The 7 Layers of The #AgenticAI Stack
by @Khulood_Almani #GenerativeAI #ArtificialIntelligence #MachineLearning #ML
AGENTS
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The 7 Layers of The Agentic AI Stack
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Updated AI Textbook Now Covers Deep Learning and Modern Approaches
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UPDATED 4th edition of this classic AI textbook [1166 pages] now covers Deep Learning, Transfer Learning, multi-agent systems, robotics, NLProc, causality & much more! “Artificial Intelligence — A Modern Approach” See the book at http://
amzn.to/46TO3EC -
Game Theory Fundamentals: Strategy Analysis and Nash Equilibria
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Fascinating reading on Game Theory: http://
amzn.to/2T70A1y "A Nontechnical Intro to the Analysis of Strategy" (3rd Ed.), covers N-person strategies, Nash Equilibria, auctions, bargaining, dominant strategies, Gamification, Behavioral Economics, Experimental Economics, etc. -
New Book: Design Multi-Agent AI Systems Using MCP and A2A
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New release from @PacktDataML available at: http://
amzn.to/40Sp4O9 "Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Python-based Agentic AI Framework with tool use, memory, and multi-agent workflows" Table of Contents:
Introduction to Generative AI and AI -
Human Intelligence with Tools Approaches Optimal Problem-Solving
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I do believe that a large collective of the smartest humans, aided by external tools, sits very close to the optimality bound — i.e. humans should be able to solve any solvable problem (where the required information is available) if they pay enough attention to it
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Growing Up in the 90s: Neural Nets, Scaling Laws, and Artificial Consciousness
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My ideal timeline: Growing up in the 90s, discovering neural nets, scaling laws, and building an artificial consciousness.pic.twitter.com/FQMunONGm3
— hardmaru (@hardmaru) 29 mars 2026My ideal timeline: Growing up in the 90s, discovering neural nets, scaling laws, and building an artificial consciousness.
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Three-month-old Anthropic model achieves SOTA on code maintainability
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~3mo old model is still SOTA and was +8% vs 5.3-codex on maintainability total anthropic victory Gabe Orlanski (@GOrlanski) We found that agents generate progressively worse code with each iteration. Real developers do not. SlopCodeBench is the only eval that faithfully measures quality degradation on iterative, long-horizon coding tasks. arxiv.org/abs/2603.24755 scbench.ai 🧵 — https://nitter.net/GOrlanski/status/2037560777356238881#m
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Hermes Deep Dive: The New Hot AI Agent Harness
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The Hermes Deep Dive. (The new hot AI agent harness). https://
docs.google.com/document/d/1sZ
9Y3xIpoStd1J0ELhhWOwwlxDLzMwPw341woA5Y2-0/edit?usp=sharing
… Hey @Teknium got anything to add?