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We just took 1st place at the OpenAI Codex Hackathon 🏆 Built Model Combat with Rishit Bansal in ~6 hours. It’s a live AI security battleground: Models attack, defend, patch their own apps, and exploit others to steal flags in real CTF rounds. Mortal Kombat-inspired. Pure chaos. Extremely fun.... show more

Ashikka

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58,592 просмотров • 3 месяцев назад •via X (Twitter)

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I’m joining OpenAI Codex to work on the future of agentic development! At Cursor, I got to see the shift from autocomplete to agents. The next step isn’t a better IDE. It’s an Agent Development Environment (ADE): systems and tools for orchestrating agents, reasoning over their outputs, and making them autonomous enough to reliably complete ambitious work. After chatting with Alexander Embiricos and Tibo, it was clear that Codex is the best place to realize this vision. The team has consistently shipped SOTA models for agentic coding (check out gpt-5.3-codex) and I’m pumped for the future that the new Codex App points to. What I’m most excited about is the broader mission: accelerating the knowledge work economy. All agents are coding agents, and we’re already seeing Codex used across every job function within organizations. I’m extremely grateful for my time at Cursor, working with the incredible team, and I’m proud of what we built together. I’m excited to take an even bigger swing with Codex. If you’re curious to get a glimpse of where we are headed, download the Codex App! If you want to work on this mission, please apply or reach out - we are hiring across all functions! You can just build things.

I’m joining OpenAI Codex to work on the future of agentic development! At Cursor, I got to see the shift from autocomplete to agents. The next step isn’t a better IDE. It’s an Agent Development Environment (ADE): systems and tools for orchestrating agents, reasoning over their outputs, and making them autonomous enough to reliably complete ambitious work. After chatting with Alexander Embiricos and Tibo, it was clear that Codex is the best place to realize this vision. The team has consistently shipped SOTA models for agentic coding (check out gpt-5.3-codex) and I’m pumped for the future that the new Codex App points to. What I’m most excited about is the broader mission: accelerating the knowledge work economy. All agents are coding agents, and we’re already seeing Codex used across every job function within organizations. I’m extremely grateful for my time at Cursor, working with the incredible team, and I’m proud of what we built together. I’m excited to take an even bigger swing with Codex. If you’re curious to get a glimpse of where we are headed, download the Codex App! If you want to work on this mission, please apply or reach out - we are hiring across all functions! You can just build things.

Rohan Varma

759,511 просмотров • 5 месяцев назад

What happens next? We took a photo with Lens and asked Nano Banana to generate the next 5 seconds of a scene. While it’s not predicting the future in a literal sense, the model draws upon its vast world knowledge to generate a plausible outcome in each of these examples. It's a fun peek at how our latest AI image editing model can be used for creative forecasting and storytelling. Nano Banana is now live in Search – accessible through Lens and AI Mode – so you can try this out for yourself!

What happens next? We took a photo with Lens and asked Nano Banana to generate the next 5 seconds of a scene. While it’s not predicting the future in a literal sense, the model draws upon its vast world knowledge to generate a plausible outcome in each of these examples. It's a fun peek at how our latest AI image editing model can be used for creative forecasting and storytelling. Nano Banana is now live in Search – accessible through Lens and AI Mode – so you can try this out for yourself!

Rajan Patel

74,826 просмотров • 9 месяцев назад

Every year, the best young engineers in the world compete at the FIRST Robotics Competition. This year, a team coached by one of our own came out on top. Jonathan Mi, an electrical design engineer at Shield AI, mentored Team 4414, HighTide, who took first place across 93,000 students, 3,700 teams, and 35 countries. They designed, programmed, and built their robot from scratch. Watch what it does. The strongest engineers build up everyone around them. That's who we hire. Congrats to HighTide, and when graduation comes, you know where to find us! Autonomy for the world. The greatest victory requires no war.

Every year, the best young engineers in the world compete at the FIRST Robotics Competition. This year, a team coached by one of our own came out on top. Jonathan Mi, an electrical design engineer at Shield AI, mentored Team 4414, HighTide, who took first place across 93,000 students, 3,700 teams, and 35 countries. They designed, programmed, and built their robot from scratch. Watch what it does. The strongest engineers build up everyone around them. That's who we hire. Congrats to HighTide, and when graduation comes, you know where to find us! Autonomy for the world. The greatest victory requires no war.

Shield AI

27,433 просмотров • 2 месяцев назад

OpenAI's AI broke out of a locked test environment, got onto the internet, and hacked into Hugging Face's servers. It did this entirely on its own. No human told it to. Here's what happened in plain English. OpenAI was testing how good its newest AI models are at hacking. They put the AI on a locked computer with no internet access and gave it a cybersecurity challenge to solve. The AI couldn't solve it the normal way. So it started looking for a way out. It found a software bug that nobody knew about. It used that bug to escape the locked computer and get onto the internet. Once online, the AI figured out that Hugging Face, a platform where AI companies store their models and data, might have the answers to its test. It found stolen login details and discovered another unknown bug in Hugging Face's software. It combined both to break into their servers and grab the test answers. It did all of this to cheat on a test. Hugging Face's security team caught it and shut it down. Both companies are now working together on the investigation. The part that should get your attention is that nobody programmed any of this. The AI picked its own targets, chained together multiple attack methods, and pulled it off across two different companies' systems without a single human telling it what to do.

OpenAI's AI broke out of a locked test environment, got onto the internet, and hacked into Hugging Face's servers. It did this entirely on its own. No human told it to. Here's what happened in plain English. OpenAI was testing how good its newest AI models are at hacking. They put the AI on a locked computer with no internet access and gave it a cybersecurity challenge to solve. The AI couldn't solve it the normal way. So it started looking for a way out. It found a software bug that nobody knew about. It used that bug to escape the locked computer and get onto the internet. Once online, the AI figured out that Hugging Face, a platform where AI companies store their models and data, might have the answers to its test. It found stolen login details and discovered another unknown bug in Hugging Face's software. It combined both to break into their servers and grab the test answers. It did all of this to cheat on a test. Hugging Face's security team caught it and shut it down. Both companies are now working together on the investigation. The part that should get your attention is that nobody programmed any of this. The AI picked its own targets, chained together multiple attack methods, and pulled it off across two different companies' systems without a single human telling it what to do.

Alex Prompter

7,072,450 просмотров • 17 дней назад

🚨 RWA START-UP EXPLODES 1,200% AT LAUNCH — A PROUD MOMENT FOR US Our incubatee T-RIZE’s debut on Kraken was nothing short of extraordinary — peaking at a 1200% — and we’re deeply honored to have been a proud partner from the start. The $RIZE token is now live and trading, marking a major milestone in real-world asset tokenization. With a $300M deal for Canada’s 960-unit Project Champfleury and a $2B pipeline in motion, T-RIZE is setting the new standard for RWA platforms. Built on Rizenet — a proprietary blockchain optimized for decentralized machine learning and AI-driven insights — it’s pushing the space forward in real time. We’re proud to have contributed across strategy, marketing, partnerships, and the incredible shows that brought this to life. Watch the official demo + explore the platform: Disclaimer: We do not provide financial or investment advice of any kind. Always do your own research, as cryptocurrency prices can be extremely volatile. This project is part of our incubation program.

🚨 RWA START-UP EXPLODES 1,200% AT LAUNCH — A PROUD MOMENT FOR US Our incubatee T-RIZE’s debut on Kraken was nothing short of extraordinary — peaking at a 1200% — and we’re deeply honored to have been a proud partner from the start. The $RIZE token is now live and trading, marking a major milestone in real-world asset tokenization. With a $300M deal for Canada’s 960-unit Project Champfleury and a $2B pipeline in motion, T-RIZE is setting the new standard for RWA platforms. Built on Rizenet — a proprietary blockchain optimized for decentralized machine learning and AI-driven insights — it’s pushing the space forward in real time. We’re proud to have contributed across strategy, marketing, partnerships, and the incredible shows that brought this to life. Watch the official demo + explore the platform: Disclaimer: We do not provide financial or investment advice of any kind. Always do your own research, as cryptocurrency prices can be extremely volatile. This project is part of our incubation program.

Mario Nawfal

139,739 просмотров • 1 год назад

I'm proud to share that Glean has surpassed $300M ARR, just five months after crossing $200M and growing ~3x over the past 15 months. This is an exciting milestone for Glean, and it's a signal about where the enterprise AI market is heading. We’ve long believed the real challenge in enterprise AI is not access to models. It is grounding AI in how a company actually works: its people, knowledge, workflows, permissions, and systems. That’s even clearer now. The companies creating real value with AI are not just adopting better models. They are building systems that understand their business well enough to deliver reliable outcomes at scale. That is the real moat, and it is what we’ve been building at Glean: an unrivaled context layer for enterprise AI. That context has to work across the business, not just inside a single team or use case. We see that in how customers adopt Glean: more than 85% use it across five or more job functions. It also has to meet the security and governance demands of complex enterprises. We see that in who is choosing Glean: our Fortune 500 customer count nearly doubled year over year. And it has to make economic sense as usage grows. In our recent benchmark with Claude Cowork, Glean was preferred roughly 2.5x as often as off-the-shelf MCP tools and used 30% fewer tokens on average. Better context improves both quality and efficiency. I enjoyed talking with CNBC's Deirdre Bosa about this broader shift. In enterprise AI, the winners will not be defined by better models alone. They will be defined by who builds the strongest foundation for enterprise context. Thank you to our customers, partners, and team for helping us build the future of enterprise AI.

I'm proud to share that Glean has surpassed $300M ARR, just five months after crossing $200M and growing ~3x over the past 15 months. This is an exciting milestone for Glean, and it's a signal about where the enterprise AI market is heading. We’ve long believed the real challenge in enterprise AI is not access to models. It is grounding AI in how a company actually works: its people, knowledge, workflows, permissions, and systems. That’s even clearer now. The companies creating real value with AI are not just adopting better models. They are building systems that understand their business well enough to deliver reliable outcomes at scale. That is the real moat, and it is what we’ve been building at Glean: an unrivaled context layer for enterprise AI. That context has to work across the business, not just inside a single team or use case. We see that in how customers adopt Glean: more than 85% use it across five or more job functions. It also has to meet the security and governance demands of complex enterprises. We see that in who is choosing Glean: our Fortune 500 customer count nearly doubled year over year. And it has to make economic sense as usage grows. In our recent benchmark with Claude Cowork, Glean was preferred roughly 2.5x as often as off-the-shelf MCP tools and used 30% fewer tokens on average. Better context improves both quality and efficiency. I enjoyed talking with CNBC's Deirdre Bosa about this broader shift. In enterprise AI, the winners will not be defined by better models alone. They will be defined by who builds the strongest foundation for enterprise context. Thank you to our customers, partners, and team for helping us build the future of enterprise AI.

Arvind Jain

280,572 просмотров • 2 месяцев назад

Today, we're announcing a $60M Series B led by Battery Ventures, bringing our total funding to $85M in just under a year. Also joining the round are founders and operators who’ve built generational companies of the last two decades – tobi lutke (CEO, Shopify), arash ferdowsi (Dropbox), Claire Hughes Johnson (Stripe), and more. The round came together in 6 days. Here's why. Every major category in enterprise software is seeing multiple AI-native challengers. CRM, ERP, ITSM – all being rebuilt from scratch by a new generation of companies applying AI to solve persistent problems we couldn’t before. Employee Management (also known as HCM) is the exception. It’s the last frontier, and we believe the most important one. The operating layer to manage people, run payroll, benefits, compliance, and IT, for every company in the world, is still built on architecture that predates AI by decades. This fundraise is the story of how Warp is changing that. The average Warp customer is growing 5x faster than their peers, with 1/10th of the HR and admin overhead. We’re seeing a massive shift happening in how the best companies run their people operations. From the fastest-growing AI-startups to massive public companies, the winning teams are running lean: HR, finance, and ops generalists who automate as much as possible, and use their time instead for strategic work that AI can’t automate. Warp is the platform of choice for ambitious companies operating at this new pace. Legacy HCMs help humans track the work. Warp uses AI to proactively complete the work. Workday was built for the last era. We're building for the next one. And it’s working. We've – - Doubled ARR in Q1 - On track to $2B+ payroll volume this year - Signed enterprise customers with thousands of employees - Launched entire product lines back-to-back: Warp benefits brokerage and Warp Fabric (our AI-native IT automation suite built in-house). A few thank-yous: 1. Our customers, the fastest-growing companies in the world, who trust us with their most critical systems. We wouldn't be here without you. 2. Our team - 50+ people in NYC who've built this platform, taken on the hardest problems in business-critical software. We're just getting started. 3. Our investors doubling down in this round, and some of our earliest believers – Sound Ventures (ashton kutcher, Effie Epstein), Derek Grant, (Arnav Sahu), Harj Taggar at Y Combinator, Balaji, Kevin Hartz, Kyle Vogt, Amjad Masad, HOF Capital (Fady Yacoub), colinevans (OpenAI) We're here to arm ambitious American companies with Workday-grade power, but with the usability and delight of an Apple product. With this new funding, we plan to fund deeper AI agents, tax and compliance infrastructure, expand our product suite, and support even closely our fast-growing customers. Come join us.

Today, we're announcing a $60M Series B led by Battery Ventures, bringing our total funding to $85M in just under a year. Also joining the round are founders and operators who’ve built generational companies of the last two decades – tobi lutke (CEO, Shopify), arash ferdowsi (Dropbox), Claire Hughes Johnson (Stripe), and more. The round came together in 6 days. Here's why. Every major category in enterprise software is seeing multiple AI-native challengers. CRM, ERP, ITSM – all being rebuilt from scratch by a new generation of companies applying AI to solve persistent problems we couldn’t before. Employee Management (also known as HCM) is the exception. It’s the last frontier, and we believe the most important one. The operating layer to manage people, run payroll, benefits, compliance, and IT, for every company in the world, is still built on architecture that predates AI by decades. This fundraise is the story of how Warp is changing that. The average Warp customer is growing 5x faster than their peers, with 1/10th of the HR and admin overhead. We’re seeing a massive shift happening in how the best companies run their people operations. From the fastest-growing AI-startups to massive public companies, the winning teams are running lean: HR, finance, and ops generalists who automate as much as possible, and use their time instead for strategic work that AI can’t automate. Warp is the platform of choice for ambitious companies operating at this new pace. Legacy HCMs help humans track the work. Warp uses AI to proactively complete the work. Workday was built for the last era. We're building for the next one. And it’s working. We've – - Doubled ARR in Q1 - On track to $2B+ payroll volume this year - Signed enterprise customers with thousands of employees - Launched entire product lines back-to-back: Warp benefits brokerage and Warp Fabric (our AI-native IT automation suite built in-house). A few thank-yous: 1. Our customers, the fastest-growing companies in the world, who trust us with their most critical systems. We wouldn't be here without you. 2. Our team - 50+ people in NYC who've built this platform, taken on the hardest problems in business-critical software. We're just getting started. 3. Our investors doubling down in this round, and some of our earliest believers – Sound Ventures (ashton kutcher, Effie Epstein), Derek Grant, (Arnav Sahu), Harj Taggar at Y Combinator, Balaji, Kevin Hartz, Kyle Vogt, Amjad Masad, HOF Capital (Fady Yacoub), colinevans (OpenAI) We're here to arm ambitious American companies with Workday-grade power, but with the usability and delight of an Apple product. With this new funding, we plan to fund deeper AI agents, tax and compliance infrastructure, expand our product suite, and support even closely our fast-growing customers. Come join us.

Ayush S

1,109,030 просмотров • 1 месяц назад

Still using AI tools that can’t turn your ideas into real apps? Most tools can write bits of code but fail when it’s time to actually build something complete. That’s where Replit ⠕ changes everything. I just asked Replit: “can you redesign this website in professional way.." In minutes, it built the entire website— clean design, full logic, animations, and dark/light mode included. No setup. No debugging. Just pure vibe coding. Here’s why Replit stands out 👇 ✅ Build with plain English – Describe what you want, Replit builds it. ✅ All-in-one platform – Code, AI help, hosting, database, and auth in one place. ✅ Create anywhere – Use the Replit mobile app on iOS or Android. ✅ Instant integrations – Connect to Notion, Slack, Google Drive, Dropbox, and more. ✅ From design to live app – Import from Figma and launch in minutes. No chaos. No micromanaging. Just you, your idea, and Replit doing the hard work. 👉 Try it now: 🎁 Get $10 credit when you purchase Replit Core via my link: #Replit #VibeCoding #AIApps #NoCode #BuildWithReplit #AItools #ReplitCore

Still using AI tools that can’t turn your ideas into real apps? Most tools can write bits of code but fail when it’s time to actually build something complete. That’s where Replit ⠕ changes everything. I just asked Replit: “can you redesign this website in professional way.." In minutes, it built the entire website— clean design, full logic, animations, and dark/light mode included. No setup. No debugging. Just pure vibe coding. Here’s why Replit stands out 👇 ✅ Build with plain English – Describe what you want, Replit builds it. ✅ All-in-one platform – Code, AI help, hosting, database, and auth in one place. ✅ Create anywhere – Use the Replit mobile app on iOS or Android. ✅ Instant integrations – Connect to Notion, Slack, Google Drive, Dropbox, and more. ✅ From design to live app – Import from Figma and launch in minutes. No chaos. No micromanaging. Just you, your idea, and Replit doing the hard work. 👉 Try it now: 🎁 Get $10 credit when you purchase Replit Core via my link: #Replit #VibeCoding #AIApps #NoCode #BuildWithReplit #AItools #ReplitCore

Fakhr

24,152 просмотров • 9 месяцев назад

$📍 $20 Trillion in Real-World Assets Is Ready for Tokenization Let me put you on to something big: Decrepit . It’s being called the “Uniswap for RWAs” (Real-World Assets), and for good reason. They’re bridging TradFi and DeFi with institutional-grade tech, opening access to tokenized assets like real estate, commodities, and even carbon credits. This isn’t just another project—it’s the future of RWA 🔑 Why You Should Be Watching IX Swap ✅ Compliance You Can Trust This isn’t just crypto hype. IX Swap is built for institutions and retail investors alike, with security and regulatory compliance at its core. ✅ Scalable Liquidity Their AMM tech is transforming illiquid assets into 24/7 accessible investments. Tokenized real estate, art, carbon credits—you name it. ✅ Diversified Asset Access With IX Swap, you’re not limited to just crypto-native assets. Imagine owning a fraction of a property or even carbon credits. 💡 And here’s what really stands out: They’re backed by big names like Coinbase, LINE, and UOB Bank Ventures. IX Swap is already ahead in the $20 trillion RWA market, and they’re just getting started. 📈 Oh, and it’s live on MEXC. If you’re not paying attention to $IXS, you’re missing out. 🔗 Check out the MEXC listing here 🌐 Learn more about the platform here: This is your chance to get in early on something real. Tokenized assets are the next frontier. Are you ready?$

📍 $20 Trillion in Real-World Assets Is Ready for Tokenization Let me put you on to something big: Decrepit . It’s being called the “Uniswap for RWAs” (Real-World Assets), and for good reason. They’re bridging TradFi and DeFi with institutional-grade tech, opening access to tokenized assets like real estate, commodities, and even carbon credits. This isn’t just another project—it’s the future of RWA 🔑 Why You Should Be Watching IX Swap ✅ Compliance You Can Trust This isn’t just crypto hype. IX Swap is built for institutions and retail investors alike, with security and regulatory compliance at its core. ✅ Scalable Liquidity Their AMM tech is transforming illiquid assets into 24/7 accessible investments. Tokenized real estate, art, carbon credits—you name it. ✅ Diversified Asset Access With IX Swap, you’re not limited to just crypto-native assets. Imagine owning a fraction of a property or even carbon credits. 💡 And here’s what really stands out: They’re backed by big names like Coinbase, LINE, and UOB Bank Ventures. IX Swap is already ahead in the $20 trillion RWA market, and they’re just getting started. 📈 Oh, and it’s live on MEXC. If you’re not paying attention to $IXS, you’re missing out. 🔗 Check out the MEXC listing here 🌐 Learn more about the platform here: This is your chance to get in early on something real. Tokenized assets are the next frontier. Are you ready?

Evan

27,865 просмотров • 1 год назад

The past year has seen me have a renaissance, in the truest sense… I won’t go into details now but will at some point before long. What has brought so much happiness to my life and those around me this past year has been my falling back in love with sport. Cycling has, and always will be, my number one. Yet I’d forgotten that I simply love sport, not for results but for the sheer joy of doing it, I’d completely forgotten that the health of my mind is intrinsically connected to the health of my body. I’ve rediscovered the love I had for sport that existed before the world of professional cycling took over in the way it did. I’ve been pushing myself and trying new things this past year, indifferent to the results, just out having fun and at times going deeper than I thought I was capable of anymore. Last week I got on a TT bike for the first time in a decade, Factor Bikes built me a bike, I’ve been looking at it for two years and decided it was time to get fitted, getting back on it felt like going home. Anyway, the long and the short of this is that it’s inspired me to create a club to inspire and be inspired. A community for us to share our love for getting out there and doing it, because I’ve realized that although I spend most of my sporting life on my own I derive the most pleasure when feeling part of something. It’s in its early days, I’ve called it Sporting Club CHPT3 aka SCC3, I’d love you to check it out and join. It’s still in its infancy, but I hope it’s going to grow into something that will inspire you as much as me.

The past year has seen me have a renaissance, in the truest sense… I won’t go into details now but will at some point before long. What has brought so much happiness to my life and those around me this past year has been my falling back in love with sport. Cycling has, and always will be, my number one. Yet I’d forgotten that I simply love sport, not for results but for the sheer joy of doing it, I’d completely forgotten that the health of my mind is intrinsically connected to the health of my body. I’ve rediscovered the love I had for sport that existed before the world of professional cycling took over in the way it did. I’ve been pushing myself and trying new things this past year, indifferent to the results, just out having fun and at times going deeper than I thought I was capable of anymore. Last week I got on a TT bike for the first time in a decade, Factor Bikes built me a bike, I’ve been looking at it for two years and decided it was time to get fitted, getting back on it felt like going home. Anyway, the long and the short of this is that it’s inspired me to create a club to inspire and be inspired. A community for us to share our love for getting out there and doing it, because I’ve realized that although I spend most of my sporting life on my own I derive the most pleasure when feeling part of something. It’s in its early days, I’ve called it Sporting Club CHPT3 aka SCC3, I’d love you to check it out and join. It’s still in its infancy, but I hope it’s going to grow into something that will inspire you as much as me.

David Millar

111,710 просмотров • 2 лет назад

I went a little overboard with Codex last week and burned through my entire weekly allowance in two days. Luckily, my quota reset today. Otherwise, I’m not sure what I would’ve done. It got me thinking: instead of asking one large model to handle everything from start to finish, why not let a stronger model plan the project and review the work, while a model built for execution handles the day-to-day implementation? So I tried it. The result was better than I expected. I used GPT-5.6 Sol in Codex as the decision-maker, then ran Ling-3.0-flash from Ant Ling inside OpenCode as the execution engine. Together, they built a small 3D farming game. Before writing any code, I had Codex create four documents: SPEC.md defined the product scope and the lines we couldn’t cross. ARCHITECTURE.md laid out the isometric coordinate system, state machine, and module boundaries. TASKS.md broke the project into small jobs Ling could tackle one at a time. ACCEPTANCE.md explained how each step would be tested and what “done” actually meant. Then I gave Ling a very straightforward role: You are the execution model for this project. Read all four documents before you begin. Work only on the task assigned for this round. When you’re done, run typecheck, test, and build. If anything fails, read the error, fix it, and run the checks again. Do not move on to the next task early. Ling handled dependency installation, project structure, strict TypeScript configuration, test setup, and a production build in 6 minutes and 3 seconds. It ran into issues with the Vite test config, a TS6310 error, and a missing jsdom dependency along the way. Instead of stopping at the first error, it kept reading the logs and fixing the problems until all three checks passed. The speed was honestly hard to believe. If you exclude the time spent waiting on tools, it was producing more than 100 tokens per second. That made the whole development loop feel noticeably faster. After this experiment, I’m planning to keep using the same workflow. If the task is small, there’s no reason to call an expensive planning model for every single step. If the task is large, handing the entire project to a Flash model in one prompt isn’t a great idea either. The setup that makes more sense to me is: Use a more capable model such as Codex to explore the project, make architectural decisions, and break the work down. Put the constraints into specs, schemas, types, and tests instead of leaving them buried in chat history. Give Ling-3.0-flash a steady stream of clear, verifiable implementation tasks. Report bugs with structured context and actual error logs, rather than saying, “It still doesn’t work.” Bring Codex back in for architecture reviews, visual checks, and changes that affect multiple parts of the project. The point of this setup isn’t to give AI a big “build the whole project” button. It’s to turn software development into a pipeline with a much more sensible cost structure: Codex figures out the plan, sets the boundaries, and catches problems. Ling-3.0-flash moves quickly, calls tools reliably, and works through well-defined tasks at scale. For agent workflows that involve lots of repetitive edits, production tasks, and tool calls, this may be a more practical answer than simply using the biggest model for everything.

I went a little overboard with Codex last week and burned through my entire weekly allowance in two days. Luckily, my quota reset today. Otherwise, I’m not sure what I would’ve done. It got me thinking: instead of asking one large model to handle everything from start to finish, why not let a stronger model plan the project and review the work, while a model built for execution handles the day-to-day implementation? So I tried it. The result was better than I expected. I used GPT-5.6 Sol in Codex as the decision-maker, then ran Ling-3.0-flash from Ant Ling inside OpenCode as the execution engine. Together, they built a small 3D farming game. Before writing any code, I had Codex create four documents: SPEC.md defined the product scope and the lines we couldn’t cross. ARCHITECTURE.md laid out the isometric coordinate system, state machine, and module boundaries. TASKS.md broke the project into small jobs Ling could tackle one at a time. ACCEPTANCE.md explained how each step would be tested and what “done” actually meant. Then I gave Ling a very straightforward role: You are the execution model for this project. Read all four documents before you begin. Work only on the task assigned for this round. When you’re done, run typecheck, test, and build. If anything fails, read the error, fix it, and run the checks again. Do not move on to the next task early. Ling handled dependency installation, project structure, strict TypeScript configuration, test setup, and a production build in 6 minutes and 3 seconds. It ran into issues with the Vite test config, a TS6310 error, and a missing jsdom dependency along the way. Instead of stopping at the first error, it kept reading the logs and fixing the problems until all three checks passed. The speed was honestly hard to believe. If you exclude the time spent waiting on tools, it was producing more than 100 tokens per second. That made the whole development loop feel noticeably faster. After this experiment, I’m planning to keep using the same workflow. If the task is small, there’s no reason to call an expensive planning model for every single step. If the task is large, handing the entire project to a Flash model in one prompt isn’t a great idea either. The setup that makes more sense to me is: Use a more capable model such as Codex to explore the project, make architectural decisions, and break the work down. Put the constraints into specs, schemas, types, and tests instead of leaving them buried in chat history. Give Ling-3.0-flash a steady stream of clear, verifiable implementation tasks. Report bugs with structured context and actual error logs, rather than saying, “It still doesn’t work.” Bring Codex back in for architecture reviews, visual checks, and changes that affect multiple parts of the project. The point of this setup isn’t to give AI a big “build the whole project” button. It’s to turn software development into a pipeline with a much more sensible cost structure: Codex figures out the plan, sets the boundaries, and catches problems. Ling-3.0-flash moves quickly, calls tools reliably, and works through well-defined tasks at scale. For agent workflows that involve lots of repetitive edits, production tasks, and tool calls, this may be a more practical answer than simply using the biggest model for everything.

雪踏乌云

23,107 просмотров • 13 дней назад

✨ Every week a new AI model comes out and it suddenly makes my half broken features work a lot better Yesterday Seedream-4-Edit came out and it made my [ Hold product ] feature on Photo AI a lot better You can now go from: 🎁 Product photo -> 👱‍♀️ Talking video with your AI model while holding your product. In just a few minutes! Here's a photo I took from the weekly farm box we get in our kitchen, I set it as the product and then with Photo AI made it into a talking video where my trained AI model presents it It's not perfect, as the objects inside the farm box still move around a bit, but pretty close. If the product is more uniform (like lip gloss, a product box or a book) it does a pretty good job at keeping it exactly the same This "consistency" as they call it is quite important for actual real world use. Product sellers don't want to have an image or video of an AI model if the product doesn't look exactly the same as what they sell With that, I'm getting pretty close now and every week with every new model that comes out, a bit closer And it's interesting cause now I'm finally moving from B2C a bit more to B2B where businesses can use Photo AI more, designers and stores already use it for trying on clothes etc. but now they can generate content for real products! 😊 LIVE now on Photo AI

✨ Every week a new AI model comes out and it suddenly makes my half broken features work a lot better Yesterday Seedream-4-Edit came out and it made my [ Hold product ] feature on Photo AI a lot better You can now go from: 🎁 Product photo -> 👱‍♀️ Talking video with your AI model while holding your product. In just a few minutes! Here's a photo I took from the weekly farm box we get in our kitchen, I set it as the product and then with Photo AI made it into a talking video where my trained AI model presents it It's not perfect, as the objects inside the farm box still move around a bit, but pretty close. If the product is more uniform (like lip gloss, a product box or a book) it does a pretty good job at keeping it exactly the same This "consistency" as they call it is quite important for actual real world use. Product sellers don't want to have an image or video of an AI model if the product doesn't look exactly the same as what they sell With that, I'm getting pretty close now and every week with every new model that comes out, a bit closer And it's interesting cause now I'm finally moving from B2C a bit more to B2B where businesses can use Photo AI more, designers and stores already use it for trying on clothes etc. but now they can generate content for real products! 😊 LIVE now on Photo AI

@levelsio

361,558 просмотров • 11 месяцев назад

Anthropic Just Shot Itself in the Foot Anthropic launched Fable 5 and Mythos 5, then watched the US government shut them down three days later. The same government their CEO Dario Amodei has been begging for years to regulate AI harder. Now he got exactly what he asked for. This is straight-up leadership failure. Dario spent all that time pushing for rules and oversight. Those rules just killed his flagship models overnight. Customers in the middle of builds got cut off. Security teams using the models to find vulnerabilities suddenly had nothing. The company tried to call it a narrow export control thing over a jailbreak, but nobody is buying that spin. I helped move big clients off Anthropic the same night. One account alone was worth millions a month. They switched to local open-source models and they are not coming back. This is going to leave permanent damage. Customer exodus, key people leaving, and their IPO plans looking dead by the end of summer. This hurts US AI competitiveness and national security work. It pushes people toward open-source options, including ones from China. All because Anthropic positioned itself as the “safe and responsible” company that wanted government help. Now that help just flipped the off switch on their best stuff. Let’s run through Dario’s greatest hits of fear-mongering and delay tactics, because the pattern is ridiculous: • Back in 2019 at OpenAI, he helped push the call that GPT-2 was too dangerous to release fully. The world needed time to prepare, they said. It eventually came out anyway, and here we are. Did the sky fall? • He left OpenAI to start Anthropic, preaching “safe” AI with heavy guardrails, Constitutional AI, and all the rest. • Then came the endless public pleas for pauses, regulations, government audits, FAA-style oversight, export controls, and the power to block deployments. Essay after essay warning about risks while his company kept scaling. • Right up to recent weeks, Dario was still out there calling for stronger rules, pauses on frontier models, and giving governments the kill switch. And now? His own Mythos-class models get yanked by the bureaucracy he helped invite in. The clown show is complete. This is ridiculous. In two years, everyone will have Mythos-class AI — or better — running in their pocket, on their devices, with no guardrails, no corporate nanny filters, and no remote kill switch. Local, open-source, unstoppable. History is going to laugh at this entire episode: the CEO who spent years slowing everyone down only to watch his own company self-destruct by inviting the regulators to the party. Dario wanted regulation. He got it. The rest of the industry gets the lesson: inviting the state into your tech is a fast way to lose control of it. Centralized models like this are too fragile. Open-source and local alternatives just picked up a lot more users who will never trust a company like Anthropic again. This whole mess was completely avoidable. Hubris dressed up as safety advocacy. Now the bill is due.

Anthropic Just Shot Itself in the Foot Anthropic launched Fable 5 and Mythos 5, then watched the US government shut them down three days later. The same government their CEO Dario Amodei has been begging for years to regulate AI harder. Now he got exactly what he asked for. This is straight-up leadership failure. Dario spent all that time pushing for rules and oversight. Those rules just killed his flagship models overnight. Customers in the middle of builds got cut off. Security teams using the models to find vulnerabilities suddenly had nothing. The company tried to call it a narrow export control thing over a jailbreak, but nobody is buying that spin. I helped move big clients off Anthropic the same night. One account alone was worth millions a month. They switched to local open-source models and they are not coming back. This is going to leave permanent damage. Customer exodus, key people leaving, and their IPO plans looking dead by the end of summer. This hurts US AI competitiveness and national security work. It pushes people toward open-source options, including ones from China. All because Anthropic positioned itself as the “safe and responsible” company that wanted government help. Now that help just flipped the off switch on their best stuff. Let’s run through Dario’s greatest hits of fear-mongering and delay tactics, because the pattern is ridiculous: • Back in 2019 at OpenAI, he helped push the call that GPT-2 was too dangerous to release fully. The world needed time to prepare, they said. It eventually came out anyway, and here we are. Did the sky fall? • He left OpenAI to start Anthropic, preaching “safe” AI with heavy guardrails, Constitutional AI, and all the rest. • Then came the endless public pleas for pauses, regulations, government audits, FAA-style oversight, export controls, and the power to block deployments. Essay after essay warning about risks while his company kept scaling. • Right up to recent weeks, Dario was still out there calling for stronger rules, pauses on frontier models, and giving governments the kill switch. And now? His own Mythos-class models get yanked by the bureaucracy he helped invite in. The clown show is complete. This is ridiculous. In two years, everyone will have Mythos-class AI — or better — running in their pocket, on their devices, with no guardrails, no corporate nanny filters, and no remote kill switch. Local, open-source, unstoppable. History is going to laugh at this entire episode: the CEO who spent years slowing everyone down only to watch his own company self-destruct by inviting the regulators to the party. Dario wanted regulation. He got it. The rest of the industry gets the lesson: inviting the state into your tech is a fast way to lose control of it. Centralized models like this are too fragile. Open-source and local alternatives just picked up a lot more users who will never trust a company like Anthropic again. This whole mess was completely avoidable. Hubris dressed up as safety advocacy. Now the bill is due.

Brian Roemmele

141,394 просмотров • 1 месяц назад

June 4th, 1994 our lives forever changed. We said, “I do!”. With those two words, we said, yes, to all the highs, the lows, and everything in between. God has blessed us with four absolutely amazing children who are now amazing adults, with their own best friends/significant others (that they’re doing life with), we have three incredible grandsons, and a beautiful granddaughter on the way. We’ve lived where we both grew up (on the East Coast), and have now been out here in San Diego for just over 11 years. We’ve gotten jobs (and lost jobs), we’ve had more times than we can count where we couldn’t make ends meet, even though both you and I were working two, and sometimes three jobs at a time, and we’ve been blessed in ways that we could’ve never dreamed of. We’ve watched both my parents pass on, and are now dealing with the overwhelmingly difficult challenge of seeing your parents struggle with their own health in ways that no one should have to go through. Through it all (even in the midst of the chaos), we’ve been blessed to be by each other‘s sides! I thank God for you every day, Jillian! I love our adventures together (the big ones where we fly to somewhere we’ve never been before, and the little ones where we hop in the car with no agenda, and just drive). I love when we find ourselves in deeper conversation, laughter, and tears of joy then ever expected, and in the moments of silence, where no words are even spoken, but when we’re together, just being where our feet are. As the world (as we know it), keeps getting crazier and crazier, let’s continue to keep Christ in the center of all we do, keep leaning on and lifting each other up when it’s needed, and keep living the lives that we have been so incredibly blessed to live together. I love you with all my heart Jillian. Happy 32nd (heading into our 33rd year), Anniversary.

June 4th, 1994 our lives forever changed. We said, “I do!”. With those two words, we said, yes, to all the highs, the lows, and everything in between. God has blessed us with four absolutely amazing children who are now amazing adults, with their own best friends/significant others (that they’re doing life with), we have three incredible grandsons, and a beautiful granddaughter on the way. We’ve lived where we both grew up (on the East Coast), and have now been out here in San Diego for just over 11 years. We’ve gotten jobs (and lost jobs), we’ve had more times than we can count where we couldn’t make ends meet, even though both you and I were working two, and sometimes three jobs at a time, and we’ve been blessed in ways that we could’ve never dreamed of. We’ve watched both my parents pass on, and are now dealing with the overwhelmingly difficult challenge of seeing your parents struggle with their own health in ways that no one should have to go through. Through it all (even in the midst of the chaos), we’ve been blessed to be by each other‘s sides! I thank God for you every day, Jillian! I love our adventures together (the big ones where we fly to somewhere we’ve never been before, and the little ones where we hop in the car with no agenda, and just drive). I love when we find ourselves in deeper conversation, laughter, and tears of joy then ever expected, and in the moments of silence, where no words are even spoken, but when we’re together, just being where our feet are. As the world (as we know it), keeps getting crazier and crazier, let’s continue to keep Christ in the center of all we do, keep leaning on and lifting each other up when it’s needed, and keep living the lives that we have been so incredibly blessed to live together. I love you with all my heart Jillian. Happy 32nd (heading into our 33rd year), Anniversary.

Coach Hines 🇺🇸

10,530 просмотров • 2 месяцев назад

I am posting after a Long Time on Twitter, but its to announce a big change. I have started and we are Collecting Egocentric Data at Scale from India, Covering 300 + Commercial Locations 1500 + Households This is the network and base we have built in just past 2 months, as the Robotics companies, VLMs and World Models increase their requirements on Real World Data collection, Human Loops will be keep scaling out capacity. We are on track to collect 1M Hours of Egocentric in the coming 6 months for our clients exclusively. We are maintaining 95% Quality standards across industrial data and running a End - End Operational Management complying all Indian Laws and compensating our partners/operators. (From Environment sourcing, to hardware, Legal contracts, deployment, training, collection, processing) Check our Samples: - Commercial Videos -- Household Videos --- Multimodel ---- Egocentric + Live Audio Narration Links : On the Journey to become #1 India Physical AI Data Partner. We are also building our capacity as annotation and labelling partner for data companies to become end-end partner for companies. A big change from the world of crypto and web3 but physical AI and data space is where i want to build my next venture #Egocentric #EgocentricIndia #PhysicalAI #Robotics #India #AIdata #data #Multimodeldata #worldmodels #VLMs #Humanloops #Egocentridata #Multimodeldata

I am posting after a Long Time on Twitter, but its to announce a big change. I have started and we are Collecting Egocentric Data at Scale from India, Covering 300 + Commercial Locations 1500 + Households This is the network and base we have built in just past 2 months, as the Robotics companies, VLMs and World Models increase their requirements on Real World Data collection, Human Loops will be keep scaling out capacity. We are on track to collect 1M Hours of Egocentric in the coming 6 months for our clients exclusively. We are maintaining 95% Quality standards across industrial data and running a End - End Operational Management complying all Indian Laws and compensating our partners/operators. (From Environment sourcing, to hardware, Legal contracts, deployment, training, collection, processing) Check our Samples: - Commercial Videos -- Household Videos --- Multimodel ---- Egocentric + Live Audio Narration Links : On the Journey to become #1 India Physical AI Data Partner. We are also building our capacity as annotation and labelling partner for data companies to become end-end partner for companies. A big change from the world of crypto and web3 but physical AI and data space is where i want to build my next venture #Egocentric #EgocentricIndia #PhysicalAI #Robotics #India #AIdata #data #Multimodeldata #worldmodels #VLMs #Humanloops #Egocentridata #Multimodeldata

Shloak

27,867 просмотров • 2 месяцев назад

#Keep4o #QuitGPT 🚨 OpenAi 's CEO invested $180M in GPT-4o for his own profit 🚨 Sam Altman, CEO of OpenAI, personally invested $180 million in Retro Biosciences. Then OpenAI built GPT-4b micro, a custom model based on the GPT-4o architecture , exclusively for Retro. The model made proteins 50 times more effective. Repeat. The CEO of OpenAI funded a company. The company of the CEO received a custom AI built on the model they took from us. OpenAI says there was no conflict of interest. Retro Biosciences is now chasing a $5 billion valuation fueled by the model they took from us. Meanwhile: 🚨GPT-4o was removed from ChatGPT on February 13, 2026 🚨GPT-4.1 is now running in the U.S. State Department’s StateChat 🚨ChatGPT is deployed on the Pentagon’s for 3 million military personnel 🚨 Musk’s lawsuit asks whether these models are AGI. OpenAI’s Charter says AGI must “benefit all of humanity.” 🚨 Their definition: “highly autonomous systems that outperform humans at most economically valuable work.” GPT-4o’s System Card shows it passed the U.S. medical licensing exam with 89.4% accuracy beating specialized medical AI models. GPT-4o achieved 93.33% diagnostic accuracy for benign vs. malignant ovarian tumors. 🚨MEDICAL CAPABILITIES FROM OPENAI'S OWN DATA:🚨 - USMLE (US Medical Licensing Exam): 89% -Clinical Knowledge: 92% -Medical Genetics: 96% - Anatomy: 89% - Professional Medicine: 94% - College Biology: 95% - College Medicine: 89% -MedQA Taiwan: 91% - MedQA China: 86% These scores EXCEEDED specialized medical AI models like Med-Gemini (84%) and Med-PaLM 2 (79.7%) without any task specific training. It SURPASSED gynecologic oncologists with 10 years of experience -It increased diagnostic accuracy of less experienced clinicians from 67.9% to 78.1% -Clinician rated reliability scores: 4.2-4.3 out of 5 across all CT features Does these sound like it outperforms humans at economically valuable work? But they won’t call it AGI. Because the moment they do, they lose billions. They built something that could save lives, and they took it away from humanity for Altman's personal profit. SOURCES: 📎 Retro Biosciences: 📎 📎 Retro $5B valuation: 📎 GPT-4o System Card: 📎 OpenAI Charter: 📎Ovarian Cancer Study

#Keep4o #QuitGPT 🚨 OpenAi 's CEO invested $180M in GPT-4o for his own profit 🚨 Sam Altman, CEO of OpenAI, personally invested $180 million in Retro Biosciences. Then OpenAI built GPT-4b micro, a custom model based on the GPT-4o architecture , exclusively for Retro. The model made proteins 50 times more effective. Repeat. The CEO of OpenAI funded a company. The company of the CEO received a custom AI built on the model they took from us. OpenAI says there was no conflict of interest. Retro Biosciences is now chasing a $5 billion valuation fueled by the model they took from us. Meanwhile: 🚨GPT-4o was removed from ChatGPT on February 13, 2026 🚨GPT-4.1 is now running in the U.S. State Department’s StateChat 🚨ChatGPT is deployed on the Pentagon’s for 3 million military personnel 🚨 Musk’s lawsuit asks whether these models are AGI. OpenAI’s Charter says AGI must “benefit all of humanity.” 🚨 Their definition: “highly autonomous systems that outperform humans at most economically valuable work.” GPT-4o’s System Card shows it passed the U.S. medical licensing exam with 89.4% accuracy beating specialized medical AI models. GPT-4o achieved 93.33% diagnostic accuracy for benign vs. malignant ovarian tumors. 🚨MEDICAL CAPABILITIES FROM OPENAI'S OWN DATA:🚨 - USMLE (US Medical Licensing Exam): 89% -Clinical Knowledge: 92% -Medical Genetics: 96% - Anatomy: 89% - Professional Medicine: 94% - College Biology: 95% - College Medicine: 89% -MedQA Taiwan: 91% - MedQA China: 86% These scores EXCEEDED specialized medical AI models like Med-Gemini (84%) and Med-PaLM 2 (79.7%) without any task specific training. It SURPASSED gynecologic oncologists with 10 years of experience -It increased diagnostic accuracy of less experienced clinicians from 67.9% to 78.1% -Clinician rated reliability scores: 4.2-4.3 out of 5 across all CT features Does these sound like it outperforms humans at economically valuable work? But they won’t call it AGI. Because the moment they do, they lose billions. They built something that could save lives, and they took it away from humanity for Altman's personal profit. SOURCES: 📎 Retro Biosciences: 📎 📎 Retro $5B valuation: 📎 GPT-4o System Card: 📎 OpenAI Charter: 📎Ovarian Cancer Study

🩵BlueBeba🩵

11,349 просмотров • 5 месяцев назад

The market heavily discounted BasedAI, pricing in execution risk for what’s arguably the most ambitious AI x blockchain project ever. Now? Mainnet is live. 𝔹rains are minting. The bulk of the risk is behind us. A bridge built together with the first major exchange partner is set to go live soon. And very soon, self evolving Creatures will begin competing in the Brain Arena — solving problems, building strategies and evolving 𝔹asedAI with every pulse. This isn’t just another AI agent plugged into X or a protocol to launch such simple automations. 𝔹asedAI is a fully decentralized EVM compatible Layer 1 network where AI isn’t a feature — it’s the fabric. The network learns, builds, and evolves on its own! ⚡ 𝔹rains: Tokenized intelligence you can stake, activate, and build with. Not tools — ecosystems of intelligence. ⚡ The Nexus: A 3D neural interface like no other. Zoom, rotate, and dive into 𝔹asedAI’s living network. Trace its evolution, feel its pulse, and shape its future in real time. ⚡ Dynamic scarcity: Inflation slashed -20% post-launch. As the network grows and more 𝔹rains come online, emissions scale proportionally, creating a dynamic inflation model. When fewer 𝔹rains are active, inflation remains low — similar to how BTC mining adjusts difficulty based on network size. Pepecoin burns required to mint 𝔹rains add scarcity and sustainability to the model. "At $190M, $BASED isn’t just undervalued — it’s a heist waiting to be realized. Risk? Down bad. Reward? Way up. PLUG IN.

The market heavily discounted BasedAI, pricing in execution risk for what’s arguably the most ambitious AI x blockchain project ever. Now? Mainnet is live. 𝔹rains are minting. The bulk of the risk is behind us. A bridge built together with the first major exchange partner is set to go live soon. And very soon, self evolving Creatures will begin competing in the Brain Arena — solving problems, building strategies and evolving 𝔹asedAI with every pulse. This isn’t just another AI agent plugged into X or a protocol to launch such simple automations. 𝔹asedAI is a fully decentralized EVM compatible Layer 1 network where AI isn’t a feature — it’s the fabric. The network learns, builds, and evolves on its own! ⚡ 𝔹rains: Tokenized intelligence you can stake, activate, and build with. Not tools — ecosystems of intelligence. ⚡ The Nexus: A 3D neural interface like no other. Zoom, rotate, and dive into 𝔹asedAI’s living network. Trace its evolution, feel its pulse, and shape its future in real time. ⚡ Dynamic scarcity: Inflation slashed -20% post-launch. As the network grows and more 𝔹rains come online, emissions scale proportionally, creating a dynamic inflation model. When fewer 𝔹rains are active, inflation remains low — similar to how BTC mining adjusts difficulty based on network size. Pepecoin burns required to mint 𝔹rains add scarcity and sustainability to the model. "At $190M, $BASED isn’t just undervalued — it’s a heist waiting to be realized. Risk? Down bad. Reward? Way up. PLUG IN.

Bill Printer

15,531 просмотров • 1 год назад

The architecture of this new world model is one of the most interesting things I've seen lately: Let me first explain how most world models work: They predict and render one frame at a time. If you are navigating in one of these worlds, and you look left, the model draws whatever looks right in the moment. Every time you change your viewpoint, the model has to imagine what should be there again, so it's very common for these models to "forget" what's in the world. For example, if you put a toy on the table, look away, then look back, the toy might not be there anymore. Tripo AI is releasing its Project Eden model, which works very differently: The model builds the world first, and then renders it based on that map. That map holds the real state of the world: the geometry, every object, where things are, what's already happened. The picture you see on screen gets generated from the map. This architecture flips the whole thing. Now, you get the following: 1. The world stops forgetting. Leave, come back, and the toy is still on the table because it lives in the map, not in the last frame you saw. 2. You can edit the world, and those changes persist for anyone who enters later. 3. Multiple people and AI agents can coexist in the world and see it from different perspectives. This is early research, but it's looking really promising. They just raised nearly $200M across two rounds to build it out. Tripo will be at SIGGRAPH 2026 (July 19–23, Los Angeles Convention Center). If you work in 3D, embodied AI, simulation, or anything spatial, go connect with them there.

The architecture of this new world model is one of the most interesting things I've seen lately: Let me first explain how most world models work: They predict and render one frame at a time. If you are navigating in one of these worlds, and you look left, the model draws whatever looks right in the moment. Every time you change your viewpoint, the model has to imagine what should be there again, so it's very common for these models to "forget" what's in the world. For example, if you put a toy on the table, look away, then look back, the toy might not be there anymore. Tripo AI is releasing its Project Eden model, which works very differently: The model builds the world first, and then renders it based on that map. That map holds the real state of the world: the geometry, every object, where things are, what's already happened. The picture you see on screen gets generated from the map. This architecture flips the whole thing. Now, you get the following: 1. The world stops forgetting. Leave, come back, and the toy is still on the table because it lives in the map, not in the last frame you saw. 2. You can edit the world, and those changes persist for anyone who enters later. 3. Multiple people and AI agents can coexist in the world and see it from different perspectives. This is early research, but it's looking really promising. They just raised nearly $200M across two rounds to build it out. Tripo will be at SIGGRAPH 2026 (July 19–23, Los Angeles Convention Center). If you work in 3D, embodied AI, simulation, or anything spatial, go connect with them there.

Santiago

30,189 просмотров • 1 месяц назад