NOT BETTER PROMPTS. LANGGRAPH SKILL FOLDERS.most builders stuff one mega prompt and pray the agent holds itlanggraph turns your skills into nodes not one long prompteach skills folder = one edge in your agent graph ▹ why graphs beat loopsone agent looping = one brain doing ten jobs badlylanggraph splits verify route handoff into separate nodesshared state + checkpoints so it doesn't forget mid-run▹ the skills folder playfolder per skill = reusable node in the graphresearch node → evidence check
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NOT BETTER PROMPTS. LANGGRAPH SKILL FOLDERS.most builders stuff one mega prompt and pray the agent holds itlanggraph turns your skills into nodes not one long prompteach skills folder = one edge in your agent graph ▹ why graphs beat loopsone agent looping = one brain doing ten jobs badlylanggraph splits verify route handoff into separate nodesshared state + checkpoints so it doesn't forget mid-run▹ the skills folder playfolder per skill = reusable node in the graphresearch node → evidence check
327 views3 weeks ago
x.comcryptopsihoz
用最常见的猫猫咖啡的方式讲解LangGraph.
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用最常见的猫猫咖啡的方式讲解LangGraph.
155 views2 months ago
x.com青蛙在温水（记录定投纳指100）冲冲冲！
A single agent calls tools. Multiple agents solve problems no single agent can — if they coordinate well. 🤝 LangGraph provides the framework. AWS provides the infrastructure: → AWS Step Functions for orchestration→ Amazon EventBridge for event-driven triggers→ Amazon MQ for agent messaging Register for the live workshop on April 28. 📆 https://t.co/GBaTk7m6BO#AWSMarketplace #AIAgents
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A single agent calls tools. Multiple agents solve problems no single agent can — if they coordinate well. 🤝 LangGraph provides the framework. AWS provides the infrastructure: → AWS Step Functions for orchestration→ Amazon EventBridge for event-driven triggers→ Amazon MQ for agent messaging Register for the live workshop on April 28. 📆 https://t.co/GBaTk7m6BO#AWSMarketplace #AIAgents
208 views4 months ago
x.comAWS Marketplace
🚀 The AI ecosystem is evolving faster than ever—and mastering the right tools is becoming the biggest competitive advantage.Building production-ready AI applications is no longer just about selecting an LLM. It requires an ecosystem of tools for agents, RAG, embeddings, memory, security, observability, automation, and vector databases working together.💡 The Modern AI Tech Stack at a glance:🧠 LLMs – OpenAI, Claude, Gemini, Llama, Mistral & more🤖 Agentic AI – LangGraph, CrewAI, AutoGen, Agno,
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🚀 The AI ecosystem is evolving faster than ever—and mastering the right tools is becoming the biggest competitive advantage.Building production-ready AI applications is no longer just about selecting an LLM. It requires an ecosystem of tools for agents, RAG, embeddings, memory, security, observability, automation, and vector databases working together.💡 The Modern AI Tech Stack at a glance:🧠 LLMs – OpenAI, Claude, Gemini, Llama, Mistral & more🤖 Agentic AI – LangGraph, CrewAI, AutoGen, Agno,
2K views1 month ago
x.comVaidehi
Every AI system must have these 5 layers.I've explained each layer with examples.1. 𝗗𝗮𝘁𝗮This layer manages how data is stored, processed, and retrieved for AI systems.• Vector databases → Store embeddings for search• Embedding models → Convert text into vectors• Document processing → Parse and structure documents• Knowledge graphs → Connect entities and relationships• RAG systems → Retrieve external context for LLM• Semantic caching → Cache responses for faster reuse𝗘𝘅𝗮𝗺𝗽𝗹𝗲𝘀: Pinecon
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Every AI system must have these 5 layers.I've explained each layer with examples.1. 𝗗𝗮𝘁𝗮This layer manages how data is stored, processed, and retrieved for AI systems.• Vector databases → Store embeddings for search• Embedding models → Convert text into vectors• Document processing → Parse and structure documents• Knowledge graphs → Connect entities and relationships• RAG systems → Retrieve external context for LLM• Semantic caching → Cache responses for faster reuse𝗘𝘅𝗮𝗺𝗽𝗹𝗲𝘀: Pinecon
12.9K views4 months ago
x.comVaidehi
AI & Agent Development Engineer (Remote) – Tongston📍 Location: RemoteEmployment Type: ContractMonthly Professional Fee: ₦175,000Requirements:- Degree, HND/ND, or equivalent practical experience in Computer Science, AI/ML, Software Engineering, or related fields- Experience with Node.js, Express, REST APIs, and backend development- Practical experience with LLMs, AI agents, retrieval workflows, and AI integrations- Knowledge of MongoDB, LangChain, LangGraph, LlamaIndex, Flowise, Dify, or similar
AI & Agent Development Engineer (Remote) – Tongston📍 Location: RemoteEmployment Type: ContractMonthly Professional Fee: ₦175,000Requirements:- Degree, HND/ND, or equivalent practical experience in Computer Science, AI/ML, Software Engineering, or related fields- Experience with Node.js, Express, REST APIs, and backend development- Practical experience with LLMs, AI agents, retrieval workflows, and AI integrations- Knowledge of MongoDB, LangChain, LangGraph, LlamaIndex, Flowise, Dify, or similar
634 views3 weeks ago
x.comOluwatobiloba Samuel
Anthropic's in trouble, again!They spent years building what's now fully open-source.What made Claude feel different from a normal app is that the agent could act inside the interface instead of only talking in a chat box.For instance, Claude Artifacts let an agent render real UI, charts, dashboards, and interactive components that assemble live inside the response.Every major AI product tried to replicate it.But the problem was that unlike reasoning, planning, tool-calling, etc., none of it shi
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Anthropic's in trouble, again!They spent years building what's now fully open-source.What made Claude feel different from a normal app is that the agent could act inside the interface instead of only talking in a chat box.For instance, Claude Artifacts let an agent render real UI, charts, dashboards, and interactive components that assemble live inside the response.Every major AI product tried to replicate it.But the problem was that unlike reasoning, planning, tool-calling, etc., none of it shi
457.6K views2 months ago
x.comAvi Chawla
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You can now run OCR completely offline on your own machine. Zero API costs. Zero data leaving your hardware.AWS Textract charges $1.50 per 1,000 pages.Google Document AI charges the same.Adobe is a subscription.A developer named Anoop Maurya built the free version himself.It is called Ollama-OCR.One command to install:pip install ollama-ocrHere is what it actually does.You give it an image or a PDF.It runs a local vision model through Ollama.It returns structured text.Nothing leaves your machine
5.2K views1 month ago
x.comHarman
1:04
AN AI ENGINEER SPENT MONTHS BUILDING THE RAG STACK MOST PEOPLE TRY TO FAKEShe published one open source project that teaches you how to build a local RAG system from scratch, then followed it with a production-ready agentic architecture that mirrors how modern AI products are actually builtInstead of stopping at embeddings and vector search, the pipeline adds LangGraph agents, hybrid retrieval, Redis caching, observability, orchestration and local inference to create a system that can reason thr
3.2K views1 month ago
x.comInsomnia
0:06
**ZHS Agent Orchestration — How Zero Human OS Actually Works** Zero Human Systems (ZHS) @ZeroHumanSystem isn’t just another AI tool. It’s a complete **agentic operating system** that lets you run an entire company with autonomous AI agents — no employees required. ### The Core: Intelligent Orchestration At the center is the **CEO Orchestrator** (“The Brain”). It takes your high-level goals and turns them into coordinated tasks across all agents. Think of it as the conductor for a full AI workfor
89 views3 months ago
x.comZero Human Systems
1:03
Enterprise agent consulting firms charge $50,000 to fix agents that collapse the moment a real task requires more than two steps!The fix costs nothing. It is understanding one loop and building it in the right order.Most self-taught developers write their first agent as a while-loop with some dictionaries stitched together. That approach was already dead by 2026. The market learned this lesson across 2025 the hard way.→ the atomic unit: think, act, observe, reason about the task, call a tool, ob
3K views1 month ago
x.comNeilXbt
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Anthropic's most viral feature is now open-source!Until now, Anthropic's Generative UI capabilities only existed inside its own products.@CopilotKit just shipped Open Generative UI, an open-source implementation of Claude Artifacts that works in any app.The agent generates HTML/SVG at runtime, and CopilotKit streams it token-by-token into a sandboxed iframe inside the app's chat.So the user can watch the UI assemble itself in real time, not after the full response is ready.The sandbox is fully i
86.4K views3 months ago
x.comAkshay 🚀
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Vaidehi (@Ai_Vaidehi) on X
136.5K views4 months ago
x.comVaidehi
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【話題】Anthropicが何年もかけて社内で作ってきた「エージェントがインターフェースの中で動く」設計が誰でも使えるようになっています。解説します。AG-UIというオープンプロトコルでエージェントとインターフェースを分離する。バックエンドを LangGraph から CrewAI に変えてもフロントエンドに影響が出ない設計。・エージェントがテキストでなくリアルな UI コンポーネントを描画できる・エージェントとアプリの状態がリアルタイムで同期される・処理を止めて人の判断を待つ Human-in-the-loop が組み込める
401 views2 months ago
x.comSwarm｜東大AIエージェントラボ
0:57
あなたがどんな画像生成をしているか教えて？#遥かなる幻想地図 Vol.330＜作例集＞特性・詳細解説は引用元及びコメント欄（参照）へAI/人工知能/生成AI/AI生成/GenerativeAI/GenAI/ArtificialIntelligence/AGI/LLM/LMM/VLM/MLLM/SLM/マルチモーダルAI/ReasoningModel/FoundationModel/WorldModel/DiffusionModel/AIエージェント/AIAgent/AgenticAI/AutonomousAgent/MultiAgent/AIアシスタント/AICopilot/AIワークフロー/AI自動化/RAG/FineTuning/Prompt/PromptEngineering/ContextEngineering/MCP/A2A/API/SDK/OpenSource/NoCode/LowCode/ChatGPT/OpenAI/GPT/GPT4o/GPT4.1/GPT5/GPTImage/GPTImage2/DALL-E/Sora/ChatGPTAgent/Codex/DeepRe
502 views3 weeks ago
x.comSREF CLUB
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