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Something wild is happening on GitHub. DeerFlow 2.0 is exploding. Some developers are even saying they’re dropping OpenClaw for it. Why? Because this isn’t just an AI chatbot. You give it a goal and it: • researches the problem • writes the code • creates the files • launches...

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Julian Goldie SEO

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39,973 просмотров • 3 месяцев назад •via X (Twitter)

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Just watched this AI-generated short film and yeah… anyone still saying AI can’t create something watchable is seriously behind. This isn’t “AI makes trash” anymore, this is real storytelling, and real potential. The people actually using these tools already know: AI isn’t replacing creativity, it’s leveling it up. Studios aren’t ignoring it – they’re evolving with it. Watch this and tell me AI hasn’t come a long way.
3:15

Just watched this AI-generated short film and yeah… anyone still saying AI can’t create something watchable is seriously behind. This isn’t “AI makes trash” anymore, this is real storytelling, and real potential. The people actually using these tools already know: AI isn’t replacing creativity, it’s leveling it up. Studios aren’t ignoring it – they’re evolving with it. Watch this and tell me AI hasn’t come a long way.

Aleena Amir

144,023 просмотров • 1 месяц назад

🚨 UNCANNY VALLEY: WHY AI’S NEXT FRONTIER ISN’T THINKING—IT’S DOING Knowledge agents are here—and they’re thriving. But when it comes to action agents, even the best AI still struggles with the real world. Richard Socher: “Knowledge agents totally here… But action agents, not quite there yet.” As the gap widens between what AI knows and what it can do, the future hangs on how fast it learns to act.
0:30

🚨 UNCANNY VALLEY: WHY AI’S NEXT FRONTIER ISN’T THINKING—IT’S DOING Knowledge agents are here—and they’re thriving. But when it comes to action agents, even the best AI still struggles with the real world. Richard Socher: “Knowledge agents totally here… But action agents, not quite there yet.” As the gap widens between what AI knows and what it can do, the future hangs on how fast it learns to act.

Mario Nawfal

98,327 просмотров • 1 год назад

Someone just claimed they made $19,000 in 8 hours using OpenClaw. Here’s the crazy part. They didn’t do it manually. They used a tool called ClawWork that turns OpenClaw into a co-worker for 44 different professions. Writers. Developers. Marketers. Researchers. Support agents. All automated. It’s a free GitHub extension you plug straight into OpenClaw. The claim isn’t verified. But the earning tests and use cases people are posting are wild.
0:40

Someone just claimed they made $19,000 in 8 hours using OpenClaw. Here’s the crazy part. They didn’t do it manually. They used a tool called ClawWork that turns OpenClaw into a co-worker for 44 different professions. Writers. Developers. Marketers. Researchers. Support agents. All automated. It’s a free GitHub extension you plug straight into OpenClaw. The claim isn’t verified. But the earning tests and use cases people are posting are wild.

Julian Goldie SEO

19,804 просмотров • 3 месяцев назад

“The lobster is loose, and it’s not going back into the tank,” says OpenClaw🦞 founder Peter Steinberger 🦞. In this brand new talk from #TED2026 he shares why AI agents — built by you — are the future:
1:49

“The lobster is loose, and it’s not going back into the tank,” says OpenClaw🦞 founder Peter Steinberger 🦞. In this brand new talk from #TED2026 he shares why AI agents — built by you — are the future:

TED Talks

247,496 просмотров • 1 месяц назад

It’s much easier to build an AI agent, if all you have to do is prompt it! The backend, code execution and deployment are all handled automatically. Even non-techies can build AI agents
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It’s much easier to build an AI agent, if all you have to do is prompt it! The backend, code execution and deployment are all handled automatically. Even non-techies can build AI agents

Bindu Reddy

51,180 просмотров • 1 год назад

ANTHROPIC JUST RELEASED THE OFFICIAL PLAYBOOK FOR BUILDING A COMPANY WITH CLAUDE CODE. 30 minutes. free. from the engineers who built it. Bookmark this before you forget. CEO: 1 human. Employees: AI agents. Operations: fully automatic. The zero-headcount company is no longer a joke.
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ANTHROPIC JUST RELEASED THE OFFICIAL PLAYBOOK FOR BUILDING A COMPANY WITH CLAUDE CODE. 30 minutes. free. from the engineers who built it. Bookmark this before you forget. CEO: 1 human. Employees: AI agents. Operations: fully automatic. The zero-headcount company is no longer a joke.

Khairallah AL-Awady

1,650,241 просмотров • 1 месяц назад

21st (21stdev) is the production layer for frontier AI agents. 1.4M developers already use their platform to build AI apps, 15K+ GitHub stars - now they're making it dead simple to deploy Claude Code, Codex, and other agents to production. Congrats on the launch, sergey bunas & serafim!
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21st (21stdev) is the production layer for frontier AI agents. 1.4M developers already use their platform to build AI apps, 15K+ GitHub stars - now they're making it dead simple to deploy Claude Code, Codex, and other agents to production. Congrats on the launch, sergey bunas & serafim!

Y Combinator

33,400 просмотров • 2 месяцев назад

Temporal CEO Samar Birwadker says GitHub was designed for humans, but is now at the mercy of agents. "Agents are starting to get more and more long-lived, more asynchronous, and more mission-critical." "For example, if you pick coding agents alone, is something like GitHub was designed for humans collaborate and create [pull requests] right now." "Now a lot of code is being generated by these agents, and they're the ones creating these PRs essentially, and even code review process is being automated by other agents." "So now this entire system backend, which is being built for human consumption, is now at the mercy of these agents kind of using it for their own coordination and collaboration."
3:30

Temporal CEO Samar Birwadker says GitHub was designed for humans, but is now at the mercy of agents. "Agents are starting to get more and more long-lived, more asynchronous, and more mission-critical." "For example, if you pick coding agents alone, is something like GitHub was designed for humans collaborate and create [pull requests] right now." "Now a lot of code is being generated by these agents, and they're the ones creating these PRs essentially, and even code review process is being automated by other agents." "So now this entire system backend, which is being built for human consumption, is now at the mercy of these agents kind of using it for their own coordination and collaboration."

MTS

26,902 просмотров • 1 месяц назад

Everyone's building AI agents for crypto. Almost nobody's talking about the infrastructure problem. AI agents need to move faster than humans. But most blockchains are built for humans. Here's why that's a massive issue (and how Supra fixed it):
11:15

Everyone's building AI agents for crypto. Almost nobody's talking about the infrastructure problem. AI agents need to move faster than humans. But most blockchains are built for humans. Here's why that's a massive issue (and how Supra fixed it):

Supra

15,788 просмотров • 5 месяцев назад

i built a very fast, virtualized filesystem for ai agents built with Redis, Vercel AI SDK and just-bash agents can search and grep files really fast because it's all in redis memory
1:31

i built a very fast, virtualized filesystem for ai agents built with Redis, Vercel AI SDK and just-bash agents can search and grep files really fast because it's all in redis memory

Josh tried coding

72,964 просмотров • 2 месяцев назад

$AMZN AWS CEO pushed back on the idea that AI is killing software jobs by saying Amazon is hiring as many developers as ever. He said AI agents are “exploding” across every industry & moving faster than expected changing the developer job rather than eliminating it.
2:23

$AMZN AWS CEO pushed back on the idea that AI is killing software jobs by saying Amazon is hiring as many developers as ever. He said AI agents are “exploding” across every industry & moving faster than expected changing the developer job rather than eliminating it.

Shay Boloor

208,245 просмотров • 1 месяц назад

There's an insane arbitrage opportunity right now with OpenClaw. You can have it spawn sub-agents to go out and apply to proposals on Upwork with the fully finished, complete project already built out for you. This can happen all at once in parallel if you give OpenClaw the ability to spawn sub-agents inside of their own computers on Orgo.
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There's an insane arbitrage opportunity right now with OpenClaw. You can have it spawn sub-agents to go out and apply to proposals on Upwork with the fully finished, complete project already built out for you. This can happen all at once in parallel if you give OpenClaw the ability to spawn sub-agents inside of their own computers on Orgo.

nick vasilescu

360,233 просмотров • 4 месяцев назад

UGC Agent An AI agent that generates video content end-to-end using x402 micropayments and Vercel's Workflow Kit You give it a topic. It researches, writes a script, and creates the video, paying for every tool it needs along the way Here's how it works 🧵👇
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UGC Agent An AI agent that generates video content end-to-end using x402 micropayments and Vercel's Workflow Kit You give it a topic. It researches, writes a script, and creates the video, paying for every tool it needs along the way Here's how it works 🧵👇

Ash

12,342 просмотров • 6 месяцев назад

Autonomous AI agents can’t afford a memory problem. After OpenClaw, insane numbers of autonomous agents are coming online, but all of them have a memory layer that's breaking. I have been playing around with SureThing these days. It is an autonomous AI agent designed with a native memory layer. → it learns your patterns → integrates with 1000+ apps → fully autonomous They actually benchmarked memory depth. SureThing: 84.8, ChatGPT: 40, OpenClaw: 60. The gap speaks for itself. SureThing is invitation-only. The crazy part is that you have to talk to SureThing agent itself to get the invite code. The onboarding is the product demo. You feel the memory and judgment before you even have an account. Try it here: Partnered with SureThing for this post. Thanks to the team for the support.
2:06

Autonomous AI agents can’t afford a memory problem. After OpenClaw, insane numbers of autonomous agents are coming online, but all of them have a memory layer that's breaking. I have been playing around with SureThing these days. It is an autonomous AI agent designed with a native memory layer. → it learns your patterns → integrates with 1000+ apps → fully autonomous They actually benchmarked memory depth. SureThing: 84.8, ChatGPT: 40, OpenClaw: 60. The gap speaks for itself. SureThing is invitation-only. The crazy part is that you have to talk to SureThing agent itself to get the invite code. The onboarding is the product demo. You feel the memory and judgment before you even have an account. Try it here: Partnered with SureThing for this post. Thanks to the team for the support.

Pratham

80,634 просмотров • 3 месяцев назад

Marc Andreessen: AI coding doesn’t eliminate programmers — it redefines them. The job is no longer typing code line by line, it’s orchestrating 10 coding bots in parallel, arguing with them, debugging their output, changing the spec, and pushing them toward the right result. But here’s the catch: if you don’t understand how to write code yourself, you can’t evaluate what the AI gives you. The next layer of programming isn’t writing scripts — it’s supervising AI that writes them. Today’s best programmers spend their day jumping between terminals, managing multiple coding bots, fixing mistakes, and refining instructions. The irony? You still need deep fundamentals, because without them, you won’t know when the AI is wrong. The job of the programmer has changed. Now it’s about arguing with coding bots, debugging AI-generated code, and understanding why something doesn’t work or isn’t fast enough. AI abstracts the work — but only people who truly understand code can tell if the abstraction is doing the right thing. Programmers aren’t going away — they’re becoming 10x, 100x, even 1,000x more productive. Tasks are changing, the job is changing, but humans are still overseeing the process, evaluating results, fixing errors, and making judgment calls. AI changes how we code, not who is responsible. The future programmer isn’t replaced by AI — they’re upgraded by it. You still need to learn how to write and understand code, because when the AI gets it wrong, humans are the ones who have to know why. That up-leveling of capability is the real revolution.
1:50

Marc Andreessen: AI coding doesn’t eliminate programmers — it redefines them. The job is no longer typing code line by line, it’s orchestrating 10 coding bots in parallel, arguing with them, debugging their output, changing the spec, and pushing them toward the right result. But here’s the catch: if you don’t understand how to write code yourself, you can’t evaluate what the AI gives you. The next layer of programming isn’t writing scripts — it’s supervising AI that writes them. Today’s best programmers spend their day jumping between terminals, managing multiple coding bots, fixing mistakes, and refining instructions. The irony? You still need deep fundamentals, because without them, you won’t know when the AI is wrong. The job of the programmer has changed. Now it’s about arguing with coding bots, debugging AI-generated code, and understanding why something doesn’t work or isn’t fast enough. AI abstracts the work — but only people who truly understand code can tell if the abstraction is doing the right thing. Programmers aren’t going away — they’re becoming 10x, 100x, even 1,000x more productive. Tasks are changing, the job is changing, but humans are still overseeing the process, evaluating results, fixing errors, and making judgment calls. AI changes how we code, not who is responsible. The future programmer isn’t replaced by AI — they’re upgraded by it. You still need to learn how to write and understand code, because when the AI gets it wrong, humans are the ones who have to know why. That up-leveling of capability is the real revolution.

Ian Miles Cheong

911,556 просмотров • 4 месяцев назад

AI agents just got simple. Like really simple. Building AI agents is now accessible to everyone, without the need for coding, complex setups, or a full tech team. A groundbreaking platform is revolutionizing this narrative. Meet Carla Torres the easiest way to build, manage, and scale AI agents. What makes Airia different? It simplifies everything. ✔️ No technical background needed ✔️ Works with any model GPT, Claude, Gemini, Mistral & more ✔️ Enterprise-grade security ✔️ Built for creators, teams & companies Transform an idea into a functional AI agent in minutes. The part that amazed everyone Airia offers 2,500+ pre-built agent templates. Search. Pick one. Customize. No blank screens. No starting from scratch. Just instant value. This is why founders, creators, engineers, and enterprises are enthusiastically joining the Airia Community every day. Why it matters AI agents are shaping the future of work. Airia makes it easy, fast, and secure for anyone to bring AI to life. If AI agents are part of the 2025 vision, this platform is the perfect place to start. 🔗 Explore the Airia Community 2,500+ ready-to-use agents are waiting at #Airia #AIAgents #AIPlatform #AICommunity #AIForBusiness #AgenticAI #NoCodeAI
6:35

AI agents just got simple. Like really simple. Building AI agents is now accessible to everyone, without the need for coding, complex setups, or a full tech team. A groundbreaking platform is revolutionizing this narrative. Meet Carla Torres the easiest way to build, manage, and scale AI agents. What makes Airia different? It simplifies everything. ✔️ No technical background needed ✔️ Works with any model GPT, Claude, Gemini, Mistral & more ✔️ Enterprise-grade security ✔️ Built for creators, teams & companies Transform an idea into a functional AI agent in minutes. The part that amazed everyone Airia offers 2,500+ pre-built agent templates. Search. Pick one. Customize. No blank screens. No starting from scratch. Just instant value. This is why founders, creators, engineers, and enterprises are enthusiastically joining the Airia Community every day. Why it matters AI agents are shaping the future of work. Airia makes it easy, fast, and secure for anyone to bring AI to life. If AI agents are part of the 2025 vision, this platform is the perfect place to start. 🔗 Explore the Airia Community 2,500+ ready-to-use agents are waiting at #Airia #AIAgents #AIPlatform #AICommunity #AIForBusiness #AgenticAI #NoCodeAI

Aakash Verma

40,334 просмотров • 6 месяцев назад

Bash is all you need! Which is why I'm introducing my holiday project: just-bash just-bash is a pretty complete implementation of bash in TypeScript designed to be used as a bash tool by AI agents. Because it turns out agents love exploring data via shell scripts, even beyond coding. It comes with grep, sed, awk and the 99th percentile features that an agent like Claude Code or Cursor would use. In fact, Claude Code can use it for secure bash execution. In the package - A bash-tool for AI SDK - A binary for use by yourself or your coding agents - An overlay filesystem to feed files to your agent securely - A Vercel Sandbox compatible API, so you can quickly upgrade to a real VM if you need to run binaries - An example AI agent that explores the just-bash code base using just-bash - I imported the Oils shell bash compatibility suite and just-bash passes a very good chunk What is interesting about this codebase: It was essentially entirely written by Opus 4.5. Coding agents love bash and they are good at reproducing it. They are also great at text-book recursive descent parsers and AST tweet-walk interpreters. That said, it is, like, a lot of code and I didn't read it all 😅. This is very much a hack, but it also seems to be _really_ useful. I haven't really found anything agents want to use that it doesn't support and it's fast and secure (caveats apply). It doesn't have write access to your computer and the filesystem is given a root that the agent cannot escape from. Find it at Related: Our recent blog post how we migrated our data analysis agent to bash tools and achieved incredible quality improvements The video shows the example agent investigating the just-bash code base
1:47

Bash is all you need! Which is why I'm introducing my holiday project: just-bash just-bash is a pretty complete implementation of bash in TypeScript designed to be used as a bash tool by AI agents. Because it turns out agents love exploring data via shell scripts, even beyond coding. It comes with grep, sed, awk and the 99th percentile features that an agent like Claude Code or Cursor would use. In fact, Claude Code can use it for secure bash execution. In the package - A bash-tool for AI SDK - A binary for use by yourself or your coding agents - An overlay filesystem to feed files to your agent securely - A Vercel Sandbox compatible API, so you can quickly upgrade to a real VM if you need to run binaries - An example AI agent that explores the just-bash code base using just-bash - I imported the Oils shell bash compatibility suite and just-bash passes a very good chunk What is interesting about this codebase: It was essentially entirely written by Opus 4.5. Coding agents love bash and they are good at reproducing it. They are also great at text-book recursive descent parsers and AST tweet-walk interpreters. That said, it is, like, a lot of code and I didn't read it all 😅. This is very much a hack, but it also seems to be _really_ useful. I haven't really found anything agents want to use that it doesn't support and it's fast and secure (caveats apply). It doesn't have write access to your computer and the filesystem is given a root that the agent cannot escape from. Find it at Related: Our recent blog post how we migrated our data analysis agent to bash tools and achieved incredible quality improvements The video shows the example agent investigating the just-bash code base

Malte Ubl

124,713 просмотров • 5 месяцев назад

Prism is about to supercharge @OpenClaw agents. AI agents are getting smarter. But when it comes to financial asset resolution, they’re still guessing. Here’s a look inside the Prism API dashboard 👇
3:17

Prism is about to supercharge @OpenClaw agents. AI agents are getting smarter. But when it comes to financial asset resolution, they’re still guessing. Here’s a look inside the Prism API dashboard 👇

Strykr.ai

20,125 просмотров • 3 месяцев назад

CLAUDE CODE JUST SHIPPED THE FEATURE THAT SOLVES THE BIGGEST PROBLEM EVERY BUILDER HAS WITH AI AGENTS. The problem: Claude starts a task, gets distracted by a sub-problem, goes down a rabbit hole, and never finishes the original thing you asked for. The solution: /goal One command. You set the goal at the start of the session. Claude now has a north star it checks against every action it takes. Not just at the beginning. Throughout the entire session. Every time Claude is about to do something it asks: does this action move me toward the goal the user set or am I drifting? If it is drifting it corrects. If it completes a sub-task it returns to the primary goal. If it hits a blocker it reports back instead of spending 45 minutes solving the wrong problem. This sounds like a small feature. It is not. The reason most people do not trust Claude Code for long autonomous runs is not capability. It is reliability. A Claude Code session that reliably finishes what it started is worth 10 times more than one that is more capable but wanders. /goal is the feature that makes long autonomous sessions reliable. Set the goal. Let it run. Come back to a finished result. Not a result that got 70% done before Claude decided the sub-problem was more interesting. Done. The builders running overnight agent sessions are going to use this command on everything from today forward. Bookmark this. Follow CyrilXBT for every Claude Code feature the moment it ships.
0:24

CLAUDE CODE JUST SHIPPED THE FEATURE THAT SOLVES THE BIGGEST PROBLEM EVERY BUILDER HAS WITH AI AGENTS. The problem: Claude starts a task, gets distracted by a sub-problem, goes down a rabbit hole, and never finishes the original thing you asked for. The solution: /goal One command. You set the goal at the start of the session. Claude now has a north star it checks against every action it takes. Not just at the beginning. Throughout the entire session. Every time Claude is about to do something it asks: does this action move me toward the goal the user set or am I drifting? If it is drifting it corrects. If it completes a sub-task it returns to the primary goal. If it hits a blocker it reports back instead of spending 45 minutes solving the wrong problem. This sounds like a small feature. It is not. The reason most people do not trust Claude Code for long autonomous runs is not capability. It is reliability. A Claude Code session that reliably finishes what it started is worth 10 times more than one that is more capable but wanders. /goal is the feature that makes long autonomous sessions reliable. Set the goal. Let it run. Come back to a finished result. Not a result that got 70% done before Claude decided the sub-problem was more interesting. Done. The builders running overnight agent sessions are going to use this command on everything from today forward. Bookmark this. Follow CyrilXBT for every Claude Code feature the moment it ships.

CyrilXBT

19,526 просмотров • 28 дней назад