How Everyone Can Tell You Write With AI:
LLMS
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Agentmemory: infinite memory for code assistants (free)
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Ahora puedes darle memoria infinita a Claude Code, Codex y Hermes.
— Nico (@nicos_ai) 16 mai 2026
100% gratis.
Agentmemory ya es tendencia en GitHub con +4.000 estrellas.
La herramienta:
→ guarda todo lo que Claude/Codex hace durante tus sesiones de programación
→ lo comprime con IA
→ recupera… pic.twitter.com/HA83TGagjrNow you can give infinite memory to Claude Code, Codex, and Hermes. 100% free. Agentmemory is already trending on GitHub with +4,000 stars. The tool:
→ saves everything Claude/Codex does during your programming sessions
→ compresses it with AI
→ automatically retrieves the -
Causal Emergence Alignment Hypothesis in Reinforcement Learning Agents
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The Causally Emergent Alignment Hypothesis: Causal Emergence Aligns with and Predicts Final Reward in Reinforcement Learning Agents Federico Pigozzi, Michael Levin: https://
arxiv.org/abs/2605.06746 #AIAgents #ReinforcementLearning -
Anthropic training: building Claude agents from A to Z
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Anthropic a publié une Formation complet de 2 HEURES sur la construction d'agents Claude.
— Jouhatsu | AI Influence Operator (@Jouhatsu_ai) 16 mai 2026
Animé par l'ingénieur qui construit Claude Code.
Gardez-la précieusement en Signet🔖
de A à Z : Structurer un agent qui se gère sans supervision. Lui donner accès au terminal pour… pic.twitter.com/3kAKAgkz79Anthropic a publié une Formation complet de 2 HEURES sur la construction d'agents Claude. Animé par l'ingénieur qui construit Claude Code. Gardez-la précieusement en Signet de A à Z : Structurer un agent qui se gère sans supervision. Lui donner accès au terminal pour
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Token Efficiency Analysis of AI-Generated HTML Artifacts
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Anthropic is pushing HTML artifacts as the future of AI workflows. What they're not telling you: a markdown report costs ~800 tokens. The same content in styled HTML costs 2,500-4,000. That's 3-5x more tokens burned on divs and CSS instead of reasoning and depth. More tokens
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New Book on Generative AI, RAG, and AI Agents
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2nd Edition, by @keithbourne v/ @PacktDataML "Unlocking Data with Generative AI and RAG — Learn AI Agent Fundamentals with RAG-powered Memory, Graph-based RAG, and Intelligent Recall" Get the book here: http://
amzn.to/49zsIkb -
Educational guide on building AI-enhanced web applications with LLMs
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Build AI-Enhanced Web Apps: http://
amzn.to/4bgux6d
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Amazon Summary: "This book shows you step-by-step and example-by-example how to build sites and applications that take advantage of large language models (LLMs) like GPT, Claude, and Llama. Written especially for web -
Learning Model Context Protocol for Building Agentic Systems
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Learn Model Context Protocol [MCP] with Python — Build Agentic Systems in Python with the new standard for AI Capabilities: http://
amzn.to/4njfsVM by @chris_noring v/ @PacktDataML 𝓦𝓱𝓪𝓽 𝓨𝓸𝓾 𝓦𝓲𝓵𝓵 𝓛𝓮𝓪𝓻𝓷:
Understand the MCP protocol and its core components -
AI Engineering: Building Applications with Foundation Models
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AI Engineering — Building Applications with Foundation Models: http://
amzn.to/4aiSv1O by @chipro —
#ML #MachineLearning #DataScience #DataScientist
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𝓣𝓸𝓹𝓲𝓬𝓼:
Understand what AI engineering is and how it differs from traditional machine learning engineering Learn the -
AI, politics, and assumptions about powerful systems
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The talk about AI & politics seems to be oddly missing a segment (a) assumes extremely capable AI is possible soon and (b) has a strong belief about how to use this technology to make human life better according to the political project they believe in. It is a moment of action.