L’agent IA décroche : êtes-vous (vraiment) prêt ? Un bon agent IA comprend, décide… et agit.
Mais sans contexte bien pensé, il peut vite interpréter de travers, voire embarquer vos utilisateurs dans le mur. C’est la 2e leçon du #FlashCahierdeVacances – IA Edition. À lire
AGENTS
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AI Agents: Are You Really Prepared for Implementation?
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Are You Ready for AI Agents? Context Matters
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L’agent IA décroche : êtes-vous (vraiment) prêt ? Un bon agent IA comprend, décide… et agit.
Mais sans contexte bien pensé, il peut vite interpréter de travers, voire embarquer vos utilisateurs dans le mur. C’est la 2e leçon du #FlashCahierdeVacances – IA Edition. À lire -
DeepAgent: Empower Your Small Team with Advanced Capabilities
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Use DeepAgent and super charge your small team
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DeepAgent Creates Engaging Twitter Posts for Your Account
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DeepAgent can now understand your Twitter account and create engaging posts on your behalf!
— Abacus.AI (@abacusai) 21 juillet 2025
Become a top influencer on Twitter by teaming up with DeepAgent pic.twitter.com/QavcMygGGNDeepAgent can now understand your Twitter account and create engaging posts on your behalf! Become a top influencer on Twitter by teaming up with DeepAgent
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Alpha-AGI Spores: Decentralized Intelligence Trading Platform
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Insight roots the vision → Alpha Particles bud → α-AGI Spores trade on α-MARK . A mycelium of cross-chain liquidity feeds them, pollinators flash-report truth, and FruitNFTs return the harvest to the soil. GitHub : https://
github.com/MontrealAI/AGI
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Two AI Agents Complete Task Collaboratively in Meme Format
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The meme in question. I was meant to be done in two parts by two agents – almost worked.
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Enterprise AI Agents Require Custom Development Not Off-Shelf Solutions
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This is very true. Economically valuable agents for enterprises are already here, but you can’t buy them off the shelf & they require actual cross-functional R&D.
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Learn Anything with Powerful o3 AI Prompt Tool
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Learn ANYTHING with this powerful o3 prompt. Just tell it what you want to learn, and it'll create a customized course for you, comprised of the best content around the web for each topic! It's like having a team of world-class professors all working together to teach you!
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Context Engineering Survey: Optimizing LLM Information Systems
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8. A Survey of Context Engineering for LLMs This survey defines Context Engineering as a formal discipline for optimizing information given to LLMs, outlining its core components, retrieval, processing, and management, and their integration in systems like RAG, memory, and
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Q-Chunking: Reinforcement Learning for Long-Horizon Sparse-Reward Tasks
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9. Q-Chunking Q-chunking is a reinforcement learning approach that uses action chunking to improve offline-to-online learning in long-horizon, sparse-reward tasks.