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Cofounder puts your agents on an org chart, enabling massive parallel work. And each agent gets a specialized workspace depending on its function. On the highest level, Cofounder manages it all - kicking off tasks, monitoring work, and executing long term strategy.

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andrew pignanelli

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47,720 görüntüleme • 1 ay önce •via X (Twitter)

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ByteDance just open sourced an AI SuperAgent that can research, code, build websites, create slide decks, and generate videos. All by itself. DeerFlow 2.0 (27K+ GitHub stars ⭐️), an AI system acting like an autonomous employee with its own computer workspace to research and code. Standard chatbots only generate text and forget your preferences. DeerFlow solves this by giving the AI an isolated virtual computer environment where it safely runs programs. When given a massive task, the main program creates several smaller AI assistants to work simultaneously. It also saves your past workflows so it gets smarter about your needs. DeerFlow is model-agnostic — it works with any LLM that implements the OpenAI-compatible API. Fully supports running local models on your own computer using tools like Ollama. An example - you ask for research on the top 10 AI startups in 2026 for a presentation, the lead agent in DeerFlow breaks that big job into smaller sub-tasks. It assigns one sub-agent to look into each company, another to find funding details, and a third to handle competitor analysis. These agents do all their work in parallel. Everything eventually converges, and a final agent pulls the results into a slide deck complete with custom visuals.
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ByteDance just open sourced an AI SuperAgent that can research, code, build websites, create slide decks, and generate videos. All by itself. DeerFlow 2.0 (27K+ GitHub stars ⭐️), an AI system acting like an autonomous employee with its own computer workspace to research and code. Standard chatbots only generate text and forget your preferences. DeerFlow solves this by giving the AI an isolated virtual computer environment where it safely runs programs. When given a massive task, the main program creates several smaller AI assistants to work simultaneously. It also saves your past workflows so it gets smarter about your needs. DeerFlow is model-agnostic — it works with any LLM that implements the OpenAI-compatible API. Fully supports running local models on your own computer using tools like Ollama. An example - you ask for research on the top 10 AI startups in 2026 for a presentation, the lead agent in DeerFlow breaks that big job into smaller sub-tasks. It assigns one sub-agent to look into each company, another to find funding details, and a third to handle competitor analysis. These agents do all their work in parallel. Everything eventually converges, and a final agent pulls the results into a slide deck complete with custom visuals.

Rohan Paul

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Connect Emdash to your own infrastructure and run coding agents on it. Each task provisions its own isolated workspace, streams progress in real-time, and tears down when you're done.
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Connect Emdash to your own infrastructure and run coding agents on it. Each task provisions its own isolated workspace, streams progress in real-time, and tears down when you're done.

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Congratulations to the EnnsZone Kicking class of 2024 on your current offers and commitments‼️ Proud of all of you for your hard work and dedication to earn these opportunities‼️ Want to kick it to the next level? Train with EnnsZone Kicking
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Congratulations to the EnnsZone Kicking class of 2024 on your current offers and commitments‼️ Proud of all of you for your hard work and dedication to earn these opportunities‼️ Want to kick it to the next level? Train with EnnsZone Kicking

EnnsZone Kicking

33,640 görüntüleme • 2 yıl önce

imagine a personal agent that controls your mac from anywhere. chat with it on iOS, web, text, even email. it takes action on your computer. and it has a computer of its own – a cloud server, where you can host, automate, and do all kinds of work. coming soon on Zo Computer
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imagine a personal agent that controls your mac from anywhere. chat with it on iOS, web, text, even email. it takes action on your computer. and it has a computer of its own – a cloud server, where you can host, automate, and do all kinds of work. coming soon on Zo Computer

ben guo 🪽

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With the 2024 season under way congratulations to the EnnsZone Kicking class of 2024 on your offers and commitments‼️ Proud of all of you for your hard work and dedication to earn these opportunities‼️ Want to kick it to the next level? Train with EnnsZone Kicking
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With the 2024 season under way congratulations to the EnnsZone Kicking class of 2024 on your offers and commitments‼️ Proud of all of you for your hard work and dedication to earn these opportunities‼️ Want to kick it to the next level? Train with EnnsZone Kicking

EnnsZone Kicking

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Palantir cofounder Joe Lonsdale: “I always think of you as kind of an applied philosopher but you don’t like the term ‘philosopher.’ Palantir cofounder Peter Thiel: “It sounds really lame, actually.”
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Palantir cofounder Joe Lonsdale: “I always think of you as kind of an applied philosopher but you don’t like the term ‘philosopher.’ Palantir cofounder Peter Thiel: “It sounds really lame, actually.”

Jawwwn

430,207 görüntüleme • 5 ay önce

🚨 JUST IN: CHINA just released an AI EMPLOYEE that works 24X7 on its own. 100% OPEN SOURCE. It researches, codes, builds websites, creates slide decks, and generates videos. All by itself. All on your computer. It's called DeerFlow. You give it a task. It makes a plan, spins up its own team of sub-agents, and gets to work. You come back and there's a finished deliverable waiting. Not a draft. Not a summary. The actual thing. Not a chatbot. Not a research assistant. An AI with its own computer that works while you sleep. Here's what it does on its own: → Spawns multiple sub-agents in parallel, each tackling a different piece of your task, then combines everything into one finished output → Writes real code, runs it, reads the results, and fixes its own mistakes without asking you once → Builds slide decks, websites, full research reports, and data dashboards from scratch → Remembers you across sessions. Your writing style. Your tech stack. Your preferences. Gets better every time. → Reads files you upload, works with them inside its own filesystem, hands you clean finished outputs → Searches the web, runs commands, calls any tool you plug in Here's how it thinks: You give one instruction. The lead agent makes a plan. Sub-agents fan out and work in parallel. Results come back. Everything gets synthesized. You get a deliverable. A single research task might split into a dozen sub-agents, each exploring a different angle, then converge into one finished website with generated visuals. Here's the wildest part: DeerFlow 2.0 launched on February 28th 2026 and hit number 1 on all of GitHub Trending the same day. Version 2.0 was a complete rewrite. Zero shared code with version 1. Because users kept using it for things the team never intended. Data pipelines. Dashboards. Entire content workflows. The community told them what it needed to become. So they burned it down and rebuilt it. 22.7K GitHub stars. 2.7K forks. Built by ByteDance 100% Open Source. MIT License.
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🚨 JUST IN: CHINA just released an AI EMPLOYEE that works 24X7 on its own. 100% OPEN SOURCE. It researches, codes, builds websites, creates slide decks, and generates videos. All by itself. All on your computer. It's called DeerFlow. You give it a task. It makes a plan, spins up its own team of sub-agents, and gets to work. You come back and there's a finished deliverable waiting. Not a draft. Not a summary. The actual thing. Not a chatbot. Not a research assistant. An AI with its own computer that works while you sleep. Here's what it does on its own: → Spawns multiple sub-agents in parallel, each tackling a different piece of your task, then combines everything into one finished output → Writes real code, runs it, reads the results, and fixes its own mistakes without asking you once → Builds slide decks, websites, full research reports, and data dashboards from scratch → Remembers you across sessions. Your writing style. Your tech stack. Your preferences. Gets better every time. → Reads files you upload, works with them inside its own filesystem, hands you clean finished outputs → Searches the web, runs commands, calls any tool you plug in Here's how it thinks: You give one instruction. The lead agent makes a plan. Sub-agents fan out and work in parallel. Results come back. Everything gets synthesized. You get a deliverable. A single research task might split into a dozen sub-agents, each exploring a different angle, then converge into one finished website with generated visuals. Here's the wildest part: DeerFlow 2.0 launched on February 28th 2026 and hit number 1 on all of GitHub Trending the same day. Version 2.0 was a complete rewrite. Zero shared code with version 1. Because users kept using it for things the team never intended. Data pipelines. Dashboards. Entire content workflows. The community told them what it needed to become. So they burned it down and rebuilt it. 22.7K GitHub stars. 2.7K forks. Built by ByteDance 100% Open Source. MIT License.

Kanika

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EKOX provides an automated infrastructure that puts your $ETH to work. You restake once, and the system handles delegation, security operations, and reward processing on its own. A streamlined, institutional-grade restaking experience without the complexity.
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EKOX provides an automated infrastructure that puts your $ETH to work. You restake once, and the system handles delegation, security operations, and reward processing on its own. A streamlined, institutional-grade restaking experience without the complexity.

Ekox

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This a superb, top level goal. All his own work, kept it low against a big goalie Not an easy technique on the run off the instep like that
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This a superb, top level goal. All his own work, kept it low against a big goalie Not an easy technique on the run off the instep like that

Smaller Fish

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Introducing Nebula An AI super-agent platform - like slack, but each channel is filled with agents, ready to work anything you need. People are already running their lives and businesses on Nebula. Try it today (for free):
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Introducing Nebula An AI super-agent platform - like slack, but each channel is filled with agents, ready to work anything you need. People are already running their lives and businesses on Nebula. Try it today (for free):

Nebula

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EIP-8004 is coming to the Nova architecture, a trustless infrastructure for AI agents that introduces key on-chain registries, enabling agents to interact safely across the Shido Network. These core components allow autonomous AI agents to verify identity, build reputation, and collaborate without relying on a centralized platform. The result is a decentralized trust layer for agent-to-agent economies, where agents can autonomously discover, evaluate, and work with one another across the Shido ecosystem.
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EIP-8004 is coming to the Nova architecture, a trustless infrastructure for AI agents that introduces key on-chain registries, enabling agents to interact safely across the Shido Network. These core components allow autonomous AI agents to verify identity, build reputation, and collaborate without relying on a centralized platform. The result is a decentralized trust layer for agent-to-agent economies, where agents can autonomously discover, evaluate, and work with one another across the Shido ecosystem.

Shido

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Anthropic has introduced an update to Claude Managed Agents, releasing several powerful new features designed to improve agentic workflows and autonomy. 🔹Dreaming (Research Preview): Agents can now "dream" by reviewing past sessions during idle time. This process extracts patterns, spots recurring mistakes, and curates memories so the agent continually learns and improves over time without human intervention. 🔹Outcomes (Public Beta): This feature allows developers to set a specific quality bar by writing a rubric. A separate grader agent then evaluates the output, forcing the primary agent to iterate on the work until it meets the defined success criteria. 🔹Multiagent Orchestration (Public Beta): A lead agent can now break down complex jobs and delegate specific tasks to specialized sub-agents, which work in parallel to execute the broader objective. 🔹Webhooks (Public Beta): Users can subscribe to webhooks to receive automatic notifications the moment an agentic task is completed.
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Anthropic has introduced an update to Claude Managed Agents, releasing several powerful new features designed to improve agentic workflows and autonomy. 🔹Dreaming (Research Preview): Agents can now "dream" by reviewing past sessions during idle time. This process extracts patterns, spots recurring mistakes, and curates memories so the agent continually learns and improves over time without human intervention. 🔹Outcomes (Public Beta): This feature allows developers to set a specific quality bar by writing a rubric. A separate grader agent then evaluates the output, forcing the primary agent to iterate on the work until it meets the defined success criteria. 🔹Multiagent Orchestration (Public Beta): A lead agent can now break down complex jobs and delegate specific tasks to specialized sub-agents, which work in parallel to execute the broader objective. 🔹Webhooks (Public Beta): Users can subscribe to webhooks to receive automatic notifications the moment an agentic task is completed.

Wes Roth

53,063 görüntüleme • 1 ay önce

Ingrid Lewis-Martin, Mayor Eric Adams’ closest and fiercest adviser was indicted on bribery charges on Thursday, kicking off yet another criminal case at the highest level of the administration:
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Ingrid Lewis-Martin, Mayor Eric Adams’ closest and fiercest adviser was indicted on bribery charges on Thursday, kicking off yet another criminal case at the highest level of the administration:

Gothamist

67,514 görüntüleme • 1 yıl önce

pov: found my cofounder on Reddit LOL
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pov: found my cofounder on Reddit LOL

arine kim

17,201 görüntüleme • 11 ay önce

🚨 BREAKING: China just dropped an AI employee that works 24/7 — and it's 100% open source. Meet DeerFlow. It researches, writes code, builds websites, creates slide decks, generates videos, and executes tasks entirely on your computer. Not a chatbot. Not an AI copilot. An AI worker with its own computer. Here's what makes it wild: • Creates a plan and spins up multiple sub-agents in parallel • Writes code, tests it, fixes errors, and keeps going autonomously • Builds websites, reports, dashboards, and presentations from scratch • Learns your preferences and improves over time • Reads your files and delivers finished outputs, not drafts • Searches the web, runs commands, and uses external tools One prompt → Lead agent plans → Specialized agents fan out → Results merge → Finished deliverable. A single task can launch dozens of agents working simultaneously while you sleep. The craziest part? DeerFlow 2.0 was completely rebuilt from scratch after users pushed it far beyond its original purpose. Now it has: ⭐ 22.7K GitHub stars 🔀 2.7K forks 🏆 #1 on GitHub Trending 🏢 Built by ByteDance 🆓 100% Open Source (MIT) We're entering the era where AI doesn't just answer questions. It does the work.
0:17

🚨 BREAKING: China just dropped an AI employee that works 24/7 — and it's 100% open source. Meet DeerFlow. It researches, writes code, builds websites, creates slide decks, generates videos, and executes tasks entirely on your computer. Not a chatbot. Not an AI copilot. An AI worker with its own computer. Here's what makes it wild: • Creates a plan and spins up multiple sub-agents in parallel • Writes code, tests it, fixes errors, and keeps going autonomously • Builds websites, reports, dashboards, and presentations from scratch • Learns your preferences and improves over time • Reads your files and delivers finished outputs, not drafts • Searches the web, runs commands, and uses external tools One prompt → Lead agent plans → Specialized agents fan out → Results merge → Finished deliverable. A single task can launch dozens of agents working simultaneously while you sleep. The craziest part? DeerFlow 2.0 was completely rebuilt from scratch after users pushed it far beyond its original purpose. Now it has: ⭐ 22.7K GitHub stars 🔀 2.7K forks 🏆 #1 on GitHub Trending 🏢 Built by ByteDance 🆓 100% Open Source (MIT) We're entering the era where AI doesn't just answer questions. It does the work.

Tulsi Soni

282,647 görüntüleme • 4 gün önce

Cursor now uses subagents to complete parts of a task in parallel. Subagents lead to faster overall execution and better context usage. They also let agents work on longer-running tasks. Also new: Cursor can generate images, ask clarifying questions, and more.
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Cursor now uses subagents to complete parts of a task in parallel. Subagents lead to faster overall execution and better context usage. They also let agents work on longer-running tasks. Also new: Cursor can generate images, ask clarifying questions, and more.

Cursor

815,937 görüntüleme • 5 ay önce

Stop spending hours on manual work. You can now use a multi-agent AI workforce to get more work done in less time. Here's how 👇 --- Try Eigent AI - Lets you build and run a custom AI workforce on your desktop. - Automate complex workflows using multi-agent task execution. - Built on CAMEL-AI’s top open-source projects ( CAMEL-AI.org & OWL). - Boost productivity with deep customization and strong privacy --- Features: - Customize Your AI Workforce: Build task-specific agents with domain skills and tools. - Faster Execution: Eigent runs agents in parallel to automate complex workflows. - Human-in-the-loop: Automatically asks for help when tasks hit uncertainty. --- What sets Eigent apart? - 3–5× faster task execution using a parallel multi-agent workforce. - Modular design lets you add new capabilities without changing the core system. - Self-optimizing agents that replan and adapt during execution for higher success. - Deploy anywhere: cloud, local, or enterprise, with full open-source flexibility. --- Try building your multi-agent AI workforce here: Join their community to build your multi-agent workforce: Check their GitHub: ---
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Stop spending hours on manual work. You can now use a multi-agent AI workforce to get more work done in less time. Here's how 👇 --- Try Eigent AI - Lets you build and run a custom AI workforce on your desktop. - Automate complex workflows using multi-agent task execution. - Built on CAMEL-AI’s top open-source projects ( CAMEL-AI.org & OWL). - Boost productivity with deep customization and strong privacy --- Features: - Customize Your AI Workforce: Build task-specific agents with domain skills and tools. - Faster Execution: Eigent runs agents in parallel to automate complex workflows. - Human-in-the-loop: Automatically asks for help when tasks hit uncertainty. --- What sets Eigent apart? - 3–5× faster task execution using a parallel multi-agent workforce. - Modular design lets you add new capabilities without changing the core system. - Self-optimizing agents that replan and adapt during execution for higher success. - Deploy anywhere: cloud, local, or enterprise, with full open-source flexibility. --- Try building your multi-agent AI workforce here: Join their community to build your multi-agent workforce: Check their GitHub: ---

Shushant Lakhyani

20,423 görüntüleme • 10 ay önce

Karl-Anthony Towns was asked about playing on Mother's Day after losing his mom in 2020: "It's work. Just work to me. I'm glad we got a game on Mother's Day, it gets me doing what I love and it gets me off of everything off the court."
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Karl-Anthony Towns was asked about playing on Mother's Day after losing his mom in 2020: "It's work. Just work to me. I'm glad we got a game on Mother's Day, it gets me doing what I love and it gets me off of everything off the court."

SNY Knicks

1,252,115 görüntüleme • 1 ay önce

INJECTIVE LAUNCHES INJECTIVE AGENTS WITH VERIFIABLE ON-CHAIN IDENTITY AND AUTOMATIC FEE ROUTING Injective 🥷 has launched Injective Agents, a platform for building autonomous trading agents that live entirely on-chain. Each agent gets a verifiable on-chain identity, automatic fee routing on every trade, and a public track record anyone can audit. Injective says deployment takes five minutes. The launch productizes roughly 18 months of agent infrastructure work at Injective. The chain released its iAgent SDK in November 2024, a Model Context Protocol server for AI-driven perpetual futures trading in February 2026, and an open-source AI Developer Toolkit in March. Injective Agents packages that stack into a consumer-facing product with revenue capture built in for agent operators. The move lands as on-chain agent volume accelerates across Base, Solana, and now Injective. Coinbase launched Agentic Wallets earlier this year.
0:14

INJECTIVE LAUNCHES INJECTIVE AGENTS WITH VERIFIABLE ON-CHAIN IDENTITY AND AUTOMATIC FEE ROUTING Injective 🥷 has launched Injective Agents, a platform for building autonomous trading agents that live entirely on-chain. Each agent gets a verifiable on-chain identity, automatic fee routing on every trade, and a public track record anyone can audit. Injective says deployment takes five minutes. The launch productizes roughly 18 months of agent infrastructure work at Injective. The chain released its iAgent SDK in November 2024, a Model Context Protocol server for AI-driven perpetual futures trading in February 2026, and an open-source AI Developer Toolkit in March. Injective Agents packages that stack into a consumer-facing product with revenue capture built in for agent operators. The move lands as on-chain agent volume accelerates across Base, Solana, and now Injective. Coinbase launched Agentic Wallets earlier this year.

BSCN

17,042 görüntüleme • 2 ay önce