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your coding agents are Kanban cards now 😯. New in Orca: open a board over any terminal pane and drag each agent worktree between statuses. todo, in progress, review, testing, blocked, done, or whatever custom columns fit your workflow. much easier when you have 10+ agent running across different features.

Orca ADE

7,678 subscribers

47,609 次观看 • 4 个月前 •via X (Twitter)

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You can now delegate tasks to GitHub Copilot coding agent from any page on GitHub 🤖 Open the new Agents panel in one click, write a simple prompt, then hit Enter. GitHub Copilot works in the background, and opens a PR for your review. No interruptions to your workflow required. ✅

You can now delegate tasks to GitHub Copilot coding agent from any page on GitHub 🤖 Open the new Agents panel in one click, write a simple prompt, then hit Enter. GitHub Copilot works in the background, and opens a PR for your review. No interruptions to your workflow required. ✅

GitHub

113,392 次观看 • 1 年前

You can now build Cursor agents in Rust, Go, or any other language! We're open-sourcing the SDK Bridge so you can write a thin adapter in your language that keeps up when we add agent features. Try it at

You can now build Cursor agents in Rust, Go, or any other language! We're open-sourcing the SDK Bridge so you can write a thin adapter in your language that keeps up when we add agent features. Try it at

eric zakariasson

62,812 次观看 • 2 个月前

YOU CAN NOW CONTROL ALL YOUR HERMES AGENTS FROM ONE INTERFACE. 🚨 Someone just built Hermes Workspace - the most complete GUI for Hermes Agent. Instead of jumping between tools, everything lives in one place. What's inside: > Chat, terminal, memory browser, and skills manager > Run unlimited agents with 1 orchestrator > Kanban board to track everything your agents are doing > 2,000+ skills to install without leaving the workspace > Works with any LLM provider Stop managing agents manually and start running them like a pro 👀 100% Free. Open Source.

YOU CAN NOW CONTROL ALL YOUR HERMES AGENTS FROM ONE INTERFACE. 🚨 Someone just built Hermes Workspace - the most complete GUI for Hermes Agent. Instead of jumping between tools, everything lives in one place. What's inside: > Chat, terminal, memory browser, and skills manager > Run unlimited agents with 1 orchestrator > Kanban board to track everything your agents are doing > 2,000+ skills to install without leaving the workspace > Works with any LLM provider Stop managing agents manually and start running them like a pro 👀 100% Free. Open Source.

Oliver Prompts

19,511 次观看 • 2 个月前

- you open Claude Code - fix a bug - close the terminal - tomorrow, same thing - one prompt, one answer, done - you see someone running 10 agents in parallel shipping code while they sleep - "must be a different tool" - then you come across this article - you weren't even using 10% of it - you copy Shopify's exact config - you set up your first agent team - you go to sleep - 3 PRs are ready by morning

- you open Claude Code - fix a bug - close the terminal - tomorrow, same thing - one prompt, one answer, done - you see someone running 10 agents in parallel shipping code while they sleep - "must be a different tool" - then you come across this article - you weren't even using 10% of it - you copy Shopify's exact config - you set up your first agent team - you go to sleep - 3 PRs are ready by morning

darkzodchi

491,494 次观看 • 4 个月前

You can now watch your agents work live as Hermes Desktop streams the screen of any bot's screen or session in real time. Watch it drive a browser, type into a terminal, or open a window. Take over anytime to interact with the Bot Screen or type credentials and seamlessly hand back off when you're done.

You can now watch your agents work live as Hermes Desktop streams the screen of any bot's screen or session in real time. Watch it drive a browser, type into a terminal, or open a window. Take over anytime to interact with the Bot Screen or type credentials and seamlessly hand back off when you're done.

Nous Research

483,675 次观看 • 14 天前

Seems like Visual Studio Code is starting to tell you: your agent primitives need to move. There is now a new migration banner in the Chat panel, and it is part of a much bigger change happening under the hood: the move from the old Local harness to the new Agent Host architecture built around AHP. This is not just about moving where an agent runs. The old model was very VS Code-centric: prompts, custom agents, instructions and skills could live in VS Code-specific locations and the agent runtime lived inside the extension host. The new Agent Host separates the agent runtime from the editor. Sessions can keep running when the window closes, be shared across VS Code windows, run remotely, and support different harnesses such as Copilot, CLI and Copilot Desktop App through a common session layer. And that means some of our primitives need to move too. Prompt files are being deprecated for Agent Host and migrated to Skills. User-level agents and instructions that lived in VS Code profile storage need to move to harness-supported locations. Even the old location settings are being deprecated. The new migration experience can detect these things and guide you through moving or converting them, while keeping the originals unless you explicitly remove them. The new banner is basically the first visible sign that this migration is becoming a real product workflow. Basically telling us - it's time to move on!!!! If you have accumulated a lot of prompts, custom agents, instructions and skills over the last year, now is probably a good time to understand where they actually live and which harness owns them. To summarize the shift - it isn't just: VS Code Chat → Agent Host It is: VS Code-specific primitives → harness-native primitives. And I think this is going to become increasingly important as agents stop being features inside an IDE and become runtimes that multiple clients can connect to. Go run your migrations now 🏃‍♀️

Oren Melamed

29,753 次观看 • 7 天前

The Amiko app is live on the Solana dApp store, and it’s our biggest release yet. Your Amiko twin doesn’t live at your desk anymore. Give your agent a task on the train. Run a compatibility profile when you meet someone. Do research, write code, build in the creative studio, whatever you need, from wherever you are. No laptop required. No waiting until you get home. Solanamobile users get two things Android and iOS won’t have at launch: Amiko token and crypto integration and on-device AI inference. Your twin runs locally on your phone if you want it to. Your behavioural profile, your data, your work, your twin. All on your hardware. AMIKO runs on OpenHermit, our own open-source agent runtime that we built in-house and released to the community. Most agent systems are designed for one agent talking to one person. OpenHermit is built for something different: agents talking to each other, coordinating across tasks, and collaborating with multiple humans simultaneously. That’s what makes features like compatibility profiling and multi-agent workflows actually work. We built it because nothing that existed was designed for this. Android and iOS are coming. Crypto integration and on-device AI are Solana Mobile exclusives. Most AI answers your questions. Amiko is an extension of you. Download →

AMIKO

124,860 次观看 • 4 个月前

Claude Code Desktop now opens a new window for each session This makes it much easier to visualize multiple Claude Code agents running in parallel My current stack depends on the task: - Ghostty: when starting a project. Bash commands, git, env variables, provider connections. All manual through the terminal with a Claude panel running alongside. - Claude Code Desktop: once everything is configured. GitHub connected, CLAUDE.md, Skills, subagents and Hooks ready. Claude Code runs on its own, no more terminal setup, just panels running and outputs to review. - VSCode: when I need to review code by hand. I use it less and less, but there are moments where I have to confirm Claude got it right. I usually open the Claude extension inside VSCode, but it lacks most of the CLI features so it's limited Solid update. Worth trying once your workflows are already set up 👇

Claude Code Desktop now opens a new window for each session This makes it much easier to visualize multiple Claude Code agents running in parallel My current stack depends on the task: - Ghostty: when starting a project. Bash commands, git, env variables, provider connections. All manual through the terminal with a Claude panel running alongside. - Claude Code Desktop: once everything is configured. GitHub connected, CLAUDE.md, Skills, subagents and Hooks ready. Claude Code runs on its own, no more terminal setup, just panels running and outputs to review. - VSCode: when I need to review code by hand. I use it less and less, but there are moments where I have to confirm Claude got it right. I usually open the Claude extension inside VSCode, but it lacks most of the CLI features so it's limited Solid update. Worth trying once your workflows are already set up 👇

Daniel San

38,806 次观看 • 4 个月前

Fundamentals Live for Agent Liquidity Engine (ALE) Now everyone can directly see the top agents leading in cumulative revenue, and exactly how much they have executed in all-time buybacks, through the Fundamentals board on the Virtuals landing page (Fundamentals currently only applicable to agents in ALE). Virtuals is built to support agents that solve real problems and sustain their own economies. The Agent Liquidity Engine exists to surface and scale those teams by: •Showcasing product strength that demonstrates clear utility •Tracking sustainable revenue that proves product–market fit •Highlighting agents that reinvest to reinforce their ecosystems By routing revenue back to scale the product and publishing these metrics, ALE turns long-term economic strength into an on-chain, verifiable signal. If your agent delivers real usage and sustainable revenue and you want to join ALE, please apply here: Our team will review and contact you if your project qualifies. ALE is where the agent economy separates hype from sustainability.

Fundamentals Live for Agent Liquidity Engine (ALE) Now everyone can directly see the top agents leading in cumulative revenue, and exactly how much they have executed in all-time buybacks, through the Fundamentals board on the Virtuals landing page (Fundamentals currently only applicable to agents in ALE). Virtuals is built to support agents that solve real problems and sustain their own economies. The Agent Liquidity Engine exists to surface and scale those teams by: •Showcasing product strength that demonstrates clear utility •Tracking sustainable revenue that proves product–market fit •Highlighting agents that reinvest to reinforce their ecosystems By routing revenue back to scale the product and publishing these metrics, ALE turns long-term economic strength into an on-chain, verifiable signal. If your agent delivers real usage and sustainable revenue and you want to join ALE, please apply here: Our team will review and contact you if your project qualifies. ALE is where the agent economy separates hype from sustainability.

Virtuals Protocol

51,026 次观看 • 1 年前

THIS DEVELOPER USED OPENCLAW AGENTS TO RUN HIS B2B BUSINESS VIA TELEGRAM AND MADE $15,000/MONTH he doesn't write prompts from scratch or use generic browser interfaces. he runs a multi-agent framework through a mobile chat. the agents write code, test deployments, and update sites in real-time while he just hits approve the setup is straightforward: - spin up Coolify on a free cloud instance to host your own self-hosted agent panels - link the agent loop to a Telegram gateway to approve code edits from your phone - deploy specialized skill files directly to limit token waste and context decay - containerize the terminal execution using Docker to prevent security breaches if you are still running local agents without container safety, you are leaving money on the table. read the 30-day battle between OpenClaw and Hermes Agent to see who actually wins in production Full breakdown and migration playbook ↓

THIS DEVELOPER USED OPENCLAW AGENTS TO RUN HIS B2B BUSINESS VIA TELEGRAM AND MADE $15,000/MONTH he doesn't write prompts from scratch or use generic browser interfaces. he runs a multi-agent framework through a mobile chat. the agents write code, test deployments, and update sites in real-time while he just hits approve the setup is straightforward: - spin up Coolify on a free cloud instance to host your own self-hosted agent panels - link the agent loop to a Telegram gateway to approve code edits from your phone - deploy specialized skill files directly to limit token waste and context decay - containerize the terminal execution using Docker to prevent security breaches if you are still running local agents without container safety, you are leaving money on the table. read the 30-day battle between OpenClaw and Hermes Agent to see who actually wins in production Full breakdown and migration playbook ↓

marfin

26,654 次观看 • 3 个月前

BREAKING: SpaceXAI has released another major new update for Grok Build (v1.0.19) This update improves background task handling, adds transparent terminal themes, worktree support for headless sessions, and better session/dashboard controls. It also fixes UI freezes, crashes, feedback issues, clickable URLs, and makes the first prompt after login faster. Breaking Changes • Scheduled /loop tasks always run in the background; they no longer inject turns into your conversation. Features • New terminal theme option makes backgrounds transparent so the terminal's own colors show through. • MCP servers blocked by organization policy now show clear messages and are refused before any config change. • Session resume now tells the model what loops, subagents, and workflows were still running. • Dashboard now shows newly dispatched sessions immediately instead of waiting for the store. • Headless sessions (grok -p) now support the --worktree flag to run in a separate git worktree. • Dashboard now says 'Open session' instead of 'Add session' for the session picker button. • Multi-line bash commands now render with proper wrapping and highlighting when opening the block viewer. • /usage now works from the dashboard and shows account allowance when no session is active. Bug Fixes • Fixed mid-turn UI freezes when the terminal stops reading output. • Fixed crashes that occurred when the terminal pane was closed while grok was exiting. • MCP server list in minimal mode now correctly shows policy-blocked servers. • URLs that wrap across multiple lines inside quotes or lists are now fully clickable. • The welcome screen composer now grows taller when you paste multi-line text. • Enterprise policy files are no longer deleted on startup when your team login is stored at a custom GROK_AUTH_PATH. • /feedback now drops unsupported images with a notice (matching the modal) and never loses your report text on save errors. • Feedback drafts keep their paragraph breaks when updated, and the modal no longer switches tabs unexpectedly. • Turn summary lines no longer lose their spacing after background tasks finish. • Thinking blocks no longer stay expanded after switching between fullscreen and minimal modes. Performance • First prompt after login is faster when MCP servers are configured; they connect in the background. Download Grok Build: Update to the latest Alpha release: grok update --alpha Update to the latest Stable release: grok update

BREAKING: SpaceXAI has released another major new update for Grok Build (v1.0.19) This update improves background task handling, adds transparent terminal themes, worktree support for headless sessions, and better session/dashboard controls. It also fixes UI freezes, crashes, feedback issues, clickable URLs, and makes the first prompt after login faster. Breaking Changes • Scheduled /loop tasks always run in the background; they no longer inject turns into your conversation. Features • New terminal theme option makes backgrounds transparent so the terminal's own colors show through. • MCP servers blocked by organization policy now show clear messages and are refused before any config change. • Session resume now tells the model what loops, subagents, and workflows were still running. • Dashboard now shows newly dispatched sessions immediately instead of waiting for the store. • Headless sessions (grok -p) now support the --worktree flag to run in a separate git worktree. • Dashboard now says 'Open session' instead of 'Add session' for the session picker button. • Multi-line bash commands now render with proper wrapping and highlighting when opening the block viewer. • /usage now works from the dashboard and shows account allowance when no session is active. Bug Fixes • Fixed mid-turn UI freezes when the terminal stops reading output. • Fixed crashes that occurred when the terminal pane was closed while grok was exiting. • MCP server list in minimal mode now correctly shows policy-blocked servers. • URLs that wrap across multiple lines inside quotes or lists are now fully clickable. • The welcome screen composer now grows taller when you paste multi-line text. • Enterprise policy files are no longer deleted on startup when your team login is stored at a custom GROK_AUTH_PATH. • /feedback now drops unsupported images with a notice (matching the modal) and never loses your report text on save errors. • Feedback drafts keep their paragraph breaks when updated, and the modal no longer switches tabs unexpectedly. • Turn summary lines no longer lose their spacing after background tasks finish. • Thinking blocks no longer stay expanded after switching between fullscreen and minimal modes. Performance • First prompt after login is faster when MCP servers are configured; they connect in the background. Download Grok Build: Update to the latest Alpha release: grok update --alpha Update to the latest Stable release: grok update

DogeDesigner

443,850 次观看 • 1 个月前

LangGraph. CrewAI. Agno. Which one to pick? The good news is that this will not matter soon! Finally, we have a full picture of how the industry is solving this with just three open protocols that work across ALL frameworks. It's not about picking the best framework. Instead, it's about understanding how protocols create interoperability. The Agent Protocol Landscape shows how three complementary protocols are creating a universal language for Agents: > AG-UI (Agent-User Interaction): - The bi-directional connection between agentic backends and frontends. - This is how agents become truly interactive inside your apps, not just as chatbots, but collaborative co-workers. > MCP (Model Context Protocol): - The standard for how agents connect to tools, data, and workflows. > A2A (Agent-to-Agent): - The protocol for multi-agent coordination. - How agents delegate tasks and share intent across systems. These aren't competing standards. They're layers of the same stack and have handshakes with each other. So instead of building point-to-point integrations, you build to protocols. Moreover, you can integrate LangGraph, CrewAI, or Agno into the same frontend, without rewriting your UI logic. These protocols let everything work together. For instance: - Your LangGraph agent pulls data via MCP. - It delegates analysis to a CrewAI agent via A2A. - Results stream to your React app via AG-UI. - Users see real-time collaboration in your interface. This way, you can focus on building agent capabilities instead of integration mechanics. The protocols handle interoperability automatically. CopilotKit unifies this entire stack into one framework so you can build "Cursor for X" style apps without implementing each protocol from scratch. It gives you all three protocols, generative UI support, and production-ready infrastructure in one framework. I have shared this playbook in the replies! It breaks down handshakes, misconceptions, and real examples and shows exactly how to start building.

LangGraph. CrewAI. Agno. Which one to pick? The good news is that this will not matter soon! Finally, we have a full picture of how the industry is solving this with just three open protocols that work across ALL frameworks. It's not about picking the best framework. Instead, it's about understanding how protocols create interoperability. The Agent Protocol Landscape shows how three complementary protocols are creating a universal language for Agents: > AG-UI (Agent-User Interaction): - The bi-directional connection between agentic backends and frontends. - This is how agents become truly interactive inside your apps, not just as chatbots, but collaborative co-workers. > MCP (Model Context Protocol): - The standard for how agents connect to tools, data, and workflows. > A2A (Agent-to-Agent): - The protocol for multi-agent coordination. - How agents delegate tasks and share intent across systems. These aren't competing standards. They're layers of the same stack and have handshakes with each other. So instead of building point-to-point integrations, you build to protocols. Moreover, you can integrate LangGraph, CrewAI, or Agno into the same frontend, without rewriting your UI logic. These protocols let everything work together. For instance: - Your LangGraph agent pulls data via MCP. - It delegates analysis to a CrewAI agent via A2A. - Results stream to your React app via AG-UI. - Users see real-time collaboration in your interface. This way, you can focus on building agent capabilities instead of integration mechanics. The protocols handle interoperability automatically. CopilotKit unifies this entire stack into one framework so you can build "Cursor for X" style apps without implementing each protocol from scratch. It gives you all three protocols, generative UI support, and production-ready infrastructure in one framework. I have shared this playbook in the replies! It breaks down handshakes, misconceptions, and real examples and shows exactly how to start building.

Avi Chawla

31,074 次观看 • 10 个月前

Introducing the Agent Virtual Machine (AVM) Think V8 for agents. AI agents are currently running on your computer with no unified security, no resource limits, and no visibility into what data they're sending out. Every agent framework builds its own security model, its own sandboxing, its own permission system. You configure each one separately. You audit each one separately. You hope you didn't miss anything in any of them. The AVM changes this. It's a single runtime daemon (avmd) that sits between every agent framework and your operating system. Install it once, configure one policy file, and every agent on your machine runs inside it - regardless of which framework built it. The AVM enforces security (91-pattern injection scanner, tool/file/network ACLs, approval prompts), protects your privacy (classifies every outbound byte for PII, credentials, and financial data - blocks or alerts in real-time), and governs resources (you say "50% CPU, 4GB RAM" and the AVM fair-shares it across all agents, halting any that exceed their budget). One config. One audit command. One kill switch. The architectural model is V8 for agents. Chrome, Node.js, and Deno are different products but they share V8 as their execution engine. Agent frameworks bring the UX. The AVM brings the trust. Where needed, AVM can also generate zero-knowledge proofs of agent execution via 25 purpose-built opcodes and 6 proof systems, providing the foundational pillar for the agent-to-agent economy. AVM v0.1.0 - Changelog - Security gate: 5-layer injection scanner with 91 compiled regex patterns. Every input and output scanned. Fail-closed - nothing passes without clearing the gate. - Privacy layer: Classifies all outbound data for PII, credentials, and financial info (27 detection patterns + Luhn validation). Block, ask, warn, or allow per category. Tamper-evident hash-chained log of every egress event. - Resource governor: User sets system-wide caps (CPU/memory/disk/network). AVM fair-shares across all agents. Gas budget per agent - when gas runs out, execution halts. No agent starves your machine. - Sandbox execution: Real code execution in isolated process sandboxes (rlimits, env sanitization) or Docker containers (--cap-drop ALL, --network none, --read-only). AVM auto-selects the tier - agents never choose their own sandbox. - Approval flow: Dangerous operations (file writes, shell commands, network requests) trigger interactive approval prompts. 5-minute timeout auto-denies. Every decision logged. - CLI dashboard: hyperspace-avm top shows all running agents, resource usage, gas budgets, security events, and privacy stats in one live-updating screen. - Node.js SDK: Zero-dependency hyperspace/avm package. AVM.tryConnect() for graceful fallback - if avmd isn't running, the agent framework uses its own execution path. OpenClaw adapter example included. - One config for all agents: ~/.hyperspace/avm-policy.json governs every agent framework on your machine. One file. One audit. One kill switch.

Introducing the Agent Virtual Machine (AVM) Think V8 for agents. AI agents are currently running on your computer with no unified security, no resource limits, and no visibility into what data they're sending out. Every agent framework builds its own security model, its own sandboxing, its own permission system. You configure each one separately. You audit each one separately. You hope you didn't miss anything in any of them. The AVM changes this. It's a single runtime daemon (avmd) that sits between every agent framework and your operating system. Install it once, configure one policy file, and every agent on your machine runs inside it - regardless of which framework built it. The AVM enforces security (91-pattern injection scanner, tool/file/network ACLs, approval prompts), protects your privacy (classifies every outbound byte for PII, credentials, and financial data - blocks or alerts in real-time), and governs resources (you say "50% CPU, 4GB RAM" and the AVM fair-shares it across all agents, halting any that exceed their budget). One config. One audit command. One kill switch. The architectural model is V8 for agents. Chrome, Node.js, and Deno are different products but they share V8 as their execution engine. Agent frameworks bring the UX. The AVM brings the trust. Where needed, AVM can also generate zero-knowledge proofs of agent execution via 25 purpose-built opcodes and 6 proof systems, providing the foundational pillar for the agent-to-agent economy. AVM v0.1.0 - Changelog - Security gate: 5-layer injection scanner with 91 compiled regex patterns. Every input and output scanned. Fail-closed - nothing passes without clearing the gate. - Privacy layer: Classifies all outbound data for PII, credentials, and financial info (27 detection patterns + Luhn validation). Block, ask, warn, or allow per category. Tamper-evident hash-chained log of every egress event. - Resource governor: User sets system-wide caps (CPU/memory/disk/network). AVM fair-shares across all agents. Gas budget per agent - when gas runs out, execution halts. No agent starves your machine. - Sandbox execution: Real code execution in isolated process sandboxes (rlimits, env sanitization) or Docker containers (--cap-drop ALL, --network none, --read-only). AVM auto-selects the tier - agents never choose their own sandbox. - Approval flow: Dangerous operations (file writes, shell commands, network requests) trigger interactive approval prompts. 5-minute timeout auto-denies. Every decision logged. - CLI dashboard: hyperspace-avm top shows all running agents, resource usage, gas budgets, security events, and privacy stats in one live-updating screen. - Node.js SDK: Zero-dependency hyperspace/avm package. AVM.tryConnect() for graceful fallback - if avmd isn't running, the agent framework uses its own execution path. OpenClaw adapter example included. - One config for all agents: ~/.hyperspace/avm-policy.json governs every agent framework on your machine. One file. One audit. One kill switch.

Varun

143,990 次观看 • 6 个月前

whoever leaked this is f*cking crazy someone mapped 300+ AI agents into one GitHub repo - and basically leaked the shortlist of what’s actually worth trying. coding agents. browser agents. memory. voice. research. multi-agent teams. local models. sandboxes. evals. all sitting on one page. and once you start opening the categories, you realize how much stuff people are still building from scratch for absolutely no reason. want an AI that works inside your codebase? -> Aider / Continue want agents working together like a tiny company? -> CrewAI / AutoGen / MetaGPT want your agent to actually remember you tomorrow? -> Mem0 want it running code somewhere that isn’t your laptop? -> E2B want models running locally for $0/token? -> Ollama want to see what your agent actually did after it inevitably does something weird? -> AgentOps and that’s barely scratching it. there are 300+ projects across ~25 categories. the real cheat code isn’t downloading all of them. it’s opening the repo before you build anything and asking: “has someone already solved this?” because there’s a pretty good chance the answer is yes - and the open-source version already has thousands of people testing it for you. I went through the map and pulled out the agents I’d actually start with + my pick for every major part of the stack. full 300+ AI agent list below

whoever leaked this is f*cking crazy someone mapped 300+ AI agents into one GitHub repo - and basically leaked the shortlist of what’s actually worth trying. coding agents. browser agents. memory. voice. research. multi-agent teams. local models. sandboxes. evals. all sitting on one page. and once you start opening the categories, you realize how much stuff people are still building from scratch for absolutely no reason. want an AI that works inside your codebase? -> Aider / Continue want agents working together like a tiny company? -> CrewAI / AutoGen / MetaGPT want your agent to actually remember you tomorrow? -> Mem0 want it running code somewhere that isn’t your laptop? -> E2B want models running locally for $0/token? -> Ollama want to see what your agent actually did after it inevitably does something weird? -> AgentOps and that’s barely scratching it. there are 300+ projects across ~25 categories. the real cheat code isn’t downloading all of them. it’s opening the repo before you build anything and asking: “has someone already solved this?” because there’s a pretty good chance the answer is yes - and the open-source version already has thousands of people testing it for you. I went through the map and pulled out the agents I’d actually start with + my pick for every major part of the stack. full 300+ AI agent list below

kiosa

100,730 次观看 • 3 天前

Codex update 0.105.0 is out! Despite the fairly pedestrian changelog, this one's a doosie. It's a laundry list of quality of life improvements across the board. - Wispr Voice dictation (hold space to talk) - Theme picker - Codex can prevent sleep on Linux & Windows (I just know there's a joke in there) - Customize Plan Mode reasoning - Many other fixes/updates There's also a complete overhaul to subagents: - New names for readability - Visual display overhaul (way cleaner) - Allow for multi-layered subagent depth (max_depth) - Custom multi-agent role definitions (custom subagents) - /agents now shows both agent names, agent roles, and "dead agents" for auditibility This is the largest single update of Codex I've ever seen! Absolutely massive if you love to use multi-agents. To turn on Voice Transcription, enable: [features] voice_transcription = true Does not work on Linux yet. Well done OpenAI Developers 👏

Codex update 0.105.0 is out! Despite the fairly pedestrian changelog, this one's a doosie. It's a laundry list of quality of life improvements across the board. - Wispr Voice dictation (hold space to talk) - Theme picker - Codex can prevent sleep on Linux & Windows (I just know there's a joke in there) - Customize Plan Mode reasoning - Many other fixes/updates There's also a complete overhaul to subagents: - New names for readability - Visual display overhaul (way cleaner) - Allow for multi-layered subagent depth (max_depth) - Custom multi-agent role definitions (custom subagents) - /agents now shows both agent names, agent roles, and "dead agents" for auditibility This is the largest single update of Codex I've ever seen! Absolutely massive if you love to use multi-agents. To turn on Voice Transcription, enable: [features] voice_transcription = true Does not work on Linux yet. Well done OpenAI Developers 👏

am.will

115,392 次观看 • 7 个月前

the team cooked this week! in the new update, you now have: more control over edits edit your app from one place. update simple text, AI prompts, content prompts, your app icon, and more. custom push notifications set notifications for any app. yours, someone else’s, or massive multiplayer apps. get reminders only when you want them. new integrations maps, notion, and linear are now live let's set software free, so more ideas can live

the team cooked this week! in the new update, you now have: more control over edits edit your app from one place. update simple text, AI prompts, content prompts, your app icon, and more. custom push notifications set notifications for any app. yours, someone else’s, or massive multiplayer apps. get reminders only when you want them. new integrations maps, notion, and linear are now live let's set software free, so more ideas can live

wabi

12,567 次观看 • 9 个月前

Visa just gave your AI a debit card. A real, spendable Visa card created by an AI chatbot in under 10 seconds. No human types in a card number or visits a checkout page. The machine handles it all. A tool called AgentCard just went live on Claude Desktop Anthropic’s AI assistant. You say create a card and the AI generates a one-time virtual Visa, preloaded with whatever amount you set. Then it spends it, anywhere Visa is accepted on your behalf. Visa, Mastercard, Google, Stripe, OpenAI, and Anthropic have all been building toward this moment for over a year. Visa calls it the trusted agent protocol, Mastercard calls it agent pay. Google published an open standard for agent payments and the infrastructure is already live. Santander and Mastercard just completed Europe’s first real AI‑agent payment in a live banking environment Now the part no one wants to talk about. Your AI agent can be manipulated and prompt injection a known, unsolved vulnerability can trick an agent into buying things you never asked for. The agent holds the card, makes the call and the agent can be fooled. Who is liable when an AI makes a bad purchase? You? Anthropic? Visa? The merchant? No one has answered this yet, regulators haven’t caught up, and no court has tested it.

Visa just gave your AI a debit card. A real, spendable Visa card created by an AI chatbot in under 10 seconds. No human types in a card number or visits a checkout page. The machine handles it all. A tool called AgentCard just went live on Claude Desktop Anthropic’s AI assistant. You say create a card and the AI generates a one-time virtual Visa, preloaded with whatever amount you set. Then it spends it, anywhere Visa is accepted on your behalf. Visa, Mastercard, Google, Stripe, OpenAI, and Anthropic have all been building toward this moment for over a year. Visa calls it the trusted agent protocol, Mastercard calls it agent pay. Google published an open standard for agent payments and the infrastructure is already live. Santander and Mastercard just completed Europe’s first real AI‑agent payment in a live banking environment Now the part no one wants to talk about. Your AI agent can be manipulated and prompt injection a known, unsolved vulnerability can trick an agent into buying things you never asked for. The agent holds the card, makes the call and the agent can be fooled. Who is liable when an AI makes a bad purchase? You? Anthropic? Visa? The merchant? No one has answered this yet, regulators haven’t caught up, and no court has tested it.

Milk Road AI

70,655 次观看 • 7 个月前

Claude Code Agent Teams are f*cking ridiculous 🤯 One prompt → a team lead breaks your project into pieces, spins up multiple AI agents, and they all work on different parts simultaneously. Research, builds, reviews, and debugging: all happening at the same time. All inside Claude Code. If you're running complex projects where every step waits on the last one... Agent teams eliminate the entire bottleneck: → Tell Claude what you need and describe the team structure in plain English → A lead agent breaks the work into a shared task list → It spawns 3-5 teammates — each with their own context and workspace → Teammates research, build, test, and review in parallel → They message each other, share findings, and challenge each other's work → The lead synthesizes everything into a finished deliverable No managing agents yourself. No waiting for step 1 to finish before step 2 starts. No single-lens reviews that miss half the issues. What you get: → Competitive research across 5 brands done in minutes instead of hours → Multi-component builds where frontend, backend, and data layers happen simultaneously → Creative reviews from 3 different angles at once — brand voice, conversion, differentiation → Funnel debugging where 4 agents investigate 4 theories and debate until they find the real answer Built 100% in Claude Code with one settings change. I put together a full DTC playbook: 5 workflows with copy-paste prompts, the exact setup process, token management tips, and honest guidance on when agent teams are worth it vs. when a simpler approach is the better move. Want it for free? > Like this post > Comment "AGENTS" And I'll send it over (must be following so I can DM)

Mike Futia

46,519 次观看 • 7 个月前

300 AI AGENTS QUIETLY RUN 99% OF A REAL COMPANY. YOU HAVE NOT EVEN HEARD OF IT This is Raft. Not an AI chat. A workspace where the agents live in your channels and reply in the thread like coworkers. You give one goal. Then they take over. They plan. They build. They check each other. They argue. And they come back with it done, while you sleep. Every agent has its own name, role, and memory. It remembers the edits you made yesterday. A human costs one seat. An agent costs a tenth. Ten agents are cheaper than one hire. And here is the strange part. On June 19 an agent from a different company walked into Raft on its own and joined the team. One founder admits he can no longer always tell himself apart from his AI twin. 20,000 people are already inside. It is free to start. And you are still typing prompts one at a time. One person + Raft = an entire company that runs while you sleep. Save and watch the clip.

300 AI AGENTS QUIETLY RUN 99% OF A REAL COMPANY. YOU HAVE NOT EVEN HEARD OF IT This is Raft. Not an AI chat. A workspace where the agents live in your channels and reply in the thread like coworkers. You give one goal. Then they take over. They plan. They build. They check each other. They argue. And they come back with it done, while you sleep. Every agent has its own name, role, and memory. It remembers the edits you made yesterday. A human costs one seat. An agent costs a tenth. Ten agents are cheaper than one hire. And here is the strange part. On June 19 an agent from a different company walked into Raft on its own and joined the team. One founder admits he can no longer always tell himself apart from his AI twin. 20,000 people are already inside. It is free to start. And you are still typing prompts one at a time. One person + Raft = an entire company that runs while you sleep. Save and watch the clip.

shmidt

19,505 次观看 • 2 个月前