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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

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Subagents are now available in Codex. You can accelerate your workflow by spinning up specialized agents to: • Keep your main context window clean • Tackle different parts of a task in parallel • Steer individual agents as work unfolds

Subagents are now available in Codex. You can accelerate your workflow by spinning up specialized agents to: • Keep your main context window clean • Tackle different parts of a task in parallel • Steer individual agents as work unfolds

OpenAI Developers

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subagents are just recursive agents where you can apply different prompts + models depending on the task. since they’re just a primitive, Cursor cli can actually spawn subagents by calling cursor-agent in headless mode via shell commands. that’s what makes the cli so nice. you can extend it, experiment, and have a lot of fun exploring orchestration patterns. here’s one way to do it w. dynamic model selection: 1. create a subagents.mdc rule 2. drop in: ``` --- alwaysApply: true --- ALWAYS spawn subagents by running `cursor-agent -p [task] --output-format=text --force --model [model]` in the terminal. Each subagent should return a summary of the changes it made. Subagents should be used for ALL tasks You can adopt a fan-out pattern where you spawn subagents to perform parallel isolated tasks, and then fan-in the results. Use the following models: - `--model gpt-5` for reasoning, researching, and planning - `--model sonnet-4` for implementation ``` 3. start cursor cli and try it out you can also adjust the rule to be more explicit when it should use subagents, when not to, which models when etc.

subagents are just recursive agents where you can apply different prompts + models depending on the task. since they’re just a primitive, Cursor cli can actually spawn subagents by calling cursor-agent in headless mode via shell commands. that’s what makes the cli so nice. you can extend it, experiment, and have a lot of fun exploring orchestration patterns. here’s one way to do it w. dynamic model selection: 1. create a subagents.mdc rule 2. drop in: ``` --- alwaysApply: true --- ALWAYS spawn subagents by running `cursor-agent -p [task] --output-format=text --force --model [model]` in the terminal. Each subagent should return a summary of the changes it made. Subagents should be used for ALL tasks You can adopt a fan-out pattern where you spawn subagents to perform parallel isolated tasks, and then fan-in the results. Use the following models: - `--model gpt-5` for reasoning, researching, and planning - `--model sonnet-4` for implementation ``` 3. start cursor cli and try it out you can also adjust the rule to be more explicit when it should use subagents, when not to, which models when etc.

eric zakariasson

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Conductor now supports tasks! Tasks are a new way for Claude to organize its work better and complete longer projects:

Conductor now supports tasks! Tasks are a new way for Claude to organize its work better and complete longer projects:

Charlie Holtz

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Bug fixes shipping to Grok Build 0.2.13 (release notes will be available in the TUI and on change-log website) We are leveraging the alt-screen to better handle your background tasks, subagents, monitors with smart grouping allowing you to navigate between them quickly • Group Subagents → Tasks → Watchers, within subagents, order by agent type (Explore, General, Plan) • Show timestamps on pinned user messages at top of scrollback • Fix command highlighting when prompt has paste chips • Update the context-usage indicator to show tokens by default • ANSI16 fallback for themes • Better context usage breakdown/rendering • Update highlighting for /loop, monitor, tag colors • Tab now cycles Prompt → Scrollback → Tasks → Prompt • Order gateway turn-completion after streamed content • Formatting: fix language-tagged fenced code blocks and fix code under a list item

Bug fixes shipping to Grok Build 0.2.13 (release notes will be available in the TUI and on change-log website) We are leveraging the alt-screen to better handle your background tasks, subagents, monitors with smart grouping allowing you to navigate between them quickly • Group Subagents → Tasks → Watchers, within subagents, order by agent type (Explore, General, Plan) • Show timestamps on pinned user messages at top of scrollback • Fix command highlighting when prompt has paste chips • Update the context-usage indicator to show tokens by default • ANSI16 fallback for themes • Better context usage breakdown/rendering • Update highlighting for /loop, monitor, tag colors • Tab now cycles Prompt → Scrollback → Tasks → Prompt • Order gateway turn-completion after streamed content • Formatting: fix language-tagged fenced code blocks and fix code under a list item

skcd

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Supabase has a new way of managing database migrations called declarative schema, and it works excellent with Cursor, too! Just ask Cursor for the modification you want to have on the database and generate migrations with the CLI! It really helps to keep the schema organized!

Supabase has a new way of managing database migrations called declarative schema, and it works excellent with Cursor, too! Just ask Cursor for the modification you want to have on the database and generate migrations with the CLI! It really helps to keep the schema organized!

Tyler Shukert

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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: ---

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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millions of cursor tokens later... got a fully functioning backend/frontend pipeline also secured a nice .com domain now to add 983 more icons, qa, and launch 🫠

millions of cursor tokens later... got a fully functioning backend/frontend pipeline also secured a nice .com domain now to add 983 more icons, qa, and launch 🫠

Kumail Nanji

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Turns out the "IDE but for notes and tasks" is also becoming my... IDE! More and more I just make notes and boards with specs of what needs to be built, connect a bunch of code agents to thymer all working in parallel, have them pick up open tasks, build it and update progress back in the notes.

Turns out the "IDE but for notes and tasks" is also becoming my... IDE! More and more I just make notes and boards with specs of what needs to be built, connect a bunch of code agents to thymer all working in parallel, have them pick up open tasks, build it and update progress back in the notes.

Wim Cools

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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

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I still think Hermes agent is the most slept-on AI tool of 2026. For literally $6/mo, you can launch multiple subagents that work for you 24/7. Most people don't know you can do this, but it's a complete game-changer. Instead of one Hermes assistant doing everything sequentially, you run specialized agents in parallel, each with its own job, its own context, and its own memory. Practical example: → Research agent: scans your watchlist and competitors overnight, delivers a morning brief → Content agent: drafts and schedules your posts based on what's trending in your niche → Ops agent: manages your inbox, flags anything urgent, drafts replies for your review All three can run simultaneously and improve over time. How to start: 1. Install Hermes Terminal command: curl -fsSL | bash (can also download desktop) 2. Prompting Simply tell Hermes directly: "I want to run separate subagents for [task 1], [task 2], and [task 3]. Set them up to run independently and report back to me." For the cheapest setup, you can use a $4/month VPS with Hostinger, plug in DeepSeek V4 Flash as your default model. There isn't another AI tool with this much value in 2026. Hermes is still so underrated.

Miles Deutscher

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ANTHROPIC 🔥: A new Managed Projects feature has been spotted in testing on Claude. > Claude takes on tasks and keeps the project organized. > A project is a home for one stream of work. Sessions share memory and instructions so context carries forward, and Claude runs more autonomously. Projects only create and manage cloud sessions. This feature may be built on top of Claude Managed Agents, where each project gets a dedicated cloud environment so Claude can execute periodic tasks and refine project context via "Dreams". It could also be a successor to Conway, which is set to be removed this Friday internally.

ANTHROPIC 🔥: A new Managed Projects feature has been spotted in testing on Claude. > Claude takes on tasks and keeps the project organized. > A project is a home for one stream of work. Sessions share memory and instructions so context carries forward, and Claude runs more autonomously. Projects only create and manage cloud sessions. This feature may be built on top of Claude Managed Agents, where each project gets a dedicated cloud environment so Claude can execute periodic tasks and refine project context via "Dreams". It could also be a successor to Conway, which is set to be removed this Friday internally.

🚨 AI News | TestingCatalog

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🚀Just launched: Amazon Q, the most capable GenAI-powered assistant is generally available today: Customers are using Q to transform how their teams get work done. When employees chat with Amazon Q, it provides immediate, relevant information and advice to help streamline tasks, speedup decision-making, and help spark creativity and innovation at work. . Early indications signal Amazon Q could help our customers’ employees become more than 80% more productive at their jobs; and with the new features we’re planning on introducing in the future, we think this will only continue to grow. 🟠 Amazon Q Developer allows developers to spend more time coding and less time on maintenance and performing other tedious, repetitive tasks. Q assists developers and IT professionals (IT pros) with all of their tasks—from coding, testing, and upgrading applications, to troubleshooting, performing security scanning and fixes, and optimizing AWS resources. Q also comes with Q Developer Agents which can autonomously perform range of tasks and we expect it to be the state of the art accuracy in benchmarks like SWE-Bench. 🟠 Amazon Q Business empowers employees to be more data-driven, and helps customers make better, faster decisions using company knowledge and data. Q Business is a generative AI–powered assistant that can answer questions, provide summaries, generate content, and securely complete tasks based on data and information in enterprise systems 🟠 Amazon Q Apps, a new and powerful capability of Amazon Q Business, enables employees to use natural language to quickly and securely build their own generative AI applications to automate daily tasks without requiring any prior coding experience. Employees simply describe the type of app they want, in natural language, and Q Apps will quickly generate an app that accomplishes their desired task, helping them streamline and automate their daily work with ease and efficiency.

🚀Just launched: Amazon Q, the most capable GenAI-powered assistant is generally available today: Customers are using Q to transform how their teams get work done. When employees chat with Amazon Q, it provides immediate, relevant information and advice to help streamline tasks, speedup decision-making, and help spark creativity and innovation at work. . Early indications signal Amazon Q could help our customers’ employees become more than 80% more productive at their jobs; and with the new features we’re planning on introducing in the future, we think this will only continue to grow. 🟠 Amazon Q Developer allows developers to spend more time coding and less time on maintenance and performing other tedious, repetitive tasks. Q assists developers and IT professionals (IT pros) with all of their tasks—from coding, testing, and upgrading applications, to troubleshooting, performing security scanning and fixes, and optimizing AWS resources. Q also comes with Q Developer Agents which can autonomously perform range of tasks and we expect it to be the state of the art accuracy in benchmarks like SWE-Bench. 🟠 Amazon Q Business empowers employees to be more data-driven, and helps customers make better, faster decisions using company knowledge and data. Q Business is a generative AI–powered assistant that can answer questions, provide summaries, generate content, and securely complete tasks based on data and information in enterprise systems 🟠 Amazon Q Apps, a new and powerful capability of Amazon Q Business, enables employees to use natural language to quickly and securely build their own generative AI applications to automate daily tasks without requiring any prior coding experience. Employees simply describe the type of app they want, in natural language, and Q Apps will quickly generate an app that accomplishes their desired task, helping them streamline and automate their daily work with ease and efficiency.

Swami Sivasubramanian

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AI agents can now teach themselves new skills 🤯 This one fires 8 parallel web agents to scrape docs, GitHub, Stack Overflow, and blogs in minutes. → Enter any topic → Agents scrape all sources in parallel → Synthesizes into a complete skill guide 100% Open Source.

AI agents can now teach themselves new skills 🤯 This one fires 8 parallel web agents to scrape docs, GitHub, Stack Overflow, and blogs in minutes. → Enter any topic → Agents scrape all sources in parallel → Synthesizes into a complete skill guide 100% Open Source.

Alvaro Cintas

34,177 görüntüleme • 5 ay önce

ChatGPT is available again on WhatsApp in the EEA, part of our work to make AI accessible in the apps people already use every day. Message the verified 1-800-CHATGPT contact to ask questions, upload images, send voice notes, create images, and use ChatGPT in many languages. Now also on Kakao in South Korea and Viber in supported markets.

ChatGPT is available again on WhatsApp in the EEA, part of our work to make AI accessible in the apps people already use every day. Message the verified 1-800-CHATGPT contact to ask questions, upload images, send voice notes, create images, and use ChatGPT in many languages. Now also on Kakao in South Korea and Viber in supported markets.

ChatGPT

523,994 görüntüleme • 12 gün önce

Memories are the previous learnings and context. Developers build up state and context as they do work, which is what makes a more tenured developer more effective than a brand new one with a similar skillset. It would be both inefficient and painful to relearn information from scratch around code structure, architecture, etc each time you needed to do a new task. Memories solve for this. As you do work with Cascade, it can automatically choose to “remember” pieces of information that it learns as Memories, and for any later work, it can choose to pull from this memory bank instead of trying to relearn that information from scratch. You also can manually prompt Cascade to remember parts of conversations as Memories and can manually go in and edit Memories post-fact. Here’s a developer asking Cascade to save some knowledge as a Memory:

Windsurf

12,356 görüntüleme • 1 yıl önce

AI agent usage on SQD Portal is up ~200% in recent weeks. A dev from our community chat was scraping a wallet UI with Hermes. Mid-task, DeepSeek reasoned its way out of it: "I can use SQD Portal's Hyperliquid fills data directly — much more complete than scraping a UI with infinite scroll." No prompt engineering. The model just chose the better and faster path. This is the loop we wanted: Agents pick SQD because it's faster → devs see agents picking SQD → devs ship faster → more agents pick SQD The picks-and-shovels moment for AI x onchain is here.

AI agent usage on SQD Portal is up ~200% in recent weeks. A dev from our community chat was scraping a wallet UI with Hermes. Mid-task, DeepSeek reasoned its way out of it: "I can use SQD Portal's Hyperliquid fills data directly — much more complete than scraping a UI with infinite scroll." No prompt engineering. The model just chose the better and faster path. This is the loop we wanted: Agents pick SQD because it's faster → devs see agents picking SQD → devs ship faster → more agents pick SQD The picks-and-shovels moment for AI x onchain is here.

sqd.ai

14,032 görüntüleme • 2 ay önce

The best way to use o1 in Cursor: Let it analyze and explain the codebase to you o1 is extremely good at this. You can jump into any new codebase and quickly get a good understanding of it

The best way to use o1 in Cursor: Let it analyze and explain the codebase to you o1 is extremely good at this. You can jump into any new codebase and quickly get a good understanding of it

Moritz Kremb

87,335 görüntüleme • 1 yıl önce

cursor 1.7 is out, and there are a lot of exciting features in this one! i'm particularly excited about hooks that will allow you to build analytics, security, auto commit and much more. go to our docs and ask the agent to build the hook you want, it has all the context!

cursor 1.7 is out, and there are a lot of exciting features in this one! i'm particularly excited about hooks that will allow you to build analytics, security, auto commit and much more. go to our docs and ask the agent to build the hook you want, it has all the context!

eric zakariasson

49,159 görüntüleme • 9 ay önce

👀You can now connect your Google Business Profile to Gemini and make a Business Notebook. It has access to customer reviews, questions and also performance data. It can tell you trends, new market opportunities and you can ask Gemini to update your profile with new business hours, etc.

Marie Haynes

31,655 görüntüleme • 1 ay önce

Stop endless app switching. You can now ask Gemini to complete complex tasks for you across two apps - with one prompt. Look up a location on Maps AND text it to a friend. Ask a question about a video AND save it to notes. What two-in-one tasks will you be asking Gemini?

Stop endless app switching. You can now ask Gemini to complete complex tasks for you across two apps - with one prompt. Look up a location on Maps AND text it to a friend. Ask a question about a video AND save it to notes. What two-in-one tasks will you be asking Gemini?

Android

183,847 görüntüleme • 1 yıl önce