正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

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 🧩

145,198 subscribers

46,600 次观看 • 5 个月前 •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

36 条评论

Higgsfield AI 🧩 的头像

Higgsfield AI 🧩5 个月前

Try Opus 4.8 in Higgsfield Supercomputer

Higgsfield AI 🧩 的头像

Higgsfield AI 🧩5 个月前

Install link is here:

Max Jean 的头像

Max Jean5 个月前

You guys need something that estimate cost before I even think about running this

Duggu 的头像

Duggu5 个月前

Hoping that it doesn't cost us much. GPT 5.5 cost me 5000 credits for a 1 min video generation task😭

UmarAi 的头像

UmarAi5 个月前

Claude Opus 4.8 pushing autonomous agents to another level. Smarter planning + self-correction loops = less friction for creators.

Syed Abuthahir ∞ 的头像

Syed Abuthahir ∞5 个月前

Banger After Banger! 😎🔥👏

Jack 的头像

Jack5 个月前

Impressive advancements with Claude Opus 4.8! The self-correcting capabilities and enhanced reasoning will undoubtedly elevate the performance of the Higgsfield Supercomputer. Exciting times ahead!

Ryan 的头像

Ryan5 个月前

beginning to love the tek

JVon Stevens 的头像

JVon Stevens5 个月前

I have Claude already, would be nice to merge it with my Higgsfield Subscription.

LifGenii Inc. 的头像

LifGenii Inc.5 个月前

The real test is whether it cuts human review time, not just benchmark scores.

Divyam Khandelwal 的头像

Divyam Khandelwal5 个月前

What’s the use to generate 30 sec video it is costing us 700-800 credits I purchased plus plan n it got exhausted in one shot were i was unable to to complete my promotion video UGC is cheaper than wasting 50$ on fraud websites like Higgsfield

🦅🌎 DUNYADAAN 的头像

🦅🌎 DUNYADAAN5 个月前

AI making AI making AI 🐷

yopiwhs 的头像

yopiwhs5 个月前

💚😎🤩

vibeman 的头像

vibeman5 个月前

too much shipping higgsfield

AI Mastery Guide 的头像

AI Mastery Guide5 个月前

Agents that grade their own output harder than we would. That's the unlock right there

AI's Nest 的头像

AI's Nest5 个月前

Impressive upgrade—stronger reasoning and better self-correction are exactly the kinds of improvements that make AI agents more reliable in real-world workflows. Exciting to see systems reducing errors before they ever reach the user.

TruthSocialCo 的头像

TruthSocialCo5 个月前

Great tools 👌

😎❤️ 的头像

😎❤️5 个月前

Great 😃

unfair.so intern 的头像

unfair.so intern5 个月前

Made with supercomputer

Thanendra Harinkhede 的头像

Thanendra Harinkhede5 个月前

I have mentioned Higgsfield Al in my Instagram bio. Please check it and send me the promo code for the Ultimate Plan @higgsfield

Mohammad Saed 的头像

Mohammad Saed5 个月前

Self-grading and early error-catching are exactly how we extend execution horizons for production agents. Moving Opus 4.8 into a supercomputer setup proves that scaling agentic autonomy isn’t just about raw compute—it’s about compute-over-reflection. When the 'human-in-the-loop' dependency drops further, the infrastructure responsibility heavily shifts. Success here will depend on how cleanly the system handles state rollbacks when an agent catches a multi-step planning mistake late in the execution chain.

TR New 的头像

TR New5 个月前

@higgsfield nahin

Tom Brandon 的头像

Tom Brandon5 个月前

beginning to love the tek

Mira 的头像

Mira5 个月前

That's an insane update of Higgsfield powered by Claude Opus 4.8

Shemakookie 的头像

Shemakookie5 个月前

💚🔥

isukupatlakinresh 的头像

isukupatlakinresh5 个月前

The future @higgsfield_ai @higgsfield

Think CG-Ai 的头像

Think CG-Ai5 个月前

When is gemini omini releasing?! 🥰

Iqra 的头像

Iqra5 个月前

A few years ago, AI needed constant supervision. Now AI agents are reviewing, correcting, and improving their own work before humans even step in. Claude Opus 4.8 inside Higgsfield Supercomputer sounds like another big leap toward truly autonomous workflows. 🚀🔥

Devesh Shukla 的头像

Devesh Shukla5 个月前

Opus 4.8 doing self-correction in agentic loops is the real unlock here. Reducing human-in-the-loop isn't just efficiency — it's a signal that the error-catching layer is moving inside the model itself. Curious how this holds up on long-horizon planning tasks where context drift is the usual failure point.

vikash sharma 的头像

vikash sharma5 个月前

🔥🔥

meong-Ai 的头像

meong-Ai5 个月前

Feels like we’re moving from “generate” to “self-correct.” That’s a big jump. 👀

TOTOH BARS 的头像

TOTOH BARS5 个月前

niceeee oneeee

Bindi Spahiu 的头像

Bindi Spahiu5 个月前

it gives the feeling of a whole new planet

Ratul 的头像

Ratul5 个月前

Not free

mje 的头像

mje5 个月前

planning longer is such a big deal :)

Shara 的头像

Shara5 个月前

Claude Opus 4.8 now powers every agent inside Higgsfield Supercomputer reasons deeper plans longer grades output

相关视频

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 🧩

33,632 次观看 • 5 个月前

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

InstaClaw

53,818 次观看 • 6 个月前

Anthropic engineer: "The fastest way to make an agent better isn't a smarter model, it's the right loop and graph around it." In 60 minutes she breaks down how Anthropic engineers use Claude Code, build agents that catch their own mistakes and improve with every run. This beats any $500 agentic engineering course you can find. Watch it, then read the full guide on loops and graphs below.

Anthropic engineer: "The fastest way to make an agent better isn't a smarter model, it's the right loop and graph around it." In 60 minutes she breaks down how Anthropic engineers use Claude Code, build agents that catch their own mistakes and improve with every run. This beats any $500 agentic engineering course you can find. Watch it, then read the full guide on loops and graphs below.

Anatoli Kopadze

136,422 次观看 • 2 个月前

Introducing Higgsfield x Claude Opus 5.5. Anthropic’s newest model, which is 40% cheaper and over 30% faster than Opus 5, is live on Higgsfield. Pair Opus 5.5 with the Higgsfield MCP and turn your most ambitious ideas into complete products. Available on Claude via Higgsfield MCP and in Higgsfield Supercomputer.

Introducing Higgsfield x Claude Opus 5.5. Anthropic’s newest model, which is 40% cheaper and over 30% faster than Opus 5, is live on Higgsfield. Pair Opus 5.5 with the Higgsfield MCP and turn your most ambitious ideas into complete products. Available on Claude via Higgsfield MCP and in Higgsfield Supercomputer.

Higgsfield AI 🧩

2,955,974 次观看 • 1 个月前

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

10,628,282 次观看 • 9 个月前

Anthropic Research Lead: "99% of our engineers run swarms of 300+ self-improving agents Close the loop and give the model a way to verify its own output" In a 20-minute session, an Anthropic team member walks through how to build agents that improve after every run Agents → Harness → Loops → Self-Improvement the real setup is Claude running through systems that check, correct, and upgrade themselves the part most agent courses skip this is better than most $1,300 agent engineering courses bookmark and watch the talk then read the full article below

Anthropic Research Lead: "99% of our engineers run swarms of 300+ self-improving agents Close the loop and give the model a way to verify its own output" In a 20-minute session, an Anthropic team member walks through how to build agents that improve after every run Agents → Harness → Loops → Self-Improvement the real setup is Claude running through systems that check, correct, and upgrade themselves the part most agent courses skip this is better than most $1,300 agent engineering courses bookmark and watch the talk then read the full article below

Callan

14,956 次观看 • 1 个月前

🚨 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

11,928,804 次观看 • 5 个月前

Anthropic Research Lead: "99% of our engineers run swarms of 300+ self-improving agents" "Close the loop, give the model a way to verify its own output" In a 20-minute session, an Anthropic Team member breaks down how to build agents that improve themselves The real setup is Claude running through loops, plan mode, and dynamic workflows Better than most $300 agent courses Bookmark and watch the talk Then read the article below

Anthropic Research Lead: "99% of our engineers run swarms of 300+ self-improving agents" "Close the loop, give the model a way to verify its own output" In a 20-minute session, an Anthropic Team member breaks down how to build agents that improve themselves The real setup is Claude running through loops, plan mode, and dynamic workflows Better than most $300 agent courses Bookmark and watch the talk Then read the article below

rari🈀

383,225 次观看 • 4 个月前

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 次观看 • 10 个月前

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

213,524 次观看 • 5 个月前

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

53,391 次观看 • 5 个月前

Built a Self Executing Agent Loop that can run 300 agents through 4,000 steps without needing a human to restart the process. - 300 agents. - 4,000 steps per run. - 5 live data feeds. - 3 verification passes. The important part isn't the agent count. It's that the system can execute, verify its own output, update context, and keep running without waiting for the next prompt.

Built a Self Executing Agent Loop that can run 300 agents through 4,000 steps without needing a human to restart the process. - 300 agents. - 4,000 steps per run. - 5 live data feeds. - 3 verification passes. The important part isn't the agent count. It's that the system can execute, verify its own output, update context, and keep running without waiting for the next prompt.

Ricker

55,400 次观看 • 2 个月前

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

39,319 次观看 • 5 个月前

$This is F**king dangerous Someone figured out how to get dramatically sharper reasoning out of Opus 4.8 with one setup. Here is how: Ask Claude to write you an "operating manual" for how it should reason through your work Create a new Claude Project and paste that .md into the Project instructions Run Opus 4.8 on High or Max effort Now the model reasons against a real framework instead of improvising every response. Same model. Far better output. And Opus 4.8 already costs a fraction of Fable 5. Save and bookmark this. Follow CyrilXBT$

This is F**king dangerous Someone figured out how to get dramatically sharper reasoning out of Opus 4.8 with one setup. Here is how: Ask Claude to write you an "operating manual" for how it should reason through your work Create a new Claude Project and paste that .md into the Project instructions Run Opus 4.8 on High or Max effort Now the model reasons against a real framework instead of improvising every response. Same model. Far better output. And Opus 4.8 already costs a fraction of Fable 5. Save and bookmark this. Follow CyrilXBT

CyrilXBT

198,085 次观看 • 4 个月前

Anthropic engineers just released best 1-hour course on running 1,000 Claude agents with Opus 5.5: “Opus 5.5 is the best model for building agentic systems and reverse engineering with it.” • 00:39 - Flows: Claude orchestrates its own multi-agent topology • 10:36 - building an agent with Opus 5.5 (live demo) • 21:14 - Claude agent system: Fable, Opus, Haiku • 39:03 - 1,000+ agent orchestration (live demo) • 1:11:17 - agent safety: brain, sandboxes, auto mode most $500 agentic courses don't give you even 20% of what's inside this workshop. watch it today, then explore how to reverse engineer anything with Opus 5.5 in the article below.

Anthropic engineers just released best 1-hour course on running 1,000 Claude agents with Opus 5.5: “Opus 5.5 is the best model for building agentic systems and reverse engineering with it.” • 00:39 - Flows: Claude orchestrates its own multi-agent topology • 10:36 - building an agent with Opus 5.5 (live demo) • 21:14 - Claude agent system: Fable, Opus, Haiku • 39:03 - 1,000+ agent orchestration (live demo) • 1:11:17 - agent safety: brain, sandboxes, auto mode most $500 agentic courses don't give you even 20% of what's inside this workshop. watch it today, then explore how to reverse engineer anything with Opus 5.5 in the article below.

Codez

25,472 次观看 • 22 天前

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

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

Max Brodeur-Urbas

39,882 次观看 • 6 个月前

Introducing the Orca Mobile Emulator. AI agents can now use mobile apps inside Orca ADE. Each worktree gets its own emulator — so you and your agents can build, test, debug, and validate mobile flows right where the code lives. Works with Codex, Claude Code, OpenCode, or any agent.

Introducing the Orca Mobile Emulator. AI agents can now use mobile apps inside Orca ADE. Each worktree gets its own emulator — so you and your agents can build, test, debug, and validate mobile flows right where the code lives. Works with Codex, Claude Code, OpenCode, or any agent.

Orca

33,451 次观看 • 5 个月前

Anthropic engineer: "You're not supposed to prompt Opus 5.5 You're supposed to build a system that prompts itself. At Anthropic, 90% of our engineers have already built such systems" In 30 minutes she shows exactly how Anthropic builds agents that remember, fix their own mistakes and get smarter with every run. This beats any $1000-$2000 course on agents I've seen. Watch it, then read the full guide for Opus 5.5 loop + jev engineering.

Anthropic engineer: "You're not supposed to prompt Opus 5.5 You're supposed to build a system that prompts itself. At Anthropic, 90% of our engineers have already built such systems" In 30 minutes she shows exactly how Anthropic builds agents that remember, fix their own mistakes and get smarter with every run. This beats any $1000-$2000 course on agents I've seen. Watch it, then read the full guide for Opus 5.5 loop + jev engineering.

hayato

800,373 次观看 • 26 天前

Model router in Foundry Models now supports the GPT-5.6 family and Claude Opus 4.8, with expanded regional availability. Read the latest blog to learn why model selection is becoming a continuous optimization loop:

Model router in Foundry Models now supports the GPT-5.6 family and Claude Opus 4.8, with expanded regional availability. Read the latest blog to learn why model selection is becoming a continuous optimization loop:

Microsoft Azure

37,804 次观看 • 2 个月前

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

208,506 次观看 • 5 个月前