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Forget endlessly scrollable walls of screenshots. Instead, we assembled +50 SMS ecommerce examples into … - 10 tactics - With context - And (real) results That scroll still looks pretty darn sexy, though.

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Aaron Orendorff

37,280 subscribers

13,664 Aufrufe • vor 3 Jahren •via X (Twitter)

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an important optim for any isometric RTS: split the map into sectors, and do frustum culling. I know that Unity already has great culling, but it feel wrong to only rely on Unity for it, what if we want to have huge maps? Of course, logic and rendering has to be completely decoupled, because entities in invisible sectors still need to "think". And of course, I broke the minimap because all sectors must be visible in it at all times. But it's fixable by manipulating visibility though rendering layers instead of mesh renderer state.

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Here we are again, taking another peaceful walk around the hospital grounds beneath this beautiful warm sunshine. It feels so good to finally get you outside these walls and share these moments with you, just the two of us. With every day that passes, I see a little more progress, a little more of you coming back. You take in the world with fresh eyes, the cherry blossoms in full bloom, the sweet scent of freshly cut grass, the cheerful songs of the birds, and the low rumble of cars passing by on the road. I look at you and my heart swells with admiration. You are so beautiful, so incredibly strong, and I am endlessly proud of every stride you’ve made to reach this very moment. I can’t wait to see all the strides still ahead of you. I love you, Maya. Forever and always. ❤️

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There was a moment when the Dr looked at us and said we might have missed the window for the surgery “He’s in a coma now,” “Less than 10% chance of survival.” Time stood still for us but we still took that 10% chance. And a miracle happened ♥️ Surgery is done, and both bhai and bhabhi are safe and healing ..truly, the biggest blessing 🙏🏽 To every single one of you who reached out, prayed, messaged, or called,thank you from the depths of my heart ♥️ This journey has been long, heavy, and deeply personal. To witness what love and community can do it’s humbling. It’s healing. It’s real. From here on, we move into recovery with hope and gratitude! I’ll still be in Pune for the next 20-30 days, so our meet-up will have to wait just a bit longer. But I promise when we do meet, we’ll have a lot to celebrate! Personal thanks to GANN TRADER for coming to the hospital to meet 🙌🏽 Love always, Yagnesh

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

Avi Chawla

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0:19

I see a lot of people commenting without even reading the caption or checking who I am. I’m a professional stunt rider, a movie stunt double and a content creator. I play characters, I create staged scenes because that is literally my job. Everything is planned, supervised and controlled. But even with all that, some people still rush into the comments to throw insults without understanding what they’re actually watching. Before getting angry, judging or making accusations, take a few seconds to look into what you’re seeing. It avoids a lot of unfairness and it shows respect for the people who spend time and energy creating entertaining content. And everything here is real work. It’s real riding, real effort and hours of preparation. There is never any artificial intelligence in my videos. I don’t blame anyone, but I kindly remind you to be careful with what you think you’re seeing before judging, because reality is not always what it looks like.

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AMAZON SENIOR DEVELOPER BUILT A CONTEXT PIPELINE THAT DECIDES WHAT THE MODEL EVEN GETS TO SEE Most teams still dump the entire codebase into every prompt and hope it sorts itself out. He ranked every file by relevance to the task instead of how recently it was touched. A router decides how much context each task earns, a typo fix pulls three files, a full rewrite pulls the whole module. Whatever survives gets compressed to the exact lines that actually matter, so nothing bloats the window with dead weight. Token cost per finished task dropped the moment the model stopped reading dead weight just to fix one function. See how the four stages work together below👇
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AMAZON SENIOR DEVELOPER BUILT A CONTEXT PIPELINE THAT DECIDES WHAT THE MODEL EVEN GETS TO SEE Most teams still dump the entire codebase into every prompt and hope it sorts itself out. He ranked every file by relevance to the task instead of how recently it was touched. A router decides how much context each task earns, a typo fix pulls three files, a full rewrite pulls the whole module. Whatever survives gets compressed to the exact lines that actually matter, so nothing bloats the window with dead weight. Token cost per finished task dropped the moment the model stopped reading dead weight just to fix one function. See how the four stages work together below👇

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