TGINSIGHT SIMILAR POSTS
Source channel @githubtrending · Post #14693 · May 10
#jupyter_notebook#a2a#agentic_ai#dapr#dapr_pub_sub#dapr_service_invocation#dapr_sidecar#dapr_workflow#docker#kafka#kubernetes#langmem#mcp#openai#openai_agents_sdk#openai_api#postgresql_database#rabbitmq#rancher_desktop#redis#serverless_containers The Dapr Agentic Cloud Ascent (DACA) design pattern helps you build powerful, scalable AI systems that can handle millions of AI agents working together without crashing. It uses Dapr technology with Kubernetes to efficiently manage many AI agents as lightweight virtual actors, ensuring fast response, reliability, and easy scaling. You can start small using free or low-cost cloud tools and grow to planet-scale systems. The OpenAI Agents SDK is recommended for beginners because it is simple, flexible, and gives you good control to develop AI agents quickly. This approach saves costs, avoids vendor lock-in, and supports resilient, event-driven AI workflows, making it ideal for developers aiming to create advanced, cloud-native AI applications[1][2][3][4]. https://github.com/panaversity/learn-agentic-ai
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@abmedia_news · Post #23709 · 04/07/2026, 01:34 PM
【🚀AI 人工智慧｜Agent Harness 才是關鍵：為什麼同一個 AI 模型在不同產品表現天差地遠 】 #Agent#Harness#AI 📍請見報導： https://abmedia.io/agent-harness-engineering-why-same-model-different-performance 📍訂閱鏈新聞頻道：https://linktr.ee/abmedia.io
@abmedia_news · Post #23801 · 04/11/2026, 09:30 AM
【🚀AI 人工智慧｜Harness Engineering 是什麼？AI 的下一個戰場不是模型，而是模型外面的那層架構 】 #Harness#Engineering#AI 📍請見報導： https://abmedia.io/harness-engineering-ai-agent-framework-explained 📍訂閱鏈新聞頻道：https://linktr.ee/abmedia.io
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@githubtrending · Post #15523 · 02/25/2026, 12:30 PM
#typescript#agent#agentic#agentic_framework#agentic_workflow#ai#ai_agents#bytedance#deep_research#harness#langchain#langgraph#langmanus#llm#multi_agent#nodejs#podcast#python#superagent#typescript DeerFlow 2.0 is an open-source super agent harness that orchestrates multiple sub-agents, memory systems, and sandboxed execution environments to accomplish complex tasks. Built on LangGraph and LangChain, it combines research, coding, and content creation capabilities with extensible skills and tools. The platform features isolated Docker containers for safe execution, long-term memory that learns your preferences, and the ability to spawn sub-agents that work in parallel on different task angles. You benefit from dramatically reduced research and automation time—tasks that typically take hours complete in minutes—while maintaining full transparency and control over agent decisions through human-in-the-loop collaboration. Whether you need deep research reports, data analysis, slide decks, or custom workflows, DeerFlow handles multi-step complexity without requiring extensive coding knowledge. https://github.com/bytedance/deer-flow
@desi_memes_funny_jokes · Post #5101 · 07/31/2024, 08:22 AM
#TransformAnger#FuelForSuccess#Harness TheEnergy #PassionDriven#Success Mindset #RiseAboveChallenges #HappinessJourney#PracticeMakesPerfect#Mindfulness#Gratitude#KindnessMatters#JoyfulMoments#PersonalGrowth#HappinessIsAChoice#SpreadLove#LiveFully#MotivationalStudio#AashiqShekhMotivational#FitnessFuelHub#RemixedRhymes#LaughingStudio
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