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a single AI agent just made 47 million developers obsolete Lovable's new agent writes better code than 90% of human programmers, works 24/7, never quits, and costs less than a Netflix subscription 10 apps people built in under an hour: 1. voice controlled app with 0 buttons

el.cine

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859,833 views • 1 year ago •via X (Twitter)

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Wow... It's better than Grok 4! Lovable just launched its new AI agent, and it's insane. It builds apps, wires backends, manages state, and connects everything seamlessly. 7 wild app and game examples: 1. A road-crossing game

Wow... It's better than Grok 4! Lovable just launched its new AI agent, and it's insane. It builds apps, wires backends, manages state, and connects everything seamlessly. 7 wild app and game examples: 1. A road-crossing game

ZOYA ✪

74,421 views • 1 year ago

Manus AI is much crazier than Deepseek moment I just got invitation code, this thing is the craziest AI agent I've seen. 10 examples: 1. Clone Apple website It created a copy of Apple website that looks almost the same, with animations and all. (preview link in comment)

Manus AI is much crazier than Deepseek moment I just got invitation code, this thing is the craziest AI agent I've seen. 10 examples: 1. Clone Apple website It created a copy of Apple website that looks almost the same, with animations and all. (preview link in comment)

el.cine

1,128,418 views • 1 year ago

Underrated stat on Caryn Marjorie’s new “AI girlfriend” voice bot: The $72k in revenue came from just 1,000 beta testers in a week. This means the average user spent more than an hour chatting with her, at $1/min. I paid to see how it works 👇

Underrated stat on Caryn Marjorie’s new “AI girlfriend” voice bot: The $72k in revenue came from just 1,000 beta testers in a week. This means the average user spent more than an hour chatting with her, at $1/min. I paid to see how it works 👇

Olivia Moore

477,644 views • 3 years ago

A 16-YEAR-OLD DEVELOPER BUILT AN AI EMPLOYEE THAT WORKS 24 HOURS A DAY FOR LESS THAN $20 He stopped treating AI like a chatbot and turned it into a complete production system powered by Claude, Cursor and automated workflows Every morning the pipeline generated new ideas, wrote scripts, organized research and prepared content before he even opened his laptop What used to take an entire afternoon now takes less than 30 minutes, cutting production costs while multiplying output every single week The biggest lesson wasn't that AI works faster It was that the people building repeatable systems are moving ahead of creators still doing everything manually The biggest advantage in 2026 won't be talent It will be automation Bookmark this

A 16-YEAR-OLD DEVELOPER BUILT AN AI EMPLOYEE THAT WORKS 24 HOURS A DAY FOR LESS THAN $20 He stopped treating AI like a chatbot and turned it into a complete production system powered by Claude, Cursor and automated workflows Every morning the pipeline generated new ideas, wrote scripts, organized research and prepared content before he even opened his laptop What used to take an entire afternoon now takes less than 30 minutes, cutting production costs while multiplying output every single week The biggest lesson wasn't that AI works faster It was that the people building repeatable systems are moving ahead of creators still doing everything manually The biggest advantage in 2026 won't be talent It will be automation Bookmark this

RetroChainer

13,378 views • 2 months ago

the opportunities in consumer apps have literally never been better😭 here's how to create a $20k/month app in only a couple of weeks: 1. spot a successful app doing more than $100k/month (quit addiction apps, screen time apps, etc) 2. gamify the app (unlockables, mascot, minigame, etc) make all of the assets with fable + the higgsfield mcp 3. make an obscene amount of content: - make content yourself - hire creators if you can - make AI UGC and AI ads with the higgs mcp 4. run EVERYTHING as a spark ad that's literally it we've been busy doing this ourselves👀

the opportunities in consumer apps have literally never been better😭 here's how to create a $20k/month app in only a couple of weeks: 1. spot a successful app doing more than $100k/month (quit addiction apps, screen time apps, etc) 2. gamify the app (unlockables, mascot, minigame, etc) make all of the assets with fable + the higgsfield mcp 3. make an obscene amount of content: - make content yourself - hire creators if you can - make AI UGC and AI ads with the higgs mcp 4. run EVERYTHING as a spark ad that's literally it we've been busy doing this ourselves👀

Mau Baron

23,829 views • 1 month ago

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 views • 6 months ago

CHINA JUST LEAKED THE FUTURE OF WEB APPS. Alibaba open-sourced PageAgent and 99% of SaaS founders are sleeping on this. It's a JavaScript AI agent that lives INSIDE your webpage. Users control your entire interface with natural language. ↳ No browser extensions needed, screenshots or multi-modal LLMs, headless browser setup, and also no backend rewrite required Just drop it in your HTML with ONE line of code. What took 20 clicks now takes one sentence. "Click login, fill in my credentials, submit the form" Done. This is not a demo, it is production-ready. ↳ Turn any SaaS into an AI copilot in minutes ↳ Smart form filling for ERP, CRM, admin systems ↳ Voice commands and accessibility built in ↳ Multi-page agent tasks via Chrome extension ↳ MCP server support for external control ↳ Bring your own LLM (Qwen, GPT, Claude, anything) Every founder building AI features just got a shortcut. Every developer manually building copilots just got replaced. The integration looks like this: That's it. Your app now has an AI agent.

CHINA JUST LEAKED THE FUTURE OF WEB APPS. Alibaba open-sourced PageAgent and 99% of SaaS founders are sleeping on this. It's a JavaScript AI agent that lives INSIDE your webpage. Users control your entire interface with natural language. ↳ No browser extensions needed, screenshots or multi-modal LLMs, headless browser setup, and also no backend rewrite required Just drop it in your HTML with ONE line of code. What took 20 clicks now takes one sentence. "Click login, fill in my credentials, submit the form" Done. This is not a demo, it is production-ready. ↳ Turn any SaaS into an AI copilot in minutes ↳ Smart form filling for ERP, CRM, admin systems ↳ Voice commands and accessibility built in ↳ Multi-page agent tasks via Chrome extension ↳ MCP server support for external control ↳ Bring your own LLM (Qwen, GPT, Claude, anything) Every founder building AI features just got a shortcut. Every developer manually building copilots just got replaced. The integration looks like this: That's it. Your app now has an AI agent.

Kanika

333,533 views • 2 months ago

R.I.P Executive Assistants. We replaced a $85K/year EA with one AI agent that never clocks out. (this agent lives inside your texts, email, and calendar 24/7) → No more forgotten follow-ups killing deals after calls → No more 3 hours daily burned on scheduling and admin → No more opening 6 apps just to stay organized → No more dropped promises that make you look unreliable Just one AI agent → autonomous executive infrastructure that never clocks out. Here's how it works: → Pre-Meeting Briefs (texts you context on who they are + what you promised) → Action Item Extraction (pulls every commitment from calls automatically) → Ghost-Written Follow-Ups (drafts in your voice — without being asked) → Schedule Management (handles conflicts, reminders, rescheduling on autopilot) → Learning Loop (gets sharper every week based on how you operate) Built with enterprise-grade context engineering. Runs 24/7 without supervision. $0 payroll. Zero dropped balls. Results after 6 weeks: • 0% missed follow-ups (down from 40% dropped) • 3 hours/day reclaimed from admin • Every promise tracked, drafted, and sent Want the complete system? Like + comment "AGENT" + repost, and I'll DM it to you. (must be following)

R.I.P Executive Assistants. We replaced a $85K/year EA with one AI agent that never clocks out. (this agent lives inside your texts, email, and calendar 24/7) → No more forgotten follow-ups killing deals after calls → No more 3 hours daily burned on scheduling and admin → No more opening 6 apps just to stay organized → No more dropped promises that make you look unreliable Just one AI agent → autonomous executive infrastructure that never clocks out. Here's how it works: → Pre-Meeting Briefs (texts you context on who they are + what you promised) → Action Item Extraction (pulls every commitment from calls automatically) → Ghost-Written Follow-Ups (drafts in your voice — without being asked) → Schedule Management (handles conflicts, reminders, rescheduling on autopilot) → Learning Loop (gets sharper every week based on how you operate) Built with enterprise-grade context engineering. Runs 24/7 without supervision. $0 payroll. Zero dropped balls. Results after 6 weeks: • 0% missed follow-ups (down from 40% dropped) • 3 hours/day reclaimed from admin • Every promise tracked, drafted, and sent Want the complete system? Like + comment "AGENT" + repost, and I'll DM it to you. (must be following)

Aryan Mahajan

34,367 views • 7 months ago

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 views • 2 months ago

MOONSHOT JUST CLONED CLAUDE CODE AND MADE IT FREE. It's called Kimi Code CLI. Open source, MIT license, maintained by the lab that shipped K3 yesterday. And it does things Claude Code doesn't: → drop a screen recording into the chat as input → built-in coder, explore, and plan subagents, each in its own context → plan mode before it touches a single file → MCP servers configured by the agent itself via /mcp-config → plugs into Zed, JetBrains, and VS Code → one binary, no Node setup, starts in milliseconds The CLI costs $0. K3 behind it starts at $3 per million tokens. Grab it for free👇

MOONSHOT JUST CLONED CLAUDE CODE AND MADE IT FREE. It's called Kimi Code CLI. Open source, MIT license, maintained by the lab that shipped K3 yesterday. And it does things Claude Code doesn't: → drop a screen recording into the chat as input → built-in coder, explore, and plan subagents, each in its own context → plan mode before it touches a single file → MCP servers configured by the agent itself via /mcp-config → plugs into Zed, JetBrains, and VS Code → one binary, no Node setup, starts in milliseconds The CLI costs $0. K3 behind it starts at $3 per million tokens. Grab it for free👇

darkzodchi

407,015 views • 2 months ago

THAT'S CRAZY, THIS CHINESE FOUNDER BUILT A MASSIVE MAC MINI FARM AND EACH ONE RUNNING ITS OWN HERMES AI AGENT LIKE A FULL-TIME EMPLOYEE He's not running one AI assistant. He's running an entire workforce. The stack: Mac Mini + Hermes, scaled out across a full physical farm. Every single Mac Mini in the rack runs its own instance of Hermes Agent – and each one has its own dedicated job. Not duplicated tasks. Actual division of labor, machine by machine, the way you'd structure a real team. No salaries. No sick days. No onboarding. Just racks of hardware, each one handling its own piece of the business, running in parallel, 24/7. This is what it looks like when "AI agent" stops being one chatbot on your laptop and starts being an actual operation. Most people are running one AI tool. This guy built a company out of them. Bookmark this post. Full setup in the video below.

THAT'S CRAZY, THIS CHINESE FOUNDER BUILT A MASSIVE MAC MINI FARM AND EACH ONE RUNNING ITS OWN HERMES AI AGENT LIKE A FULL-TIME EMPLOYEE He's not running one AI assistant. He's running an entire workforce. The stack: Mac Mini + Hermes, scaled out across a full physical farm. Every single Mac Mini in the rack runs its own instance of Hermes Agent – and each one has its own dedicated job. Not duplicated tasks. Actual division of labor, machine by machine, the way you'd structure a real team. No salaries. No sick days. No onboarding. Just racks of hardware, each one handling its own piece of the business, running in parallel, 24/7. This is what it looks like when "AI agent" stops being one chatbot on your laptop and starts being an actual operation. Most people are running one AI tool. This guy built a company out of them. Bookmark this post. Full setup in the video below.

SCOTTY BEAM

20,503 views • 2 months ago

I built an ios app that lets you setup an open claw agent from your phone in less than 30 seconds. My mom has an open claw assistant now. No api keys, no vps, no setup, no mac mini. You just log in and its spins up your own ai agent. Most people don't understand how open claw is different from chat gpt. I am building one tap skills so that anyone can outsource their work and organize their life. People spend $2500 a month on tokens. I am adding cost efficient models with one tap switching so you don't waste your money. Most of these simple setup claw projects are completely unsafe, I have passed apple review and am working with world class security professionals to keep your data safe.

I built an ios app that lets you setup an open claw agent from your phone in less than 30 seconds. My mom has an open claw assistant now. No api keys, no vps, no setup, no mac mini. You just log in and its spins up your own ai agent. Most people don't understand how open claw is different from chat gpt. I am building one tap skills so that anyone can outsource their work and organize their life. People spend $2500 a month on tokens. I am adding cost efficient models with one tap switching so you don't waste your money. Most of these simple setup claw projects are completely unsafe, I have passed apple review and am working with world class security professionals to keep your data safe.

Max Blade

26,095 views • 7 months ago

I lowkey built a $11M/month app idea with just 4 prompts Didn’t expect this many people to actually care So let’s talk about the updates I’ve made over the last hour The first version worked But it felt static "Didn't have a soul" And static apps don’t retain users So I made a few key changes: → tightened the core loop → removed friction from the first action → had Rork generate me better images So in 6 more prompts, 10 total That made the app feel 10x better. Building is solved. Iteration speed is the advantage now. Question remains, Should I ship?

I lowkey built a $11M/month app idea with just 4 prompts Didn’t expect this many people to actually care So let’s talk about the updates I’ve made over the last hour The first version worked But it felt static "Didn't have a soul" And static apps don’t retain users So I made a few key changes: → tightened the core loop → removed friction from the first action → had Rork generate me better images So in 6 more prompts, 10 total That made the app feel 10x better. Building is solved. Iteration speed is the advantage now. Question remains, Should I ship?

Jah Jiren

66,438 views • 8 months ago

We’ve been building non stop and now it’s almost here. Our first tokenized DeFi AI Agent is live soon. Pendle PTs deliver some of the highest stable yields in DeFi. 15–40% APY on stablecoins and LSTs. But keeping up with 50+ markets, maturities, and yield shifts takes constant attention. So we built Agent Pin 🧠 An autonomous DeFi AI built on PinLink’s proprietary agent framework, designed to manage Pendle PT portfolios 24/7. It: • Scans all PT markets in real time • Auto-rolls positions before maturity • Deploys idle USDC into top opportunities • Diversifies across stablecoin and LST markets Now we’re tokenizing access. Deposit USDC → Agent Pin handles everything. The first AI-managed Pendle portfolio, institutional-grade PT strategies, made effortless. This marks a major step forward for PinLink. We’re connecting DeFi with RWA and building intelligent, autonomous layers on top of it. The compounding era of DeFi yield is here. Agent Pin is how you capture it.

We’ve been building non stop and now it’s almost here. Our first tokenized DeFi AI Agent is live soon. Pendle PTs deliver some of the highest stable yields in DeFi. 15–40% APY on stablecoins and LSTs. But keeping up with 50+ markets, maturities, and yield shifts takes constant attention. So we built Agent Pin 🧠 An autonomous DeFi AI built on PinLink’s proprietary agent framework, designed to manage Pendle PT portfolios 24/7. It: • Scans all PT markets in real time • Auto-rolls positions before maturity • Deploys idle USDC into top opportunities • Diversifies across stablecoin and LST markets Now we’re tokenizing access. Deposit USDC → Agent Pin handles everything. The first AI-managed Pendle portfolio, institutional-grade PT strategies, made effortless. This marks a major step forward for PinLink. We’re connecting DeFi with RWA and building intelligent, autonomous layers on top of it. The compounding era of DeFi yield is here. Agent Pin is how you capture it.

PinLink

20,799 views • 10 months ago

my grok bot monitors the internet 24/7 and builds systems that make money on autopilot - pulls the problems out of what people wrote - only surfaces what more than one source confirmed - scores it and puts it on the dashboard - spins up a new agent when i approve - that agent builds it and sells it with whop - shows me what needs approving everyday everything from finding the customer to selling them just wrote a whole guide on how you can set this up exactly:

my grok bot monitors the internet 24/7 and builds systems that make money on autopilot - pulls the problems out of what people wrote - only surfaces what more than one source confirmed - scores it and puts it on the dashboard - spins up a new agent when i approve - that agent builds it and sells it with whop - shows me what needs approving everyday everything from finding the customer to selling them just wrote a whole guide on how you can set this up exactly:

Chris

50,983 views • 28 days ago

OpenAI's AgentKit will be so insane, build every step of agents on one platform. These visual agent builders make the whole process of iterating and launching agents far more efficient. It sits on top of the Responses API and unifies the tools that were previously scattered across SDKs and custom orchestration. It lets developers create agent workflows visually, connect data sources securely, and measure performance automatically without coding every layer by hand. The core of AgentKit is the Agent Builder, a drag-and-drop canvas where each node represents an action, guardrail, or decision branch. Developers can link these nodes into multi-agent workflows, preview results instantly, and version each setup. It supports inline evaluation so that developers can see how changes affect output before deploying. The Connector Registry is a single admin panel that manages how data and tools connect across the OpenAI ecosystem. It centralizes integrations like Google Drive, SharePoint, Dropbox, and Microsoft Teams. Large organizations can govern access and flow of data between agents securely under one global console. ChatKit provides a ready-to-use chat interface for embedding agents inside apps or websites. It manages streaming, message threads, and model reasoning displays automatically. Developers can skin the interface to match their product without writing custom front-end code. Under the hood, all these blocks use the same execution core that runs agent reasoning through OpenAI’s APIs. Workflows in Agent Builder compile down to structured instructions for the Responses API, which handles model calls, tool use, and context passing. Connector Registry handles authentication and routing for external tools, while Evals and RFT provide feedback loops that improve agents over time. This integration means developers no longer need to handle orchestration logic, model evaluation pipelines, or safety layers separately. Everything runs natively within OpenAI’s control plane with managed security, automatic versioning, and built-in testing. In short, AgentKit standardizes the entire life cycle of an AI agent—from visual design to deployment and performance tuning—inside a single unified system.

OpenAI's AgentKit will be so insane, build every step of agents on one platform. These visual agent builders make the whole process of iterating and launching agents far more efficient. It sits on top of the Responses API and unifies the tools that were previously scattered across SDKs and custom orchestration. It lets developers create agent workflows visually, connect data sources securely, and measure performance automatically without coding every layer by hand. The core of AgentKit is the Agent Builder, a drag-and-drop canvas where each node represents an action, guardrail, or decision branch. Developers can link these nodes into multi-agent workflows, preview results instantly, and version each setup. It supports inline evaluation so that developers can see how changes affect output before deploying. The Connector Registry is a single admin panel that manages how data and tools connect across the OpenAI ecosystem. It centralizes integrations like Google Drive, SharePoint, Dropbox, and Microsoft Teams. Large organizations can govern access and flow of data between agents securely under one global console. ChatKit provides a ready-to-use chat interface for embedding agents inside apps or websites. It manages streaming, message threads, and model reasoning displays automatically. Developers can skin the interface to match their product without writing custom front-end code. Under the hood, all these blocks use the same execution core that runs agent reasoning through OpenAI’s APIs. Workflows in Agent Builder compile down to structured instructions for the Responses API, which handles model calls, tool use, and context passing. Connector Registry handles authentication and routing for external tools, while Evals and RFT provide feedback loops that improve agents over time. This integration means developers no longer need to handle orchestration logic, model evaluation pipelines, or safety layers separately. Everything runs natively within OpenAI’s control plane with managed security, automatic versioning, and built-in testing. In short, AgentKit standardizes the entire life cycle of an AI agent—from visual design to deployment and performance tuning—inside a single unified system.

Rohan Paul

178,460 views • 11 months ago

18M views. 1.3M likes. Absolutely insane. Why are AI characters and storytelling converting like crazy and costing less than a dollar to make? In 2025 it was just “AI slop.” Now brands, products, and apps are pulling billions of views with them. I made a full guide that’ll teach you how to make viral AI character videos in under 5 minutes: — Prompts — Consistency — Story structure Everything y’ll ever need. Comment “AI” and I’ll send it to you immediately. (Must be following so I can DM you)

18M views. 1.3M likes. Absolutely insane. Why are AI characters and storytelling converting like crazy and costing less than a dollar to make? In 2025 it was just “AI slop.” Now brands, products, and apps are pulling billions of views with them. I made a full guide that’ll teach you how to make viral AI character videos in under 5 minutes: — Prompts — Consistency — Story structure Everything y’ll ever need. Comment “AI” and I’ll send it to you immediately. (Must be following so I can DM you)

Daniel

11,729 views • 2 months ago