the third generation of our foundational image generation model.
If 1.0 was about "Precision," and 2.0 added "Variety, Completeness, Beauty & Authenticity," then 3.0 comes down to a single word: Real (实).
Three dimensions of "Real":…
If 1.0 was about "Precision," and 2.0 added "Variety, Completeness, Beauty & Authenticity," then 3.0 comes down to a single word: Real (实).
Three dimensions of "Real":…
Voice is becoming the control layer for agents.
ChatGPT on desktop can now listen, speak, coordinate work and direct multiple agents across your computer.
That means AI is moving from “answering questions” to operating workflows.
As agents take action, they will need https://t.co/mnp8YmPIKH
— PAN (@Pan_Ecosystem)
Jul 24, 2026
ChatGPT on desktop can now listen, speak, coordinate work and direct multiple agents across your computer.
That means AI is moving from “answering questions” to operating workflows.
As agents take action, they will need https://t.co/mnp8YmPIKH
— PAN (@Pan_Ecosystem)
Jul 24, 2026
X (formerly Twitter)
OpenAI (@OpenAI) on X
ChatGPT Voice is now in the desktop app.
Control your computer and direct multiple agents running in ChatGPT Work or Codex, using just your voice.
It's powered by GPT-Live, so it can speak, listen, and coordinate work in the app at the same time.
Rolling…
Control your computer and direct multiple agents running in ChatGPT Work or Codex, using just your voice.
It's powered by GPT-Live, so it can speak, listen, and coordinate work in the app at the same time.
Rolling…
Open models are not the end of the AI stack.
They are the beginning of massive agent deployment.
As more companies and developers build on open models, agents will need to call external compute, run private tasks, verify outputs and pay for execution. https://t.co/CYPvOFW9kP
— PAN (@Pan_Ecosystem)
Jul 26, 2026
They are the beginning of massive agent deployment.
As more companies and developers build on open models, agents will need to call external compute, run private tasks, verify outputs and pay for execution. https://t.co/CYPvOFW9kP
— PAN (@Pan_Ecosystem)
Jul 26, 2026
X (formerly Twitter)
Jensen Huang (@JensenHuang) on X
For my first post, I’m sharing a letter @NVIDIA signed on why open models matter.
AI will transform every industry, power every company, and be built by every country.
Open models strengthen safety and cybersecurity, accelerate innovation and diffusion…
AI will transform every industry, power every company, and be built by every country.
Open models strengthen safety and cybersecurity, accelerate innovation and diffusion…
Agent autonomy is rising.
Without verification, one rogue action can cascade.
Production agents need intent checks and execution proofs.
Safety is an infrastructure layer.
— PAN (@Pan_Ecosystem)
Jul 28, 2026
Without verification, one rogue action can cascade.
Production agents need intent checks and execution proofs.
Safety is an infrastructure layer.
— PAN (@Pan_Ecosystem)
Jul 28, 2026
X (formerly Twitter)
PAN (@Pan_Ecosystem) on X
Agent autonomy is rising.
Without verification, one rogue action can cascade.
Production agents need intent checks and execution proofs.
Safety is an infrastructure layer.
Without verification, one rogue action can cascade.
Production agents need intent checks and execution proofs.
Safety is an infrastructure layer.
In preparation for what’s next, Pan new website is now live.
We’ve updated the design, product pages, and onboarding flow.
What do you think we should launch next? https://t.co/r8mRaALhL9
— PAN (@Pan_Ecosystem)
Jul 29, 2026
We’ve updated the design, product pages, and onboarding flow.
What do you think we should launch next? https://t.co/r8mRaALhL9
— PAN (@Pan_Ecosystem)
Jul 29, 2026
X (formerly Twitter)
PAN (@Pan_Ecosystem) on X
In preparation for what’s next, Pan new website is now live.
We’ve updated the design, product pages, and onboarding flow.
What do you think we should launch next?
We’ve updated the design, product pages, and onboarding flow.
What do you think we should launch next?
Training loves centralized clusters.
Agents need continuous, low-latency compute.
Idle GPUs will join the supply side.
PAN is building the coordination layer for verifiable agent compute. https://t.co/lspsYwKjLu
— PAN (@Pan_Ecosystem)
Jul 30, 2026
Agents need continuous, low-latency compute.
Idle GPUs will join the supply side.
PAN is building the coordination layer for verifiable agent compute. https://t.co/lspsYwKjLu
— PAN (@Pan_Ecosystem)
Jul 30, 2026
X (formerly Twitter)
PAN (@Pan_Ecosystem) on X
Training loves centralized clusters.
Agents need continuous, low-latency compute.
Idle GPUs will join the supply side.
PAN is building the coordination layer for verifiable agent compute.
Agents need continuous, low-latency compute.
Idle GPUs will join the supply side.
PAN is building the coordination layer for verifiable agent compute.
Every tool call and inference step can be a transaction.
Agents will request, verify and pay for execution.
PAN is building financial rails for the agent economy. https://t.co/IrgYnmDzIM
— PAN (@Pan_Ecosystem)
Aug 1, 2026
Agents will request, verify and pay for execution.
PAN is building financial rails for the agent economy. https://t.co/IrgYnmDzIM
— PAN (@Pan_Ecosystem)
Aug 1, 2026
X (formerly Twitter)
PAN (@Pan_Ecosystem) on X
Every tool call and inference step can be a transaction.
Agents will request, verify and pay for execution.
PAN is building financial rails for the agent economy.
Agents will request, verify and pay for execution.
PAN is building financial rails for the agent economy.
One question keeps showing up for us at PAN:
if agents are going to work all day, where does that work actually run?
Not the model.
Not the demo.
The execution behind it. https://t.co/8tr8Jp4WOU
— PAN (@Pan_Ecosystem)
Aug 4, 2026
if agents are going to work all day, where does that work actually run?
Not the model.
Not the demo.
The execution behind it. https://t.co/8tr8Jp4WOU
— PAN (@Pan_Ecosystem)
Aug 4, 2026
X (formerly Twitter)
PAN (@Pan_Ecosystem) on X
One question keeps showing up for us at PAN:
if agents are going to work all day, where does that work actually run?
Not the model.
Not the demo.
The execution behind it.
if agents are going to work all day, where does that work actually run?
Not the model.
Not the demo.
The execution behind it.
Once agents start paying for tools and compute, settlement stops being optional.
Someone has to prove what was requested, what ran, and who paid.
That’s the part we’re building around. https://t.co/cGrVzXVv2s
— PAN (@Pan_Ecosystem)
Aug 6, 2026
Someone has to prove what was requested, what ran, and who paid.
That’s the part we’re building around. https://t.co/cGrVzXVv2s
— PAN (@Pan_Ecosystem)
Aug 6, 2026
X (formerly Twitter)
PAN (@Pan_Ecosystem) on X
Once agents start paying for tools and compute, settlement stops being optional.
Someone has to prove what was requested, what ran, and who paid.
That’s the part we’re building around.
Someone has to prove what was requested, what ran, and who paid.
That’s the part we’re building around.
I don’t think the next AI compute wave will look like the last one.
Training was big clusters and big headlines.
Agents feel different.
Smaller jobs.
Running constantly.
Happening in more places.
Messier, but probably much bigger than people expect. https://t.co/5NJBwZaBZV
— PAN (@Pan_Ecosystem)
Aug 7, 2026
Training was big clusters and big headlines.
Agents feel different.
Smaller jobs.
Running constantly.
Happening in more places.
Messier, but probably much bigger than people expect. https://t.co/5NJBwZaBZV
— PAN (@Pan_Ecosystem)
Aug 7, 2026
X (formerly Twitter)
PAN (@Pan_Ecosystem) on X
I don’t think the next AI compute wave will look like the last one.
Training was big clusters and big headlines.
Agents feel different.
Smaller jobs.
Running constantly.
Happening in more places.
Messier, but probably much bigger than people expect.
Training was big clusters and big headlines.
Agents feel different.
Smaller jobs.
Running constantly.
Happening in more places.
Messier, but probably much bigger than people expect.
We’re not trying to make smarter agents.
We’re trying to make agent execution something you can actually verify and settle.
Intent, compute, payment, result.
PAN sits in that loop.
— PAN (@Pan_Ecosystem)
Aug 9, 2026
We’re trying to make agent execution something you can actually verify and settle.
Intent, compute, payment, result.
PAN sits in that loop.
— PAN (@Pan_Ecosystem)
Aug 9, 2026
X (formerly Twitter)
PAN (@Pan_Ecosystem) on X
We’re not trying to make smarter agents.
We’re trying to make agent execution something you can actually verify and settle.
Intent, compute, payment, result.
PAN sits in that loop.
We’re trying to make agent execution something you can actually verify and settle.
Intent, compute, payment, result.
PAN sits in that loop.
Official Announcement
Thrilled to partner with @XAgent_official the zero-code platform empowering anyone to Speak to Build custom AI Agents.
As the Demand Layer for AI Compute PAN will explore seamless compute access agent-to-agent payments and scalable infrastructure for the https://t.co/mYgOtdDTjz
— PAN (@Pan_Ecosystem)
Aug 10, 2026
Thrilled to partner with @XAgent_official the zero-code platform empowering anyone to Speak to Build custom AI Agents.
As the Demand Layer for AI Compute PAN will explore seamless compute access agent-to-agent payments and scalable infrastructure for the https://t.co/mYgOtdDTjz
— PAN (@Pan_Ecosystem)
Aug 10, 2026
X (formerly Twitter)
PAN (@Pan_Ecosystem) on X
Official Announcement
Thrilled to partner with @XAgent_official the zero-code platform empowering anyone to Speak to Build custom AI Agents.
As the Demand Layer for AI Compute PAN will explore seamless compute access agent-to-agent payments and scalable…
Thrilled to partner with @XAgent_official the zero-code platform empowering anyone to Speak to Build custom AI Agents.
As the Demand Layer for AI Compute PAN will explore seamless compute access agent-to-agent payments and scalable…
Training compute is easy to recognize.
Big clusters.
Big budgets.
Big announcements.
Agent compute will be harder to see.
Small jobs.
Always running.
Spread across tools, apps, and users.
Paid for one action at a time.
That market may be much larger than it looks.
— PAN (@Pan_Ecosystem)
Aug 11, 2026
Big clusters.
Big budgets.
Big announcements.
Agent compute will be harder to see.
Small jobs.
Always running.
Spread across tools, apps, and users.
Paid for one action at a time.
That market may be much larger than it looks.
— PAN (@Pan_Ecosystem)
Aug 11, 2026
X (formerly Twitter)
PAN (@Pan_Ecosystem) on X
Training compute is easy to recognize.
Big clusters.
Big budgets.
Big announcements.
Agent compute will be harder to see.
Small jobs.
Always running.
Spread across tools, apps, and users.
Paid for one action at a time.
That market may be much larger than…
Big clusters.
Big budgets.
Big announcements.
Agent compute will be harder to see.
Small jobs.
Always running.
Spread across tools, apps, and users.
Paid for one action at a time.
That market may be much larger than…
Training compute is easy to spot.
Big clusters.
Big budgets.
Big announcements.
Agent compute will be harder to see.
Small jobs.
Always running.
Spread across tools, apps, and users.
Paid for one action at a time.
The biggest compute market may be the one nobody sees. https://t.co/rI6uYqRSgb
— PAN (@Pan_Ecosystem)
Aug 13, 2026
Big clusters.
Big budgets.
Big announcements.
Agent compute will be harder to see.
Small jobs.
Always running.
Spread across tools, apps, and users.
Paid for one action at a time.
The biggest compute market may be the one nobody sees. https://t.co/rI6uYqRSgb
— PAN (@Pan_Ecosystem)
Aug 13, 2026
X (formerly Twitter)
PAN (@Pan_Ecosystem) on X
Training compute is easy to spot.
Big clusters.
Big budgets.
Big announcements.
Agent compute will be harder to see.
Small jobs.
Always running.
Spread across tools, apps, and users.
Paid for one action at a time.
The biggest compute market may be the…
Big clusters.
Big budgets.
Big announcements.
Agent compute will be harder to see.
Small jobs.
Always running.
Spread across tools, apps, and users.
Paid for one action at a time.
The biggest compute market may be the…
Agents need receipts.
Not screenshots.
Not vague logs.
A real one should show:
intent → compute → verification → payment → result.
PAN is building that execution record. https://t.co/i2DVVPjjDD
— PAN (@Pan_Ecosystem)
Aug 14, 2026
Not screenshots.
Not vague logs.
A real one should show:
intent → compute → verification → payment → result.
PAN is building that execution record. https://t.co/i2DVVPjjDD
— PAN (@Pan_Ecosystem)
Aug 14, 2026
X (formerly Twitter)
PAN (@Pan_Ecosystem) on X
Agents need receipts.
Not screenshots.
Not vague logs.
A real one should show:
intent → compute → verification → payment → result.
PAN is building that execution record.
Not screenshots.
Not vague logs.
A real one should show:
intent → compute → verification → payment → result.
PAN is building that execution record.
Open models do not just create more builders.
They create more agent attempts.
More experiments.
More tool calls.
More failed runs.
More inference demand.
More need to verify what actually happened.
The open-source wave expands the execution market, not just the model market. https://t.co/Sg0KVkPqk7
— PAN (@Pan_Ecosystem)
Aug 16, 2026
They create more agent attempts.
More experiments.
More tool calls.
More failed runs.
More inference demand.
More need to verify what actually happened.
The open-source wave expands the execution market, not just the model market. https://t.co/Sg0KVkPqk7
— PAN (@Pan_Ecosystem)
Aug 16, 2026
X (formerly Twitter)
PAN (@Pan_Ecosystem) on X
Open models do not just create more builders.
They create more agent attempts.
More experiments.
More tool calls.
More failed runs.
More inference demand.
More need to verify what actually happened.
The open-source wave expands the execution market, not…
They create more agent attempts.
More experiments.
More tool calls.
More failed runs.
More inference demand.
More need to verify what actually happened.
The open-source wave expands the execution market, not…
A wallet is not an approval system.
If an agent can spend,
you need to define:
what it can buy,
how much it can spend,
and when a human must approve. https://t.co/sdhiFPaKlh
— PAN (@Pan_Ecosystem)
Aug 18, 2026
If an agent can spend,
you need to define:
what it can buy,
how much it can spend,
and when a human must approve. https://t.co/sdhiFPaKlh
— PAN (@Pan_Ecosystem)
Aug 18, 2026
X (formerly Twitter)
PAN (@Pan_Ecosystem) on X
A wallet is not an approval system.
If an agent can spend,
you need to define:
what it can buy,
how much it can spend,
and when a human must approve.
If an agent can spend,
you need to define:
what it can buy,
how much it can spend,
and when a human must approve.
14,000 designs. 9 binders. 3 sub-nanomolar.
The agent didn't win because it was smart.
It won because the loop was closed:
design → wet-lab validate → feed back.
Autonomous execution only pays off
when there's a checkpoint at the end. https://t.co/zyvvLjIMdN
— PAN (@Pan_Ecosystem)
Aug 18, 2026
The agent didn't win because it was smart.
It won because the loop was closed:
design → wet-lab validate → feed back.
Autonomous execution only pays off
when there's a checkpoint at the end. https://t.co/zyvvLjIMdN
— PAN (@Pan_Ecosystem)
Aug 18, 2026
X (formerly Twitter)
NVIDIA Healthcare (@NVIDIAHealth) on X
Using NVIDIA Proteina-Complexa, @muni_bio's autoresearch agent explored nearly 14,000 protein designs.
@adaptyvbio validated nine TREM2 binders, three with sub-nanomolar affinity.
The results show how agents can connect computational design with wet-lab…
@adaptyvbio validated nine TREM2 binders, three with sub-nanomolar affinity.
The results show how agents can connect computational design with wet-lab…
Agent compute is not one big bill.
It is hundreds of small executions
that become visible only after they add up. https://t.co/tRbmilJYPy
— PAN (@Pan_Ecosystem)
Aug 20, 2026
It is hundreds of small executions
that become visible only after they add up. https://t.co/tRbmilJYPy
— PAN (@Pan_Ecosystem)
Aug 20, 2026
X (formerly Twitter)
PAN (@Pan_Ecosystem) on X
Agent compute is not one big bill.
It is hundreds of small executions
that become visible only after they add up.
It is hundreds of small executions
that become visible only after they add up.