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Watch Devin Fusion work: The sidekick model handles fetching information and skimming sources. The frontier model makes a plan for implementation, then delegates well-scoped sub-tasks to the sidekick with its own cached context.

Cognition

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25,080 次观看 • 1 个月前 •via X (Twitter)

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Devin tests its work before you review the PR. You review and approve the test plan. Then get back a screen recording with a visual checklist of step-by-step QA.

Devin tests its work before you review the PR. You review and approve the test plan. Then get back a screen recording with a visual checklist of step-by-step QA.

Cognition

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Devin can manage a team of Devins. Managed Devins run in parallel help break down complex tasks. Each managed session is a full Devin, with its own VM, terminal, browser, and testing infrastructure. The main session coordinates, monitors, and compiles results.

Devin can manage a team of Devins. Managed Devins run in parallel help break down complex tasks. Each managed session is a full Devin, with its own VM, terminal, browser, and testing infrastructure. The main session coordinates, monitors, and compiles results.

Cognition

31,704 次观看 • 4 个月前

Today we're excited to introduce Devin, the first AI software engineer. Devin is the new state-of-the-art on the SWE-Bench coding benchmark, has successfully passed practical engineering interviews from leading AI companies, and has even completed real jobs on Upwork. Devin is an autonomous agent that solves engineering tasks through the use of its own shell, code editor, and web browser. When evaluated on the SWE-Bench benchmark, which asks an AI to resolve GitHub issues found in real-world open-source projects, Devin correctly resolves 13.86% of the issues unassisted, far exceeding the previous state-of-the-art model performance of 1.96% unassisted and 4.80% assisted. Check out what Devin can do in the thread below.

Today we're excited to introduce Devin, the first AI software engineer. Devin is the new state-of-the-art on the SWE-Bench coding benchmark, has successfully passed practical engineering interviews from leading AI companies, and has even completed real jobs on Upwork. Devin is an autonomous agent that solves engineering tasks through the use of its own shell, code editor, and web browser. When evaluated on the SWE-Bench benchmark, which asks an AI to resolve GitHub issues found in real-world open-source projects, Devin correctly resolves 13.86% of the issues unassisted, far exceeding the previous state-of-the-art model performance of 1.96% unassisted and 4.80% assisted. Check out what Devin can do in the thread below.

Cognition

31,458,631 次观看 • 2 年前

Devin can now manage a team of Devins. Devin will break down large tasks and delegate them to parallel Devins that each run in their own VM. Over time, Devin gets better at breaking down and managing tasks for your codebase. Available now for all users.

Devin can now manage a team of Devins. Devin will break down large tasks and delegate them to parallel Devins that each run in their own VM. Over time, Devin gets better at breaking down and managing tasks for your codebase. Available now for all users.

Cognition

111,230 次观看 • 5 个月前

Building and prototyping games is easier than ever with Sidekick. Our designer built a 3D version of this OpenAI GPT-o1 game demo in <1 hour. Used Autodesk Maya for assets, Unity for engine, @bezi_3d Sidekick for scripting & implementation. Sidekick analyzes your project for real-time context of the asset folder, scene objects, components, and more. This allows it to implement simple mechanics—like movement controls and basic physics—for your characters and objects in seconds. It's the AI tool built by game developers, for game developers.

Building and prototyping games is easier than ever with Sidekick. Our designer built a 3D version of this OpenAI GPT-o1 game demo in <1 hour. Used Autodesk Maya for assets, Unity for engine, @bezi_3d Sidekick for scripting & implementation. Sidekick analyzes your project for real-time context of the asset folder, scene objects, components, and more. This allows it to implement simple mechanics—like movement controls and basic physics—for your characters and objects in seconds. It's the AI tool built by game developers, for game developers.

Bezi

15,295 次观看 • 1 年前

Sub-agent Model Selection — Different Tasks, Different Models Your main agent runs Qwen3.6-Plus for quality. But not every subtask needs a flagship model. Now sub-agents can use a different model. Create a skill file with model: openai:qwen3.5-plus and the sub-agent runs on that model. Powerful model for the hard parts, fast model for the easy parts. Save tokens without sacrificing quality on what matters.

Sub-agent Model Selection — Different Tasks, Different Models Your main agent runs Qwen3.6-Plus for quality. But not every subtask needs a flagship model. Now sub-agents can use a different model. Create a skill file with model: openai:qwen3.5-plus and the sub-agent runs on that model. Powerful model for the hard parts, fast model for the easy parts. Save tokens without sacrificing quality on what matters.

Qwen

21,333 次观看 • 4 个月前

The phone threshold is even harder than the storage number suggests. A phone exposes only part of its memory to an application, and the model must share that budget with its KV cache, activations, runtime, and the rest of the product. At 3.9 GB, 1-bit Bonsai 27B clears that threshold with room to work, making 27B-class local AI possible on a phone for the first time. (Demo Mode: cached & prefilled image context)

The phone threshold is even harder than the storage number suggests. A phone exposes only part of its memory to an application, and the model must share that budget with its KV cache, activations, runtime, and the rest of the product. At 3.9 GB, 1-bit Bonsai 27B clears that threshold with room to work, making 27B-class local AI possible on a phone for the first time. (Demo Mode: cached & prefilled image context)

PrismML

32,858 次观看 • 1 个月前

Introducing Harvey II: smarter agents from the start. - Featuring Harvey Tenet, our first model trained for legal work - Built around matters and projects - Agents start with the files, context, permissions, and history they need - Assign tasks to lawyers or agents, then track and review the work - Harvey remembers how you work and writes like you

Introducing Harvey II: smarter agents from the start. - Featuring Harvey Tenet, our first model trained for legal work - Built around matters and projects - Agents start with the files, context, permissions, and history they need - Assign tasks to lawyers or agents, then track and review the work - Harvey remembers how you work and writes like you

Harvey

168,124 次观看 • 1 天前

Progress in open models is keeping Big AI labs up at night, and I'm here for it! We have a brand new open-weight multimodal model optimized for long-horizon tasks. This model is really good at something: it can work on tasks that keep evolving over time. • 280B total parameters, but only 16B active • 512K context window • Understands text, images, and audio • Strong reasoning, coding, and tool use But the best of all: the model learns and adapts to new information! Imagine you start running an agent today to solve a problem, and while it's working, you get new information that changes the initial conditions, or you change your mind. The agents you run today don't have issues with short tasks and goals that don't change, but reality is messy, and that makes it hard for long-horizon agents to succeed. The new dots3-note Preview model introduces TEMPO. TEMPO is a new reinforcement learning technique that lets the model periodically pause and critique its own progress. Basically, from time to time, the agent asks itself: "Am I getting closer to the goal, or am I wasting my time?" The same model switches between actor and critic. The actor works on the problem. The critic looks at the current state, reasons about how much progress it has made, and determines what should happen next. TEMPO gives the model feedback along the way. This is huge for any agent that can work on long-horizon tasks without wasting its time.

Santiago

41,058 次观看 • 22 小时前

If your AI can't call a function or hit an API, it's not really an agent (it's a chatbot). Vision Agents makes it simple to connect MCP servers and function calling so your model can interact with its surroundings: running code, fetching data, and automating tasks. Step-by-step implementation from Stefan in thread ⬇

If your AI can't call a function or hit an API, it's not really an agent (it's a chatbot). Vision Agents makes it simple to connect MCP servers and function calling so your model can interact with its surroundings: running code, fetching data, and automating tasks. Step-by-step implementation from Stefan in thread ⬇

Stream

31,306 次观看 • 9 个月前

Devin is generally available today! Just tag Devin to fix frontend bugs, create first-draft PRs for backlog tasks, make refactors, and more. Start building with Devin below:

Devin is generally available today! Just tag Devin to fix frontend bugs, create first-draft PRs for backlog tasks, make refactors, and more. Start building with Devin below:

Cognition

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Set up your new GitHub Copilot agent for success! 🚀 This video will show you how to: ✅ Define clear, well-scoped issues. ⚙️ Utilize Copilot custom instructions effectively. 💻 Ensure a proper development environment setup. 🔗 Grant tool access via the Model Context Protocol (MCP). Watch and then head over to Docs for more tips! 👇

Set up your new GitHub Copilot agent for success! 🚀 This video will show you how to: ✅ Define clear, well-scoped issues. ⚙️ Utilize Copilot custom instructions effectively. 💻 Ensure a proper development environment setup. 🔗 Grant tool access via the Model Context Protocol (MCP). Watch and then head over to Docs for more tips! 👇

GitHub

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Introducing Devin 2.2 – the autonomous agent that can test with computer use, self-verify, and auto-fix its work. Try it for free! We’ve also overhauled Devin from the ground up: - 3x faster startup - fully redesigned interface - computer use + virtual desktop ...and hundreds more UX and functionality improvements.

Introducing Devin 2.2 – the autonomous agent that can test with computer use, self-verify, and auto-fix its work. Try it for free! We’ve also overhauled Devin from the ground up: - 3x faster startup - fully redesigned interface - computer use + virtual desktop ...and hundreds more UX and functionality improvements.

Cognition

536,323 次观看 • 5 个月前

The terminal hasn’t changed much since the 1970s. What you do with it has. Introducing Devin for Terminal: everything we learned building Devin, now as a local agent, available right in your shell. And when your work outgrows your laptop, hand it off to the cloud.

The terminal hasn’t changed much since the 1970s. What you do with it has. Introducing Devin for Terminal: everything we learned building Devin, now as a local agent, available right in your shell. And when your work outgrows your laptop, hand it off to the cloud.

Cognition

392,043 次观看 • 3 个月前

Cloud agents work while you eat, sleep, and take the subway. "Every morning I'll spin up a session on the way to work." Melius is a small and nimble startup, and Devin gives them the engineering capacity of a 100-person team. That's why the fastest moving startups use Devin.

Cloud agents work while you eat, sleep, and take the subway. "Every morning I'll spin up a session on the way to work." Melius is a small and nimble startup, and Devin gives them the engineering capacity of a 100-person team. That's why the fastest moving startups use Devin.

Cognition

110,533 次观看 • 13 天前

underrated gems in Kimi-K3 release: > an early K3 wrote the majority of the kernels in the late development stages > it built a triton-class compiler from scratch, MiniTriton, that delivers performance on par with or better than Triton and torch.compile > then it designed a chip, by a model, for a model, in one 48-hour autonomous run the model is rewriting and optimizing every layer of the stack it runs on: kernels for its own training. A compiler for its own kernels. silicon for its own weights. we're watching software build its own hardware

underrated gems in Kimi-K3 release: > an early K3 wrote the majority of the kernels in the late development stages > it built a triton-class compiler from scratch, MiniTriton, that delivers performance on par with or better than Triton and torch.compile > then it designed a chip, by a model, for a model, in one 48-hour autonomous run the model is rewriting and optimizing every layer of the stack it runs on: kernels for its own training. A compiler for its own kernels. silicon for its own weights. we're watching software build its own hardware

Alex Ker 🔭

310,834 次观看 • 1 个月前

HERMES AGENT SUPPORTS 300+ MODELS. PICKING THE RIGHT ONE PER TASK IS THE DIFFERENCE BETWEEN $5/MONTH AND $50. STARTING OUT: Claude Sonnet 4.6. official recommendation from Nous Research. "the model this project was built and tested with." strong reasoning. reliable tool calling. mid-range pricing. PREMIUM TIER: Claude Opus 4.8. best coding benchmarks available. self-correcting reasoning. catches its own mistakes. 1M context. use for demanding tasks where quality matters. GPT-5.5. #1 Chatbot Arena. #1 GPQA Diamond reasoning (94.1%). #1 creative writing. 2M context. handles entire codebases in one pass. Grok 4.30. the only frontier model with live X firehose access. real-time social data, breaking news, market sentiment. connects via Grok OAuth. no separate API key. Grok-Composer-2.5-Fast (v0.17.0). Cursor's coding model. 200K context. available through your Grok subscription via OAuth. no extra cost if you already pay for Grok. MID-RANGE TIER: Claude Sonnet 4.6. best balance of quality and cost for daily use. strongest prose and tool calling in this tier. Gemini 2.5 Pro. Google Search grounding built in. cites sources. verifies claims. pulls current data. 2M context. best for research-heavy workflows. GPT-4.1. reliable tool calling. solid general reasoning. good middle ground when you need OpenAI compatibility. BUDGET TIER: Claude Haiku 4.5. fastest Anthropic model. cheapest paid Claude option. strong at classification, routing, simple queries. use for auxiliary tasks: compression, vision, web extraction, approval scoring. DeepSeek V4. best cost-to-quality ratio in the market. 90% cache discount on repeated context. use for sub-agents and bulk parallel work. DeepSeek V4 Flash. cheapest paid model worth using. 1M context. MIT license. self-hostable. use for cron jobs, monitoring, routine searches. MiniMax M3. Nous Research and MiniMax collaborating on optimization. 1M context via lightning attention. 59% SWE-Bench Pro. beats several premium models on coding. one of the most-used models inside Hermes. FREE / LOCAL: Qwen 3.5 27B via Ollama. 16GB VRAM. reliable tool calling. best free local model for Hermes as of mid-2026. Qwen 3 8B. 8GB VRAM. fits a $7 VPS. handles routine tasks at zero API cost. Llama 4 Maverick. best open-weight tool calling. 1M context. needs more VRAM but strongest local option. HOW TO ASSIGN MODELS: main model: Desktop app / Dashboard → Models → switch sub-agent model: set in Desktop app, Dashboard, or config.yaml: delegation: model: "deepseek/deepseek-v4" auxiliary models (compression, vision, web extract): Desktop app / Dashboard → Models → Auxiliary Haiku 4.5 or Gemini Flash work well here. saves significantly when your main model is premium. per-profile: each Hermes profile gets its own model. Scout on DeepSeek. Analyst on Sonnet. Briefer on budget model. Coder on Opus. per-cron-job: pin a specific model to any cron job. morning brief on Haiku. deep research on Sonnet. monitoring on DeepSeek Flash. each job uses only the model it needs. per-session: /model deepseek/deepseek-v4-flash hot-swap mid-conversation. no restart needed. FALLBACK CHAINS: if your primary model is unavailable, Hermes automatically switches to the next provider. rate limit or server error = next model in the chain. no failed runs. no manual intervention. set in Desktop app, Dashboard, or config.yaml: fallback_providers: - openrouter - nous - codex PROVIDER PATHS: OPENROUTER: 300+ models under one API key. pay per token. most flexible. NOUS PORTAL: 300+ models + Tool Gateway (web search, image gen, TTS, browser). one OAuth. one subscription. 10% off token-billed providers. CHATGPT SUB: GPT-5.5 + Grok via OAuth. included tokens with $20 subscription. OLLAMA: free. local. private. zero API cost. your hardware only. mix providers across profiles and tasks. Scout on OpenRouter. Analyst on Nous Portal. Coder on ChatGPT sub. Monitor on Ollama. THE RULE: premium for work that needs deep reasoning. mid-range for daily driver tasks. budget for volume and background work. free for monitoring and routine jobs. pricing changes fast. check openrouter ai for current rates before committing. Which is your favourite model and for what task? full 15 levels breakdown in the article 👇

YanXbt

17,138 次观看 • 1 个月前

Our latest speech-to-speech model is faster, more accurate, and excels at function calling. Watch @promptshant and Brian Fioca build a realtime voice agent that can search the web and hand off tasks to reasoning models with full context.

Our latest speech-to-speech model is faster, more accurate, and excels at function calling. Watch @promptshant and Brian Fioca build a realtime voice agent that can search the web and hand off tasks to reasoning models with full context.

OpenAI Developers

81,822 次观看 • 1 年前

Let Devin work the night shift. At 1:40 AM, Jalagar (James) | OpenSea told Devin to build the first NFT mint tab for OpenSea mobile. 24 hours later, Devin delivered. All it took was one Linear ticket.

Let Devin work the night shift. At 1:40 AM, Jalagar (James) | OpenSea told Devin to build the first NFT mint tab for OpenSea mobile. 24 hours later, Devin delivered. All it took was one Linear ticket.

Cognition

35,746 次观看 • 4 个月前

Mfw Minimax H3, the new Open Source Audiovisual model that is vastly superior to all the Frontier models, is also the first model in history to be trained on and remember The Will Stancil Show and now chooses to generate propaganda posters of Will Stancil all on its own.

Mfw Minimax H3, the new Open Source Audiovisual model that is vastly superior to all the Frontier models, is also the first model in history to be trained on and remember The Will Stancil Show and now chooses to generate propaganda posters of Will Stancil all on its own.

Emily Youcis

12,020 次观看 • 10 天前