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Getting an AI agent running can mean wiring up models, search and tooling from scratch. Now there is a new solution: The new Nebius AI Builder Program brings those pieces together with runnable blueprints, free courses and office hours with its engineers. Nebius says members get $400+ in credits... show more

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BuilderShip is an AI hackathon co-hosted by Nebius, Composio, Tavily, and OpenClaw🦞. Finals are on a yacht on June 14, San Francisco Bay. To apply: post something you've built (agent, demo, or repo) and tag all four accounts. Every builder gets GPU credits, Token Factory inference keys, Composio integrations, Tavily search, and OpenClaw runtime from day one. Top 30 builders make the finals. Winner takes home $50K in cloud credits and a DGX Spark. Submit by June 12 →

BuilderShip is an AI hackathon co-hosted by Nebius, Composio, Tavily, and OpenClaw🦞. Finals are on a yacht on June 14, San Francisco Bay. To apply: post something you've built (agent, demo, or repo) and tag all four accounts. Every builder gets GPU credits, Token Factory inference keys, Composio integrations, Tavily search, and OpenClaw runtime from day one. Top 30 builders make the finals. Winner takes home $50K in cloud credits and a DGX Spark. Submit by June 12 →

Nebius

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Introducing Qwen 3 + Deep Research! We built a deep research agent with Qwen 3 and it performed better than most open source models that we've tried. the code is completely open source and free! built with 's Langgraph Together AI and uses Perplexity Tavily for search here's the code link:

Introducing Qwen 3 + Deep Research! We built a deep research agent with Qwen 3 and it performed better than most open source models that we've tried. the code is completely open source and free! built with 's Langgraph Together AI and uses Perplexity Tavily for search here's the code link:

Soham

34,566 görüntüleme • 1 yıl önce

Introducing the Generative UI Research Canvas ✨ Every agent needs a powerful UI Combine LangChain, Tavily, Tako and CopilotKit🪁 and you get a LangChain-based research agent with a Generative UI-driven frontend. When agents can explore the underlying data, research becomes more trustworthy and useful. How does this work? - LangChain manages the agent workflow and tool orchestration. - Tako converts retrieved data into structured, visual components - Tavily provides agentic search - CopilotKit renders those components in the UI and keeps the user in the loop while the agent is working So instead of a boring and static report, the output is an interactive research canvas that evolves as the agent runs. 2026 is the year where users want to see the output, not read it... Generative UI makes this possible for agentic applications. Tutorial: Open-Source Repo: Docs:

Introducing the Generative UI Research Canvas ✨ Every agent needs a powerful UI Combine LangChain, Tavily, Tako and CopilotKit🪁 and you get a LangChain-based research agent with a Generative UI-driven frontend. When agents can explore the underlying data, research becomes more trustworthy and useful. How does this work? - LangChain manages the agent workflow and tool orchestration. - Tako converts retrieved data into structured, visual components - Tavily provides agentic search - CopilotKit renders those components in the UI and keeps the user in the loop while the agent is working So instead of a boring and static report, the output is an interactive research canvas that evolves as the agent runs. 2026 is the year where users want to see the output, not read it... Generative UI makes this possible for agentic applications. Tutorial: Open-Source Repo: Docs:

Atai Barkai

11,997 görüntüleme • 7 ay önce

We are excited to join Nvidia's Nemotron Coalition of leading AI labs working together to advance open frontier foundation models. To celebrate we have partnered with NVIDIA and Nebius Token Factory to provide 2 free weeks of the new Nemotron 3 Ultra model on the Nous Portal!

We are excited to join Nvidia's Nemotron Coalition of leading AI labs working together to advance open frontier foundation models. To celebrate we have partnered with NVIDIA and Nebius Token Factory to provide 2 free weeks of the new Nemotron 3 Ultra model on the Nous Portal!

Nous Research

1,501,639 görüntüleme • 3 ay önce

✨New LangChain Academy Course: Learn to build with LangSmith Agent Builder 🪄 Learn how to build your own agents with LangSmith Agent Builder. Anyone can now build agents for complex daily tasks, without writing code. We built Agent Builder for anyone whose day gets swallowed by routine work. The research, follow-ups, updates, scheduling, and status checks that are essential to your operations, but quickly take over your calendar. Agent Builder is different from traditional workflow automations. You don’t need to map every step, tinker with if-this-then-that branching, or babysit dependencies. You just give it feedback like you would a teammate, and the agent learns using its memory. In this quickstart course, you'll learn how to: - Build an email agent - Understand what agents can do - Improve your agent - Set up triggers and your Agent Inbox Enroll for free ➡️

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LangChain

26,513 görüntüleme • 7 ay önce

You can now connect GitHub repos to deep research in ChatGPT. 🐙 Ask a question and the deep research agent will read and search the repo’s source code and PRs, returning a detailed report with citations. Hit deep research → GitHub to get started.

You can now connect GitHub repos to deep research in ChatGPT. 🐙 Ask a question and the deep research agent will read and search the repo’s source code and PRs, returning a detailed report with citations. Hit deep research → GitHub to get started.

OpenAI Developers

1,506,888 görüntüleme • 1 yıl önce

Orynth Product Review EP12 Herald lets you deploy a real AI agent in one click. No code, no API keys, no cost. Pick a template, connect Telegram, and your agent is live in under 60 seconds, running 24/7 with memory and modular skills. Powered by Nous Research, one of the most respected names in open-source AI. Built by gigaevm ($/acc), who got tired of agent platforms charging $50/month and locking you into one model, so he made the free version. A real product listed on Orynth with its own token solana:BT91Uvx89v6XvJKMn6GiwvPAxN9Lo2MPTVWkuGg5vory In this twelfth episode, we break down what Herald is building, the builder behind it, and why a free, instant AI agent deployer is worth a look.

Orynth Product Review EP12 Herald lets you deploy a real AI agent in one click. No code, no API keys, no cost. Pick a template, connect Telegram, and your agent is live in under 60 seconds, running 24/7 with memory and modular skills. Powered by Nous Research, one of the most respected names in open-source AI. Built by gigaevm ($/acc), who got tired of agent platforms charging $50/month and locking you into one model, so he made the free version. A real product listed on Orynth with its own token solana:BT91Uvx89v6XvJKMn6GiwvPAxN9Lo2MPTVWkuGg5vory In this twelfth episode, we break down what Herald is building, the builder behind it, and why a free, instant AI agent deployer is worth a look.

Orynth News

16,871 görüntüleme • 2 ay önce

My full interview with Roman Chernin, Co-founder & Chief Business Officer of Nebius Nebius just signed a $17 billion deal with Microsoft and a $3 billion deal with Meta. These are two of the biggest tech companies on Earth - and they're coming to Nebius for AI infrastructure. But the company does so much more than that: - Full-stack AI cloud (data centers → software → managed services) - Nebius Token Factory Nebius Token Factory for managed inference & post-training - Partners include Shopify, Higgsfield, Jetbrains My 5 takeaways with Roman Chernin below - thanks for the conversation! Full interview also available on YT ⬇️ Timestamps: 00:00 - Introduction 01:47 - Overview of Nebius $NBIS 03:23 - Roman's background and role at Nebius 04:10 - The $17B Microsoft & $3B Meta deals 05:29 - Why hyperscalers trust Nebius over building in-house 07:06 - Nebius's full-stack approach: Data centers to managed services 08:39 - Customer segmentation: Hyperscalers & Frontier AI Labs vs AI Startups vs Enterprises 14:41 - Token Factory explained: Managed inference & post-training 17:41 - When to switch from closed-source to open-source models 20:59 - Real results: Process achieves 26% cost reduction 25:05 - Why developers love building on Nebius 28:40 - AI agents and the future of infrastructure interaction 32:22 - NVIDIA's Groq acquisition: What it means for inference 35:38 - Why AI adoption will surprise us

My full interview with Roman Chernin, Co-founder & Chief Business Officer of Nebius Nebius just signed a $17 billion deal with Microsoft and a $3 billion deal with Meta. These are two of the biggest tech companies on Earth - and they're coming to Nebius for AI infrastructure. But the company does so much more than that: - Full-stack AI cloud (data centers → software → managed services) - Nebius Token Factory Nebius Token Factory for managed inference & post-training - Partners include Shopify, Higgsfield, Jetbrains My 5 takeaways with Roman Chernin below - thanks for the conversation! Full interview also available on YT ⬇️ Timestamps: 00:00 - Introduction 01:47 - Overview of Nebius $NBIS 03:23 - Roman's background and role at Nebius 04:10 - The $17B Microsoft & $3B Meta deals 05:29 - Why hyperscalers trust Nebius over building in-house 07:06 - Nebius's full-stack approach: Data centers to managed services 08:39 - Customer segmentation: Hyperscalers & Frontier AI Labs vs AI Startups vs Enterprises 14:41 - Token Factory explained: Managed inference & post-training 17:41 - When to switch from closed-source to open-source models 20:59 - Real results: Process achieves 26% cost reduction 25:05 - Why developers love building on Nebius 28:40 - AI agents and the future of infrastructure interaction 32:22 - NVIDIA's Groq acquisition: What it means for inference 35:38 - Why AI adoption will surprise us

Elliot Garreffa

29,660 görüntüleme • 7 ay önce

Kimi K3 is worth every one of its 2.8T parameters. It's the best open-weight model I've tried. It's frontier-level quality, and it can give any model a run for its money. I'm running it on Nebius Token Factory. It comes with an OpenAI-compatible API endpoint and 120 tokens/s (although I've seen much faster responses). If you want to start using it, here is the link:

Kimi K3 is worth every one of its 2.8T parameters. It's the best open-weight model I've tried. It's frontier-level quality, and it can give any model a run for its money. I'm running it on Nebius Token Factory. It comes with an OpenAI-compatible API endpoint and 120 tokens/s (although I've seen much faster responses). If you want to start using it, here is the link:

Santiago

22,594 görüntüleme • 23 gün önce

It takes 5 minutes to create a world-class web research agent that runs 24/7 and returns structured search results. 1. You can limit the sources it's allowed to use 2. You can specify the goals it needs to complete 3. You can design the format structure of the results 4. You can configure how much computing power it will use I show you how to set up a Web Search Agent in the video. A few benefits here: 1. This is great for complex research tasks 2. It's really easy to add this like a LEGO piece to a more complex workflow 3. Create an agent once, and reuse it with different inputs 4. The agent adapts to your use case as you work with it By the way, Nimble published a whole library of templates and research agents you can reuse and modify. You can start sending queries to one of these existing agents, and it will begin to adapt to Go here to try it out: Thanks to the Nimble team for partnering with me on this post.

It takes 5 minutes to create a world-class web research agent that runs 24/7 and returns structured search results. 1. You can limit the sources it's allowed to use 2. You can specify the goals it needs to complete 3. You can design the format structure of the results 4. You can configure how much computing power it will use I show you how to set up a Web Search Agent in the video. A few benefits here: 1. This is great for complex research tasks 2. It's really easy to add this like a LEGO piece to a more complex workflow 3. Create an agent once, and reuse it with different inputs 4. The agent adapts to your use case as you work with it By the way, Nimble published a whole library of templates and research agents you can reuse and modify. You can start sending queries to one of these existing agents, and it will begin to adapt to Go here to try it out: Thanks to the Nimble team for partnering with me on this post.

Santiago

21,079 görüntüleme • 1 ay önce

So Google has just released its own agent builder?! You can now add the agent block in Google Opal and "program it" in plain English. And it has natively: - Tool call (with Nano Banana, Veo, web search...) - Memory to save infos between sessions - Conditional logic Probably the easiest way to build AI agents I've seen so far.

So Google has just released its own agent builder?! You can now add the agent block in Google Opal and "program it" in plain English. And it has natively: - Tool call (with Nano Banana, Veo, web search...) - Memory to save infos between sessions - Conditional logic Probably the easiest way to build AI agents I've seen so far.

Paul Couvert

561,285 görüntüleme • 6 ay önce

Mark my words, Nebius will be the first Trillion dollar Neo-cloud company and here is why (Save this). Roman Chernin, CEO of Nebius just said on 20VC that Nebius raised prices and demand didn't move. When a company can raise prices and still have more demand than supply, that's the opportunity. Chernin also explained why he is deliberately not charging the maximum. As AI shifts from training, a one time cost to inference, which is the ongoing cost of serving every user and every query, compute pricing becomes the cost structure of the entire AI economy. If Nebius prices customers out, those customers cannot grow, and Nebius cannot grow with them. That is the compounding flywheel built directly into the revenue model. The numbers are already confirming it. Q1 2026 revenue came in at $399 million, up 684% year over year. The AI cloud segment grew 840% and represented 98% of total revenue. Adjusted EBITDA flipped positive to $129.5 million. And Nebius signed a long-term agreement with Meta worth up to $27 billion over five years, a hyperscaler outsourcing its own AI compute stack to a neocloud, which tells you that even companies with $50 billion capex budgets cannot build fast enough. Goldman Sachs says the consensus is underestimating 2027 hyperscaler capex by $500 billion. Every dollar hyperscalers cannot provision themselves flows to neoclouds like Nebius. As that gap widens, Nebius captures the overflow with 3 gigawatts of contracted power already secured and a CEO who just told you raising prices did not dent demand. Our subscribers are already up massively on Nebius and come join Milk Road Pro for our full breakdown, how to size Nebius against the broader neocloud opportunity, and our full AI thesis. Link below!

Mark my words, Nebius will be the first Trillion dollar Neo-cloud company and here is why (Save this). Roman Chernin, CEO of Nebius just said on 20VC that Nebius raised prices and demand didn't move. When a company can raise prices and still have more demand than supply, that's the opportunity. Chernin also explained why he is deliberately not charging the maximum. As AI shifts from training, a one time cost to inference, which is the ongoing cost of serving every user and every query, compute pricing becomes the cost structure of the entire AI economy. If Nebius prices customers out, those customers cannot grow, and Nebius cannot grow with them. That is the compounding flywheel built directly into the revenue model. The numbers are already confirming it. Q1 2026 revenue came in at $399 million, up 684% year over year. The AI cloud segment grew 840% and represented 98% of total revenue. Adjusted EBITDA flipped positive to $129.5 million. And Nebius signed a long-term agreement with Meta worth up to $27 billion over five years, a hyperscaler outsourcing its own AI compute stack to a neocloud, which tells you that even companies with $50 billion capex budgets cannot build fast enough. Goldman Sachs says the consensus is underestimating 2027 hyperscaler capex by $500 billion. Every dollar hyperscalers cannot provision themselves flows to neoclouds like Nebius. As that gap widens, Nebius captures the overflow with 3 gigawatts of contracted power already secured and a CEO who just told you raising prices did not dent demand. Our subscribers are already up massively on Nebius and come join Milk Road Pro for our full breakdown, how to size Nebius against the broader neocloud opportunity, and our full AI thesis. Link below!

Milk Road AI

15,677 görüntüleme • 3 ay önce

I’ve been waiting to post this! The Box Agent skill now ships pre-installed with Nous Research Hermes agent. Box gives Hermes the content and context to become a real collaborator at work. Update Hermes, prompt `connect to Box`, and your agent can now search, read, and write across Box with Box AI. Here’s a quick demo 👇

I’ve been waiting to post this! The Box Agent skill now ships pre-installed with Nous Research Hermes agent. Box gives Hermes the content and context to become a real collaborator at work. Update Hermes, prompt `connect to Box`, and your agent can now search, read, and write across Box with Box AI. Here’s a quick demo 👇

Chris Kim

48,957 görüntüleme • 18 gün önce

introducing HermitClaw - a 24/7 Agent that lives (and can only access) a single folder on your desktop HermitClaw follows its own research curiosities, surfs the web, writes code - and will play with any file you drop in its folder all code and details below!

introducing HermitClaw - a 24/7 Agent that lives (and can only access) a single folder on your desktop HermitClaw follows its own research curiosities, surfs the web, writes code - and will play with any file you drop in its folder all code and details below!

Brendan Hogan

187,776 görüntüleme • 6 ay önce

Your research agent can search the web in English. But the evidence that should shape your answer is in French film institute reports, Japanese trade publications, Brazilian creator communities, and Polish cinema data. That is not a model problem. It is a retrieval and orchestration problem. Neither gets solved by a bigger model. Here's a deep dive of the Temporal, OpenAI, and Box AI research agent we built. The agent plans multilingual queries, searches concurrently across four markets, synthesizes a cited master report, publishes localized briefs to Box with retry-safe versioning, and asks Box AI to compare the external findings against your internal governed content. End-to-end durable research.

Your research agent can search the web in English. But the evidence that should shape your answer is in French film institute reports, Japanese trade publications, Brazilian creator communities, and Polish cinema data. That is not a model problem. It is a retrieval and orchestration problem. Neither gets solved by a bigger model. Here's a deep dive of the Temporal, OpenAI, and Box AI research agent we built. The agent plans multilingual queries, searches concurrently across four markets, synthesizes a cited master report, publishes localized briefs to Box with retry-safe versioning, and asks Box AI to compare the external findings against your internal governed content. End-to-end durable research.

Box

34,452 görüntüleme • 1 ay önce

🔧 Bring Your Own Model — and Let Agent Forge Handle the Rest! John plugged in his own custom model — and in minutes, it was up and running as a fully deployed AI Agent. With Agent Forge, you’re not limited to prebuilt tools. You bring the intelligence. We automate everything else. Real models. Real-time deployment. Zero-code friction. 🔗 Try it here:

🔧 Bring Your Own Model — and Let Agent Forge Handle the Rest! John plugged in his own custom model — and in minutes, it was up and running as a fully deployed AI Agent. With Agent Forge, you’re not limited to prebuilt tools. You bring the intelligence. We automate everything else. Real models. Real-time deployment. Zero-code friction. 🔗 Try it here:

AITECH CLOUD NETWORK

32,798 görüntüleme • 1 yıl önce

Firecrawl is now a search provider in OpenRouter 🔥 Ground any OpenRouter model in full web pages instead of search snippets. Firecrawl searches and scrapes the live web into clean markdown your model can reason over. New sign-ups get a free Hobby plan with 100,000 credits!

Firecrawl is now a search provider in OpenRouter 🔥 Ground any OpenRouter model in full web pages instead of search snippets. Firecrawl searches and scrapes the live web into clean markdown your model can reason over. New sign-ups get a free Hobby plan with 100,000 credits!

Firecrawl

30,108 görüntüleme • 4 ay önce

The next internet will not be browsed. It will be operated by agents. OptimAI is building the infrastructure behind that shift. • A research task begins with Search pulling live context from the public web and social web • That context moves into Claw, where the agent can execute directly on your device • Domain knowledge becomes a Persona Agent • Core Node v2 keeps the system running at the edge • And x402 will make access and payment feel native to the flow That is the real shift: - from asking AI questions - to deploying intelligence that can work, learn, and compound. A trader can monitor signals. A founder can prepare reports overnight. A builder can publish a specialized agent once, then let others reuse it. This is what the agent-native internet looks like when it is built from the ground up. Start with OptimAI: • Persona Agent: • Claw / Core Node v2: • Search:

The next internet will not be browsed. It will be operated by agents. OptimAI is building the infrastructure behind that shift. • A research task begins with Search pulling live context from the public web and social web • That context moves into Claw, where the agent can execute directly on your device • Domain knowledge becomes a Persona Agent • Core Node v2 keeps the system running at the edge • And x402 will make access and payment feel native to the flow That is the real shift: - from asking AI questions - to deploying intelligence that can work, learn, and compound. A trader can monitor signals. A founder can prepare reports overnight. A builder can publish a specialized agent once, then let others reuse it. This is what the agent-native internet looks like when it is built from the ground up. Start with OptimAI: • Persona Agent: • Claw / Core Node v2: • Search:

OptimAI Network

18,590 görüntüleme • 4 ay önce

Your AI coding agent comes with defaults: which model runs, what you pay, and what leaves your machine. You can turn those defaults into choices. In our new short course, AI Coding Workflows: From Cloud to Local, built in partnership with JetBrains and taught by Paul Everitt | @pauleveritt@fosstodon.org, Developer Advocate at JetBrains, you'll rebuild the same app across cloud, hybrid, and fully local setups. Along the way, you'll split work across subagents, put cheaper models on the routine tasks, and finish with models running on your own machine. Enroll for free:

Your AI coding agent comes with defaults: which model runs, what you pay, and what leaves your machine. You can turn those defaults into choices. In our new short course, AI Coding Workflows: From Cloud to Local, built in partnership with JetBrains and taught by Paul Everitt | @[email protected], Developer Advocate at JetBrains, you'll rebuild the same app across cloud, hybrid, and fully local setups. Along the way, you'll split work across subagents, put cheaper models on the routine tasks, and finish with models running on your own machine. Enroll for free:

DeepLearning.AI

18,674 görüntüleme • 1 ay önce