Carol Lin

CEO of Global Business. Building for the agent era where intelligence matters only when it works in the real world.

[Carol Lin @CarolGLMs]

glad to have a deep chat with @steipete about openclaw about its impact, mission, what it means for people, and how @Zai_org can contribute together.

Let’s continually..

🦞Build for open source.
🦞Do meaningful work.
🦞Take OpenClaw everywhere ..

to every nation, every school, every human.

[Carol Lin @CarolGLMs]

@cz_binance where can i buy the book in Singapore？

[jietang @jietang]

Recent thoughts:
The Shift to Long-Horizon Tasks
The most likely breakthrough this year will be in long-horizon tasks. We are moving toward a stage where Large Language Models (LLMs) learn to complete extended, complex missions by interacting with Agent environments. This is perhaps where the true value of LLMs lies. Take cybersecurity as an example: imagine a model that continuously hunts for software bugs and vulnerabilities. While it sounds like a search process, it’s actually the model learning the high-level intuition and methodology of a professional hacker. Unlike humans, AI can run 24/7 without fatigue. It could potentially find exploits at a much higher frequwill ency and claim bounties on platforms like HackerOne or BugCrowd. It sounds fun, but fundamentally, it's a revolution that displaces the hacker. If even hackers are being "disrupted," one can only imagine the impact on general programmers.

From One-Person to None-Person Companies
Building on long-horizon capabilities, Autonomous Agent Systems (AAS) will inevitably become the next frontier. Last year, we were discussing the rise of the "One Person Company" (OPC). I didn't expect us to move so quickly toward the "None Person Company" (NPC). It’s an ironic twist—we might all end up as NPCs in this new ecosystem.

Engineering the Impossible: Memory and Learning
To realize the vision above, we must solve three technical pillars: Memory, Continual Learning, and Self-Judging.
I used to think these would require massive paradigm shifts and years of research. However, the pressure from both the technical and application sides is so intense that we are seeing these capabilities emerge through ingenious engineering "tricks":
Memory: Long context windows (1M+) and RAG have significantly bridged the gap.
Continual Learning: While true continual learning remains difficult, the release cycles are shrinking. Global models are updated monthly; domestic models are catching up. If we reach weekly updates by next year, it will effectively function as continual learning.
Self-Judging: This remains the most elusive, yet models like Opus 4.7 are already demonstrating early self-correction and judgment capabilities.

The Self-Evolving Endgame
The most difficult—and most promising—path is Self-Evolution. The current wave is incredibly fierce. I suspect that models like Claude may have already achieved a baseline for self-training: writing their own code, cleaning their own data, generating synthetic data, and then training on it. It might "waste" some compute, but it saves the most precious resources: human labor and time. In the LLM era, speed is everything. Rapid iteration is what creates the cognitive gap between leaders and followers. Claude’s rumored 2-million-chip cluster for next year is likely dedicated to exactly this: autonomous model self-training.
Technical Summary:
1M Context: Necessary baseline.
Memory & Continual Learning: Prerequisites, likely solved first via "tricky" engineering.
Harnessing Environments: The breakthrough point.
Self-Judging: The tipping point.
Full Self-Training: The endgame.

Redefining AGI and the Industry
If this is the road to AGI, then AGI’s definition should be the sum of all human collective intelligence, not just an individual’s intelligence. It must possess the creative capacity to produce something as profound as the "Theory of Relativity"—meeting the bar set by Hassabis.
During this transition, every APP will need to be reconstructed as AI-native. In fact, we might move past the concept of APPs entirely. The most significant challenge will be the reconstruction of the operating system itself. In the future, you won’t see a traditional desktop; you will see an LLM OS, where applications are "generated on demand." This challenges the 80-year-old Von Neumann architecture and represents a total upheaval of the computer science industry.

The Irreversible Wave
From completing long-horizon tasks to fully autonomous operations, every sector—Security, Finance, Law, E-commerce—will be reshaped. Many friends have reached out lately, asking how to transform their enterprises to keep pace with AI. But few truly realize that this irreversible process has already begun. As this massive technical wave hits, we must be prepared to act, but we must also start thinking seriously about how to regulate it.

[Carol Lin @CarolGLMs]

The next phase of AI competition will be won in the enterprise where deployment, trust, and workflow integration matter more than model quality alone.

[Matt Garman @mattsgarman]

Thought I would start posting about interesting things happening at AWS. Not a bad day to start.🚀

Today at #WhatsNextWithAWS we announced a big step forward with @OpenAI on Amazon Bedrock:
1. OpenAI models now available
2. Codex for enterprise development
3. Amazon Bedrock Managed Agents for running agents in production

Together, these give customers more choice and flexibility to use the best models for their needs, all on @awscloud. Thanks @dhdresser for joining us.

Full announcement: https://t.co/ClNANBqtu3

[Carol Lin @CarolGLMs]

In AI, business models shape product behavior.If an assistant is meant to help you think, trust and alignment can’t be secondary to monetization.

[Claude @claudeai]

Claude is built to be a genuinely helpful assistant for work and for deep thinking.

Advertising would be incompatible with that vision.

Read why Claude will remain ad-free: https://t.co/Dr8FOJxINC

[Carol Lin @CarolGLMs]

This is where the market is heading: from model access to workflow integration. In the agent era, real adoption depends on how well intelligence fits into production systems...

[OpenAI Newsroom @OpenAINewsroom]

Earlier this year, OpenAI and @amazon partnered to bring OpenAI’s frontier capabilities to enterprises, startups, and customers around the world.

We’re taking the next step: making our models, Codex, and Bedrock Managed Agents available to @awscloud customers, in limited preview.

Making OpenAI available on AWS means enterprises can get AI into production faster - across software engineering and other professional workflows.

We’re excited to see what gets built!

https://t.co/04HlMSSOEe

[OpenAI Newsroom @OpenAINewsroom]

Earlier this year, OpenAI and @amazon partnered to bring OpenAI’s frontier capabilities to enterprises, startups, and customers around the world.

We’re taking the next step: making our models, Codex, and Bedrock Managed Agents available to @awscloud customers, in limited preview.

Making OpenAI available on AWS means enterprises can get AI into production faster - across software engineering and other professional workflows.

We’re excited to see what gets built!

https://t.co/04HlMSSOEe

[Z.ai @Zai_org]

Scaling laws push model capability forward. But whether that capability becomes reliable in production depends on how we handle Scaling Pain.

https://t.co/81QCQw941P
In our latest blog, we share how we debugged GLM-5 serving at scale: reproducing rare garbled outputs, repetition, and rare-character generation; tracing and eliminating KV Cache race conditions; fixing HiCache synchronization issues; and introducing LayerSplit for up to 132% throughput improvement.

We hope these lessons help the community avoid similar pitfalls and build more robust inference infrastructure.

[VergeX AI @vergex_ai]

VergeX × https://t.co/7Gi2w5DVoX GLM-5 Odyssey

5B+ GLM-5 credits consumed.
+1.5B additional capacity, absorbed immediately.

1,500+ new users onboarded.

[Carol Lin @CarolGLMs]

@vergex_ai @Zai_org @ZaiforStartups cool

[GOSIM Foundation @gosimfoundation]

We are thrilled to welcome @Zhipu_AI as a Gold Sponsor for #GOSIMParis 2026! 🇫🇷

https://t.co/WAh8o5QBXT

From groundbreaking LLMs to a thriving developer ecosystem, Zhipu is at the heart of the AI revolution. Stay tuned as we power the GOSIM Agentic Hackathon,（https://t.co/EooMQiorhX） where developers will build the future of open-source intelligence using Zhipu’s cutting-edge models

See you in Paris! 🗼✨

#GOSIM #ZhipuAI #OpenSource #AI #TechInnovation

[jietang @jietang]

GLM 5.1 is coming https://t.co/rSnHYW95Dk. Coding is the cornersone and Long Horizon Task (LHT) is the new feature this time. focus more on 1. memory 2. evolving/continual learning 3. self judge/reflextion.

[Carol Lin @CarolGLMs]

GLM5.1 x #Google Vertex

https://t.co/DER7R7dnCN

[Z.ai for Startups @ZaiforStartups]

Most models still break mid-task

not because they’re not smart enough

but because they can’t stay in the loop

8-hour runs start to change that

this is how agents stop breaking.

[Carol Lin @CarolGLMs]

impressive…

[Lexi 勒西 @lexi_labs]

Seedance 2.0 又一新作。这种美女大片，并不会让人反感，相反还挺好看。

[zR @zRdianjiao]

GLM-5V-Turbo from @Zai_org also comes with full set of Skills tools.

🧩 Image & video captioning
📝 Document-based writing
📍 Object grounding
📊 PDF to PPT
🌐 PDF to web
🛠️ PRD to app
🎨 Prompt generation
📄 Resume screening
🖥️ Web replication
📈 Stock analysis

More than multimodal understanding — this is about turning vision into real productivity.

Now open-sourced. Welcome to try:
https://t.co/kDr7PrcJxr

[Carol Lin @CarolGLMs]

Haidilao + Qclaw

Do you know if you go to Haidilao (the hotpot restaurant) in China now, you may receive free installation services about #qclaw ?
@steipete

[Carol Lin @CarolGLMs]

@OpenBuildxyz cant agree more

[Carol Lin @CarolGLMs]

Big thanks to all our partners for the support..

We’re inviting the best startups to join now..let’s see who makes the finals 👀

Singapore · May 9
See you there.

[Z.ai for Startups @ZaiforStartups]

Agents don’t learn by watching.

They learn by building.

CodeBuddy × GLM — Global AI Hackathon Singapore 🇸🇬

Build. Ship. See what actually breaks.

$1,000+ prizes + mentorship.

Apply by April 20th.

[Carol Lin @CarolGLMs]

Nice job ，which startup’s next? 🤗

If you’re building an AI-native startup, moving fast, and love GLM ❤️come join our startup community. Apply now!

[Z.ai for Startups @ZaiforStartups]

AI can generate anything.
But generation ≠ design.

Lokuma is the missing layer —
an AI designer your agents can call.

Turning raw outputs into real:
landing pages, webs, campaigns.

Now part of https://t.co/ax4zXxvDd1 Startup Program
let’s co-create the future of AI agents.

[Carol Lin @CarolGLMs]

Hard to nail everything when you’re not “Google” yet.

Still remember “the Sora moment ”had everyone going crazy ..

[Bloomberg @business]

OpenAI plans to discontinue its Sora video-generation service six months after debuting a standalone app, the company said on Tuesday https://t.co/VAgESjcNjg