/goal and other fully automated AI agents are cool, but not a great model for the future of work with people. Instead you want your AI to know when to ask you GOOD questions, maybe because it is stuck, maybe because your taste matters, maybe because you would find it interesting.
AGENTS
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Solving a multi-agent management problem with Google DeepMind
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It's been almost 1 and a half years that I can't solve a multi-agent cohort management problem and now I just came across a library from @GoogleDeepMind released 2 months ago that offers an ultra elegant approach. Damn, this company is really the boss.
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Built tools for Claude code transcripts, prefers native feature
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Yeah I've built tools for working with those in the past – https://
github.com/simonw/claude-
code-transcripts
… – but I'd much prefer to have a "native" feature for that so I don't have to worry about mine breaking if they change something -
Transcription, key artifact of coding agents
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When you work with coding agents, transcription becomes one of the most significant artifacts of the work you do; I think recording these is just as important (if not more) than maintaining good commit messages and
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Disappearance of the Copy as Markdown option in Codex Desktop
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I am really upset about this: OpenAI's Codex Desktop had an option 'Copy as Markdown' to export complete chat transcripts, but this feature disappeared in an update a few days ago Really my favorite feature of
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AI Agents: Orchestrating Multiple LLMs for Enhanced Capabilities
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AI Agents ≠ single LLM They’re systems of models • General LLMs → reasoning
• Domain LLMs → expertise
• RAG → real-time data
• Tools → actions & automation
• Open-source → control & privacy Real power = orchestration of multiple LLMs Via Giuliano Liguori -
Gary Marcus questions definitions for AlphaFold and Claude consciousness
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on what possible set of definitions?? and do you think AlphaFold is a conscious being? if how would you draw a line between that and say Claude? it doesn’t hold up to careful inspection.
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AI agents process manufacturing data at scale, speed, and compliance.
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Agents process manufacturing data at scale and speed no human could match while maintaining regulatory compliance.
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From Apprenticeship to Agentic Orchestration: Digital Workers as the Primary Engine
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This represents a transition from slow apprenticeship to agentic orchestration where digital workers become the primary engine.
