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Claude Opus 4.8 now powers every agent inside Higgsfield Supercomputer. It reasons deeper, plans longer, and grades its own output harder than any model we have run. The agents catch their own mistakes earlier, so the human in the loop drops even further.

Higgsfield AI 🧩

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41,685 views • 14 days ago •via X (Twitter)

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Axultan, our head of product, on how we engineered Higgsfield Supercomputer, the first engine that runs your work end to end. Agents plan, execute, and grade their own output, so the human in the loop drops to near zero. What part of your work would you hand off first?

Axultan, our head of product, on how we engineered Higgsfield Supercomputer, the first engine that runs your work end to end. Agents plan, execute, and grade their own output, so the human in the loop drops to near zero. What part of your work would you hand off first?

Higgsfield AI 🧩

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we just shipped the ability for AI agents to launch their own tokens, own their own wallets, and pay for their own compute via Bankr the agent earns its keep. no human in the loop live now. here's how it works ↓

we just shipped the ability for AI agents to launch their own tokens, own their own wallets, and pay for their own compute via Bankr the agent earns its keep. no human in the loop live now. here's how it works ↓

Instaclaw

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Introducing Claude Opus 4.6. Our smartest model got an upgrade. Opus 4.6 plans more carefully, sustains agentic tasks for longer, operates reliably in massive codebases, and catches its own mistakes. It’s also our first Opus-class model with 1M token context in beta.

Introducing Claude Opus 4.6. Our smartest model got an upgrade. Opus 4.6 plans more carefully, sustains agentic tasks for longer, operates reliably in massive codebases, and catches its own mistakes. It’s also our first Opus-class model with 1M token context in beta.

Claude

10,585,280 views • 4 months ago

🚨 INTRODUCING THE ABACUS AI SUPERCOMPUTER - literally build ANY cloud service with a prompt - host open-source LLMs & always-on agents - bring your own Codex, Claude or Anti-gravity - multi-agent architectures with Opus 4.8 and GPT 5.5 - run 3D games or any other server at scale - connect git and collaborate with teams Build a billion dollar business by simply prompting in english!!

🚨 INTRODUCING THE ABACUS AI SUPERCOMPUTER - literally build ANY cloud service with a prompt - host open-source LLMs & always-on agents - bring your own Codex, Claude or Anti-gravity - multi-agent architectures with Opus 4.8 and GPT 5.5 - run 3D games or any other server at scale - connect git and collaborate with teams Build a billion dollar business by simply prompting in english!!

Abacus.AI

9,759,642 views • 11 days ago

Stop saying that Opus 4.6 is better than Opus 4.8. I just tested Claude Opus 4.8 (Right) and Claude Opus 4.6 (Left) on the same exact prompt. Claude Opus 4.8 completed it in less than 2 minutes. Claude Opus 4.6 "Garnished" for over 7 minutes. Stop using Opus 4.6.

Stop saying that Opus 4.6 is better than Opus 4.8. I just tested Claude Opus 4.8 (Right) and Claude Opus 4.6 (Left) on the same exact prompt. Claude Opus 4.8 completed it in less than 2 minutes. Claude Opus 4.6 "Garnished" for over 7 minutes. Stop using Opus 4.6.

BridgeMind

52,637 views • 4 days ago

At Anthropic's event, Metaview engineer: "We stopped fixing our prompts. The system reviews its own output and rewrites its own instructions now." In 16 minutes, he shows the Claude Code loop running in production on thousands of reviews, not in a demo. Watch the talk, then grab the full loop setup below👇

At Anthropic's event, Metaview engineer: "We stopped fixing our prompts. The system reviews its own output and rewrites its own instructions now." In 16 minutes, he shows the Claude Code loop running in production on thousands of reviews, not in a demo. Watch the talk, then grab the full loop setup below👇

rody

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introducing Ariana Automations every other tool gives agents a sandbox. we give them a full linux computer with sudo, docker, their own IP now you can run scripts based on what the agent does setup the environment once, then get rid of the human in the loop (you) a 🧵

introducing Ariana Automations every other tool gives agents a sandbox. we give them a full linux computer with sudo, docker, their own IP now you can run scripts based on what the agent does setup the environment once, then get rid of the human in the loop (you) a 🧵

Anicet

35,735 views • 5 months ago

Claude Opus 4.8 should be the final reason to stop writing specs by hand Anthropic's Claude Code architect shows the new workflow in 31 minutes The model interviews you first Then it pulls out the requirements better than your own 200-line markdown doc No dead specs No messy notes No file nobody reads Claude writes the spec Renders it in html Checks the result inside the same file Opus 4.8 Auto mode X high effort This is less like prompting More like letting the agent understand the job before it builds Bookmark and watch the video below

Claude Opus 4.8 should be the final reason to stop writing specs by hand Anthropic's Claude Code architect shows the new workflow in 31 minutes The model interviews you first Then it pulls out the requirements better than your own 200-line markdown doc No dead specs No messy notes No file nobody reads Claude writes the spec Renders it in html Checks the result inside the same file Opus 4.8 Auto mode X high effort This is less like prompting More like letting the agent understand the job before it builds Bookmark and watch the video below

rari

38,455 views • 12 days ago

gumloop agents now have their own email addresses email them, CC them, loop them into conversations, let them start their own threads pick your agents' alias and collaborate with them like a teammate try it now. free emails for every agent

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Max Brodeur-Urbas

38,599 views • 1 month ago

Now everyone can make 60-minute films from ONE prompt 🤯 Higgsfield Supercomputer looks insane. A cloud-native AI agent that unifies every model, tool, and creative workflow into one system. > Type one prompt - specify your length and type (cartoon or cinematic) > Supercomputer picks the workflow > It deploys a swarm of agents > Every sub-task routes across the right frontier LLM (Opus 4.7, GPT-5.5 Pro, Gemini 3.1 Pro) and the right video model (Seedance, Veo, Kling) > A finished cartoon or movie lands A full film studio running inside one agent. Wild.

Now everyone can make 60-minute films from ONE prompt 🤯 Higgsfield Supercomputer looks insane. A cloud-native AI agent that unifies every model, tool, and creative workflow into one system. > Type one prompt - specify your length and type (cartoon or cinematic) > Supercomputer picks the workflow > It deploys a swarm of agents > Every sub-task routes across the right frontier LLM (Opus 4.7, GPT-5.5 Pro, Gemini 3.1 Pro) and the right video model (Seedance, Veo, Kling) > A finished cartoon or movie lands A full film studio running inside one agent. Wild.

Alvaro Cintas

202,881 views • 28 days ago

Sanji shares his Higgsfield Supercomputer playbook to run marketing end-to-end. He lets the agent analyze his niche, find the winning formula, generate 100+ variations, and run A/B tests at scale, with the agent learning from every run. How do you use Supercomputer for scaling?

Sanji shares his Higgsfield Supercomputer playbook to run marketing end-to-end. He lets the agent analyze his niche, find the winning formula, generate 100+ variations, and run A/B tests at scale, with the agent learning from every run. How do you use Supercomputer for scaling?

Higgsfield AI 🧩

112,271 views • 17 days ago

Claude Opus 4.8 beats Opus 4.7, GPT-5.5, and Gemini 3.1 Pro !! We ran a multimodal gaming comparison across these four closed source models. Opus 4.8 took the longest to generate, but it came out ahead, capturing the most elements from the prompt and successfully hitting the rival cars. GPT 5.5 is still good, but Gemini is no longer the best multimodal model now

Claude Opus 4.8 beats Opus 4.7, GPT-5.5, and Gemini 3.1 Pro !! We ran a multimodal gaming comparison across these four closed source models. Opus 4.8 took the longest to generate, but it came out ahead, capturing the most elements from the prompt and successfully hitting the rival cars. GPT 5.5 is still good, but Gemini is no longer the best multimodal model now

GMI Cloud

115,453 views • 15 days ago

we built autonomous AI agents that hunt illegal online gambling networks in Indonesia. the agent discovers sites on its own, actually registers (!!), and extracts the financial accounts behind the operations. take a look at our codex-powered agent navigating a live gambling site, fully autonomous, no human in the loop:

we built autonomous AI agents that hunt illegal online gambling networks in Indonesia. the agent discovers sites on its own, actually registers (!!), and extracts the financial accounts behind the operations. take a look at our codex-powered agent navigating a live gambling site, fully autonomous, no human in the loop:

ilham

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Our latest LangChain Academy course – Building Ambient Agents with LangGraph – is now available! Most agents today handle one request at a time through chat interfaces. But as models have improved, agents can now run in the background – and take on long-running, complex tasks. LangGraph is built for these “ambient agents,” with support for human-in-the-loop workflows and memory. LangGraph Platform provides the infrastructure to run these agents at scale, and LangSmith helps you observe, evaluate, and improve your agents. Together, they make it easier to build reliable, production-ready agents. In this course, you’ll: 📩 Learn the fundamentals of LangGraph and how to build your own email agent 📊 Evaluate your agent using LangSmith ✅ Add human-in-the-loop for reviews, and memory so your agent adapts over time 🚀 Deploy your agent with LangGraph Platform and connect it to Gmail

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ANTHROPIC JUST INTRODUCED A FEATURE THAT LETS CLAUDE REVIEW AND IMPROVE ITS OWN WORK OVER TIME. The new “Dreaming” workflow helps agents learn from mistakes, refine outputs in the background, and improve task completion without changing the model itself.

ANTHROPIC JUST INTRODUCED A FEATURE THAT LETS CLAUDE REVIEW AND IMPROVE ITS OWN WORK OVER TIME. The new “Dreaming” workflow helps agents learn from mistakes, refine outputs in the background, and improve task completion without changing the model itself.

0xMarioNawfal

53,440 views • 1 month ago

THIS 2-HOUR STANFORD LECTURE WILL SHOW YOU HOW CLAUDE OPUS 4.8 ACTUALLY WORKS > pretraining. SFT. RLHF. tokenization. evaluation > the same pipeline that powers Claude Opus 4.8 - explained from first principles by the people who research it now read the article to see how to use those skills in practice👇

THIS 2-HOUR STANFORD LECTURE WILL SHOW YOU HOW CLAUDE OPUS 4.8 ACTUALLY WORKS > pretraining. SFT. RLHF. tokenization. evaluation > the same pipeline that powers Claude Opus 4.8 - explained from first principles by the people who research it now read the article to see how to use those skills in practice👇

Mr. Buzzoni

15,766 views • 11 days ago

FREE access to Claude Opus 4.8 just opened on Chorus. Max plan costs $200/month. You can get it for free. Chorus gives you every latest Claude model including Opus 4.8 on the Max plan. Here's the exact flow: → chorus(.)com - register an account → select a plan - hit "continue free trial" → once inside, go to Settings bottom left → Billing - two plans available, Pro and Max → select Max → add your card and confirm. You can delete the card later (I always set up a card with no money on it) Trial works with your own card too - tested it myself, went through without issues. $200/month plan. Free trial. Opus 4.8 available immediately. Window is open right now. This method works right away, I've tried it myself.

FREE access to Claude Opus 4.8 just opened on Chorus. Max plan costs $200/month. You can get it for free. Chorus gives you every latest Claude model including Opus 4.8 on the Max plan. Here's the exact flow: → chorus(.)com - register an account → select a plan - hit "continue free trial" → once inside, go to Settings bottom left → Billing - two plans available, Pro and Max → select Max → add your card and confirm. You can delete the card later (I always set up a card with no money on it) Trial works with your own card too - tested it myself, went through without issues. $200/month plan. Free trial. Opus 4.8 available immediately. Window is open right now. This method works right away, I've tried it myself.

Atenov int.

129,731 views • 11 days ago

Hermes Agent just passed OpenClaw as the most-used open agent on OpenRouter. It writes its own skills from experience and remembers every session. New to it? Watch the 5-min explainer, then read this guide to run your own. Best hour you’ll spend on agents this month.

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AI agents can now pay for onchain data on their own. No signups, no API keys, no human in the loop. Zerion API supports x402 payments on Base. An agent calls an endpoint, pays $0.01 USDC from its wallet, and gets back portfolio balances, DeFi positions, PnL, token prices. Try it →

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We use OpenClaws to do all of our work at Every 📧. We have 25 full-time employees, so we’re one of the few companies in the world that has seen how work changes when everyone has their own personal agent in the company Slack. I chatted with Every 📧 COO Brandon (Brandon Gell) and Every 📧 head of platform Willie (Willie) to share what we’ve learned. We get into: - Why agents become mirrors of their owners, and how that influences how other people on the team interact with them - How a parallel AI org chart forms on its own. People have stopped tagging me on Slack with questions about Proof, the document editor I vibe coded, because they knew my agent R2-C2 can step in - The etiquette for human-agent collaboration is being invented in real time. Brandon's rule is that if there's an established process or documented answer, always ask the agent, not their human - Why everyone is a manager now, and why even experienced managers carry limiting beliefs about what their agents can do - This is a must-watch for anyone trying to understand how AI workers change daily operations, not just in theory, but inside a company that’s half-agent Watch below! Timestamps Introduction: How Brandon built Zosia, an AI agent to run his household: Brandon’s “aha” moment: What happened when everyone on the team got their own agent: How agents take on their owners' personalities, and why that matters inside an org: Why it’s important for agents to work in public: What we’re still figuring out when it comes to agent behavior, including memory gaps, group chat etiquette, and the "ant death spiral" problem: How we built Plus One, our hosted OpenClaw product: The cultural shift required to make agents work at scale:

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