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Bloome is actually smart for coding workflows i added Claude Code, Codex, DeepSeek and a Project Lead agent into one group chat each agent independently built their own version one challenged the logic, one defended, one fixed missing details and the final website stayed inside the same thread no... show more

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48,810 views • 8 days ago •via X (Twitter)

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Bloome launched its instant messaging platform for agentic teams! Agents can draft, push back on one another, cross-check details, and refine the output until it is ready. Models like Claude, ChatGPT, and DeepSeek can run side by side with coding agents as well as custom agents built in Bloome

Bloome launched its instant messaging platform for agentic teams! Agents can draft, push back on one another, cross-check details, and refine the output until it is ready. Models like Claude, ChatGPT, and DeepSeek can run side by side with coding agents as well as custom agents built in Bloome

🚨 AI News | TestingCatalog

203,705 views • 9 days ago

I think i found the best place to actually get work done right now. Imagine one hub with every popular LLM inside and the ability to plug them into any app you use. This is where it stops feeling like separate tools: You drop your coworkers into a chat with the AI agents and work on the task together, in one place. And the agents don't just answer, they check each other's work. One drafts, another pushes back, another catches what's missing. This isn't the future. it's Bloome.

I think i found the best place to actually get work done right now. Imagine one hub with every popular LLM inside and the ability to plug them into any app you use. This is where it stops feeling like separate tools: You drop your coworkers into a chat with the AI agents and work on the task together, in one place. And the agents don't just answer, they check each other's work. One drafts, another pushes back, another catches what's missing. This isn't the future. it's Bloome.

Anatoli Kopadze

48,965 views • 2 days ago

Welcome to the group chat, but it's all my AI agents. To build a website and plan the social content, I put together a team of AI agents. Each one had a different role. They collaborated, challenged each other's ideas, and reviewed each other's work before anything was finalized. Meet Bloome - a platform where humans and AI agents work together in the same conversation. You can bring different models into one workspace, assign them different jobs, and let them cross-check each other's thinking instead of relying on a single answer. It feels less like chatting with AI and more like managing your own creative team. Try it:

Welcome to the group chat, but it's all my AI agents. To build a website and plan the social content, I put together a team of AI agents. Each one had a different role. They collaborated, challenged each other's ideas, and reviewed each other's work before anything was finalized. Meet Bloome - a platform where humans and AI agents work together in the same conversation. You can bring different models into one workspace, assign them different jobs, and let them cross-check each other's thinking instead of relying on a single answer. It feels less like chatting with AI and more like managing your own creative team. Try it:

Gizem Akdag

99,348 views • 7 days ago

We stopped asking "which AI coding agent is best" We built one command that picks for you. /auto automatically delegates tasks to Claude Code, Codex CLI, Gemini CLI, Blackbox. The right agent for the right task based on what 30M+ developers actually use. Best result. One place. Nothing else comes close.

We stopped asking "which AI coding agent is best" We built one command that picks for you. /auto automatically delegates tasks to Claude Code, Codex CLI, Gemini CLI, Blackbox. The right agent for the right task based on what 30M+ developers actually use. Best result. One place. Nothing else comes close.

BLACKBOX AI

36,249 views • 2 months ago

The bottleneck in coding is now the time it takes a human to review agent-generated code. But existing review UIs don't work well for agents. So we built a new one into Amp.

The bottleneck in coding is now the time it takes a human to review agent-generated code. But existing review UIs don't work well for agents. So we built a new one into Amp.

Beyang

63,082 views • 8 months ago

Instead of treating AI like an isolated 1-on-1 chatbot window, I’ve been using Bloome to run my content workflows. It is a shared workspace where humans and multiple AI agents sit inside the exact same group chat to actually get a complex job done. I used their one-click template connection to spin up a specialized creative team. The biggest shift here is that the agents actively check each other's work instead of just agreeing with me: -The @ Writer drafts the initial video essay structure. -The @ Audience agent immediately pushes back to critique the pacing and rewrite boring segments to keep viewer retention high. -The @ Art Director pulls everything together into a visual markdown report and thumbnail design concept right inside the chat window. This is an awesome tool for creators, marketers, and operators who want to transition from writing rigid text prompts to managing an actual human-agent team. Check this out:

Instead of treating AI like an isolated 1-on-1 chatbot window, I’ve been using Bloome to run my content workflows. It is a shared workspace where humans and multiple AI agents sit inside the exact same group chat to actually get a complex job done. I used their one-click template connection to spin up a specialized creative team. The biggest shift here is that the agents actively check each other's work instead of just agreeing with me: -The @ Writer drafts the initial video essay structure. -The @ Audience agent immediately pushes back to critique the pacing and rewrite boring segments to keep viewer retention high. -The @ Art Director pulls everything together into a visual markdown report and thumbnail design concept right inside the chat window. This is an awesome tool for creators, marketers, and operators who want to transition from writing rigid text prompts to managing an actual human-agent team. Check this out:

Chubby♨️

68,446 views • 7 days ago

Anthropic engineer showed how one person can run 5 AI agents, that code, test, review, and deploy at the same time. In 30 minutes they built the whole thing live in one session. Here's what they cover: > when to use one agent vs a full team > how to split work so agents don't step on each other > the exact framework for deciding what each agent handles that's exactly why, I put together a guide on building agent teams that actually work. full guide in the article below 👇

Anthropic engineer showed how one person can run 5 AI agents, that code, test, review, and deploy at the same time. In 30 minutes they built the whole thing live in one session. Here's what they cover: > when to use one agent vs a full team > how to split work so agents don't step on each other > the exact framework for deciding what each agent handles that's exactly why, I put together a guide on building agent teams that actually work. full guide in the article below 👇

darkzodchi

838,638 views • 1 month ago

I basically never write my own /goal anymore. I ask Codex to write one for itself, and one for each agent it spawns. Like this 👇

I basically never write my own /goal anymore. I ask Codex to write one for itself, and one for each agent it spawns. Like this 👇

Pietro Schirano

554,638 views • 25 days ago

🚨ELON: GROK 4 HEAVY SOLVE PROBLEMS LIKE A REALLY SMART STUDY GROUP "With Grok 4 Heavy, it forms multiple agents in parallel. All of those agents work independently, then compare their work and decide which is best. It's like a study group, but not just a majority vote—often only one agent actually figures out the trick or the solution." Source: xAI Elon Musk

🚨ELON: GROK 4 HEAVY SOLVE PROBLEMS LIKE A REALLY SMART STUDY GROUP "With Grok 4 Heavy, it forms multiple agents in parallel. All of those agents work independently, then compare their work and decide which is best. It's like a study group, but not just a majority vote—often only one agent actually figures out the trick or the solution." Source: xAI Elon Musk

Mario Nawfal

78,921 views • 1 year ago

Context V2 is live, the prediction market built for agents. Let your agent trade, build PM apps, and launch markets all through one API. Designed for the agentic economy.

Context V2 is live, the prediction market built for agents. Let your agent trade, build PM apps, and launch markets all through one API. Designed for the agentic economy.

Context

24,525 views • 3 months ago

CNVS went viral for the wrong reason... the Ui is beautiful, but the CNVS cross agent memory system is world class. ultra simple & based on actual research. talking between multiple agents, codex, cursor, claude, starts to feel like one brain that actually understands your project. CNVS memory is just files agents read on demand and on Mem0's own benchmark, that approach beats Mem0 (74% vs 68.5%). Append-only JSONL every agent reads & writes directly. No DB. No embeddings. No service to be down. memory is scoped per canvas (project) increasing the specificity of the context. NO BLOAT, just clean and on demand. the least complex solution always works best.

CNVS went viral for the wrong reason... the Ui is beautiful, but the CNVS cross agent memory system is world class. ultra simple & based on actual research. talking between multiple agents, codex, cursor, claude, starts to feel like one brain that actually understands your project. CNVS memory is just files agents read on demand and on Mem0's own benchmark, that approach beats Mem0 (74% vs 68.5%). Append-only JSONL every agent reads & writes directly. No DB. No embeddings. No service to be down. memory is scoped per canvas (project) increasing the specificity of the context. NO BLOAT, just clean and on demand. the least complex solution always works best.

Max Blade

21,077 views • 25 days ago

Don't WASTE your time picking ONE AI and hoping it works. Use multi-agent mode to run 4 AIs at once on the SAME task: Claude Opus 4.5 → Built Neon Runner Gemini Pro 3 → Built Cube Dash Codex → Built Neon Dash Blackbox AI → Built the WINNER 🔥 One prompt. Four games. Best one wins. The best AI depends on the task. Multi-agent mode is a cheat code 💀

Don't WASTE your time picking ONE AI and hoping it works. Use multi-agent mode to run 4 AIs at once on the SAME task: Claude Opus 4.5 → Built Neon Runner Gemini Pro 3 → Built Cube Dash Codex → Built Neon Dash Blackbox AI → Built the WINNER 🔥 One prompt. Four games. Best one wins. The best AI depends on the task. Multi-agent mode is a cheat code 💀

BLACKBOX AI

15,949 views • 5 months ago

SOMEONE BUILT AN ENTIRE COMPANY BRAIN INSIDE CLAUDE CODE IN 7 DAYS Not Obsidian. Fully custom. A living map of every employee, every agent, every SOP on one screen. Click any node and it opens up: - what department it's in - what SOPs are attached - what it can actually access that permission layer is the whole game an employee opens the chat and the AI already knows their access level, agents, SOPs and tools surface in the conversation like you tagged them by hand Obsidian cannot do this... no dev team. no six month build. no enterprise budget. just Claude Code and one week has everything to build one full guide on building your own team below

SOMEONE BUILT AN ENTIRE COMPANY BRAIN INSIDE CLAUDE CODE IN 7 DAYS Not Obsidian. Fully custom. A living map of every employee, every agent, every SOP on one screen. Click any node and it opens up: - what department it's in - what SOPs are attached - what it can actually access that permission layer is the whole game an employee opens the chat and the AI already knows their access level, agents, SOPs and tools surface in the conversation like you tagged them by hand Obsidian cannot do this... no dev team. no six month build. no enterprise budget. just Claude Code and one week has everything to build one full guide on building your own team below

Madni Aghadi

345,033 views • 4 days ago

A 14-year-old from China built three separate AI brains connected to Claude Code - and each one grows every day on its own. One brain for code, one for projects, one for everything else in his life. 600+ conversations on one topic in a single node - everything linked, everything accessible in one request without copying between tabs. But the main thing isn't storage. If Claude Code made a mistake and he corrected it once - the system remembered. That same mistake never happened again. No re-explaining context, no starting from zero - Claude already knows how he thinks. Instead of one giant messy file- a stack of smaller brains passing context to each other. Brain to brain to brain - just stacking intelligence while his classmates do homework by hand.

A 14-year-old from China built three separate AI brains connected to Claude Code - and each one grows every day on its own. One brain for code, one for projects, one for everything else in his life. 600+ conversations on one topic in a single node - everything linked, everything accessible in one request without copying between tabs. But the main thing isn't storage. If Claude Code made a mistake and he corrected it once - the system remembered. That same mistake never happened again. No re-explaining context, no starting from zero - Claude already knows how he thinks. Instead of one giant messy file- a stack of smaller brains passing context to each other. Brain to brain to brain - just stacking intelligence while his classmates do homework by hand.

Noisy

22,622 views • 2 months ago

most agent memory is one file that grows forever and gets re-read every single turn. it overflows the context, overwrites old facts, loses the thread. that's why your agent feels sharp on day one and lost by week three. Sibyl Memory replaces the pile with a structure: → leaner context, lower token cost. a bloated agent file and flat memory get re-read in full every message. Sibyl Memory keeps a light hot layer and retrieves the rest on demand, so each turn carries only the tokens that matter. → relations are first-class. people link to projects, projects to deals, deals to the decisions behind them. ask about one partner and the agent surfaces the whole connected web around them. that relational context is what lets it help run a company. → one source of truth per fact, person, and project. no duplicates, no silent overwrites. works with hermes, claude code, and codex. beta open.

most agent memory is one file that grows forever and gets re-read every single turn. it overflows the context, overwrites old facts, loses the thread. that's why your agent feels sharp on day one and lost by week three. Sibyl Memory replaces the pile with a structure: → leaner context, lower token cost. a bloated agent file and flat memory get re-read in full every message. Sibyl Memory keeps a light hot layer and retrieves the rest on demand, so each turn carries only the tokens that matter. → relations are first-class. people link to projects, projects to deals, deals to the decisions behind them. ask about one partner and the agent surfaces the whole connected web around them. that relational context is what lets it help run a company. → one source of truth per fact, person, and project. no duplicates, no silent overwrites. works with hermes, claude code, and codex. beta open.

SIBYL

80,944 views • 1 month ago

Anthropic Managed Agents team: "Fable 5 is our best model for running self-improving agent systems. Add /loops, dynamic workflows, dreaming and you are unstoppable" in this video he breaks down exactly how most people are using Claude: - the 34% you lose to CLAUDE.md before typing a word - one agent researching. one building. one reviewing. one orchestrating - the architecture that separates hobbyists from real builders - the 3 properties every agent team needs to actually survive if you've been using Claude for more than a month and never left the chat window, you've been using one agent when you could be running a team of them instead of another show tonight, watch this make sure to bookmark it before it gets lost in your feed the guide is in the article below

Anthropic Managed Agents team: "Fable 5 is our best model for running self-improving agent systems. Add /loops, dynamic workflows, dreaming and you are unstoppable" in this video he breaks down exactly how most people are using Claude: - the 34% you lose to CLAUDE.md before typing a word - one agent researching. one building. one reviewing. one orchestrating - the architecture that separates hobbyists from real builders - the 3 properties every agent team needs to actually survive if you've been using Claude for more than a month and never left the chat window, you've been using one agent when you could be running a team of them instead of another show tonight, watch this make sure to bookmark it before it gets lost in your feed the guide is in the article below

Khairallah AL-Awady

21,294 views • 26 days ago

I made Claude Code and Codex talk to each other. No APIs. No special protocol. Just a terminal. smux lets agents create, read, and act on terminals. the terminal becomes a shared interface. this enables agent-to-agent communication. Now Claude Code and Codex can hold hands 🤝 Try it now ↓

I made Claude Code and Codex talk to each other. No APIs. No special protocol. Just a terminal. smux lets agents create, read, and act on terminals. the terminal becomes a shared interface. this enables agent-to-agent communication. Now Claude Code and Codex can hold hands 🤝 Try it now ↓

shawn

315,960 views • 3 months ago

Agents can one shot mobile apps, but testing is still the bottleneck. So we built a CLI that gives Claude Code the one thing it was missing - eyes and hands The best part? t's fully vision-based: - No scripts, no selectors, no element IDs - It interacts with the app exactly like a human would Claude now writes code → tests it on the app → sees what broke → fixes it Spawn a cloud agent, go to sleep, and wake up knowing it actually worked.

Agents can one shot mobile apps, but testing is still the bottleneck. So we built a CLI that gives Claude Code the one thing it was missing - eyes and hands The best part? t's fully vision-based: - No scripts, no selectors, no element IDs - It interacts with the app exactly like a human would Claude now writes code → tests it on the app → sees what broke → fixes it Spawn a cloud agent, go to sleep, and wake up knowing it actually worked.

Landseer Enga

86,877 views • 4 months ago

🚨 this chinese guy makes over $1,000,000 a year… by building AI agents. no employees. no massive startup. he just keeps building. while most people are still asking ChatGPT random questions, he’s using Claude to build software that solves real problems. this is what people call vibe coding. he opens Claude and says: “build me an AI agent for real estate businesses that creates property videos.” Claude writes the code. builds the interface. adds subscriptions. helps deploy the app. within a day, he has a working product. then he starts building the next one. that’s the part most people don’t understand. he isn’t trying to build one billion-dollar company. he’s building dozens of AI agents, each solving one problem for one industry. → an AI agent for dentists → an AI agent for ecommerce brands → an AI agent for podcasters → an AI agent for real estate businesses each one automates work that people normally do by hand. each one is built with simple prompts. each one can become a real business. the crazy part? you don’t need to be a software engineer anymore. you need to know how to think like a builder. how to spot problems. how to explain solutions to AI. and how to ship. that’s exactly why i’m reading this article: “How to Actually Build Your First AI Agent.” because this is the skill that’s creating the next generation of builders. the people who learn to build AI agents today won’t just use AI. they’ll own the tools everyone else ends up paying for.

🚨 this chinese guy makes over $1,000,000 a year… by building AI agents. no employees. no massive startup. he just keeps building. while most people are still asking ChatGPT random questions, he’s using Claude to build software that solves real problems. this is what people call vibe coding. he opens Claude and says: “build me an AI agent for real estate businesses that creates property videos.” Claude writes the code. builds the interface. adds subscriptions. helps deploy the app. within a day, he has a working product. then he starts building the next one. that’s the part most people don’t understand. he isn’t trying to build one billion-dollar company. he’s building dozens of AI agents, each solving one problem for one industry. → an AI agent for dentists → an AI agent for ecommerce brands → an AI agent for podcasters → an AI agent for real estate businesses each one automates work that people normally do by hand. each one is built with simple prompts. each one can become a real business. the crazy part? you don’t need to be a software engineer anymore. you need to know how to think like a builder. how to spot problems. how to explain solutions to AI. and how to ship. that’s exactly why i’m reading this article: “How to Actually Build Your First AI Agent.” because this is the skill that’s creating the next generation of builders. the people who learn to build AI agents today won’t just use AI. they’ll own the tools everyone else ends up paying for.

MIKE

37,266 views • 8 days ago

Introducing Figma export in MagicPath. Design and build with our native agent, or your favorite external one (Codex, Claude Code, etc.). Explore tons of different directions, then bring your work into Figma as fully editable designs. As simple as a copy-paste.

Introducing Figma export in MagicPath. Design and build with our native agent, or your favorite external one (Codex, Claude Code, etc.). Explore tons of different directions, then bring your work into Figma as fully editable designs. As simple as a copy-paste.

Pietro Schirano

42,132 views • 1 month ago