if your workflow looks the same as it did 3 months ago something is very wrong
SYSTEMS
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Building Business-Ready Generative AI Systems with Agents and LLMs
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"Building Business-Ready Generative #AI Systems — Build Human-Centered Generative AI Systems with Context-Aware Agents, Memory, and LLMs for the Enterprise" at http://
amzn.to/3Jdcio5 v/ @PacktDataML Learn:
Implement an AI controller with a conversation AI agent and -
Comprehensive Guide to Supercomputing for AI Architectures and Scaling
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Supercomputing for AI – Foundations, Architectures, and Scaling Deep Learning. [804-page masterpiece] Read it online: https://
jorditorresbcn.github.io/supercomputing
-for-ai-book/
… Buy it: https://
amzn.to/4qS4pFz GitHub repo: https://
github.com/jorditorresBCN
/supercomputing-for-ai
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Sandbox Security and MCP Access Control for Safe AI Systems
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Run in a sandbox + limit data access via MCP gateways -> you're now in world of safely-skip-permissions
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LLMs as System Components: Beyond Tool Calling
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No, tool calling has been around for many years – LLMs can be part of a *system* that can run experiments. LLMs are definitely useful!
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Files as Long Term Memory Context Windows Working Memory
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Files are long term memory. Context windows are working memory. That's all you need.
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ConceptMoE: Adaptive Token-to-Concept Compression for Computing
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ConceptMoE Adaptive Token-to-Concept Compression for Implicit Compute Allocation
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Agentic AI Fundamentals: Planning, Memory, Tools, and Multi-Agent Systems
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Agentic AI, simplified: • Agents are systems
• Plan → Act → Reflect loops
• Memory = compounding intelligence
• Tools = real-world impact
• Multi-agent > single-agent If it only chats, it’s not agentic. Via @ingliguori -
LLMs as Part of Intelligent Systems
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Yes very exciting direction – an LLM can be part of a *system* that could be very helpful.
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Architecting AI Software Systems: A Guide to Scalable Integration
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"Architecting AI Software Systems: Crafting robust and scalable AI systems for modern software development" at http://
amzn.to/4oMi9Ag v/ @PacktDataML 𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼:
Learn to integrate AI with traditional software architectures, enabling architects to design