Addendum: @SakanaAILabs
' headline is misleading. While Sakana does train its own standalone models, Sakana Fugu is not one of them. Rather, Fugu is a multi-agent orchestration system designed to coordinate already-existing AI models
AGENTS
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Sakana Fugu is a multi-agent orchestration system, not a standalone model.
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Impeccable: A Design Understanding and Real-Time Modification Add-on for AI Coding Agents
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Many people may not know what Impeccable is for. Simply put, it's a "design add-on" for AI coding agents. It's not just about having the agent write out the page, but enabling it to understand design language, project context, visual inspection, and to look and modify in the browser in real time. I've used it myself. Except for the name being hard to pronounce, everything else is pretty smooth. What it solves is not "AI
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AI and marketing: intelligent agents, deep personalization, and rapid execution
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#AI changes #marketing from a discipline built around #campaigns, #content, and #dashboards into a discipline shaped by #intelligent agents, deeper personalization, and faster execution. The greatest
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30 Agents Every AI Engineer Must Build – Production-Ready Agent Systems
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30 Agents Every AI Engineer Must Build — Build production-ready agent systems using proven architectures and patterns: http://
amzn.to/41ckg6z v/ @PacktDataML —
What you will learn:
Deploy production-ready agent systems that scale securely and reliably
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New Book: Design Multi-Agent AI Systems Using MCP and A2A
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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 agents -
Mastering NLP book: from ML foundations to LLM agents and RAG pipelines
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“Mastering NLP From Foundations to Agents” by Lior Gazit and Meysam Ghaffari, from @PacktPublishing @PacktDataML http://
amzn.to/4nJrLw4 Learn this:
•Engineer NLP systems from ML foundations to LLM architectures
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The Core of AI Agent: Context, Harness, and Loop
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这个讲得非常好，推荐大家看一下这个视频。
— 艾略特 (@elliotchen100) 23 juin 2026
很多人做 AI 还停在“怎么写 prompt”，但 Agent 真正能开始干活，是从 context、harness 到 loop 这一整套东西接起来：知道什么、能用什么、怎么判断下一步、怎么反复推进。
把这几个概念串起来看，很多 AI 产品的差距就很清楚了。 https://t.co/vrKCKQ5jvcThis is very well said. I recommend everyone to watch this video. Many people working on AI are still stuck on 'how to write prompts', but an Agent can truly start working only when the whole set of things from context, harness, to loop are connected: knowing what, being able to use what, how to judge the next step, how to iteratively advance. By linking these concepts together, the gaps between many AI products become clear.
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Grok learns from conversation, thanks entrepreneurs
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What grok learned from this conversation: https://
x.com/i/grok/share/a
1f30061cd7d4ba98d6fc22f17c6bf7b
… Thanks for inviting me to meet so many interesting entrepreneurs. -
Thanking Deepak for visionary self-assembling multi-agent LLM systems
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Thanks a lot, Deepak!!
— hardmaru (@hardmaru) 23 juin 2026
One day, we'll have self-assembling multi-agent LLM systems like your work:https://t.co/qhi40ctLaaThanks a lot, Deepak!! One day, we'll have self-assembling multi-agent LLM systems like your work:
