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Tag: loop

  • Tomasz Tunguz: Congratulations, Robot. You’ve Been Promoted!

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    Kurt Seifried
    in

    Source URL: https://www.tomtunguz.com/congratulations-robot-youve-been-promoted/ Source: Tomasz Tunguz Title: Congratulations, Robot. You’ve Been Promoted! Feedly Summary: Watching the OpenAI Dev Day videos, I listened as Thibault, engineering lead for Codex, announced “Codex is now a senior engineer.” AI entered the organization as an intern – uncertain & inexperienced. Over the summer, engineering leaders said treat it like…

  • Tomasz Tunguz: OpenAI Calls Codex a Senior Engineer

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    Kurt Seifried
    in

    Source URL: https://www.tomtunguz.com/openai-calls-codex-a-senior-engineer/ Source: Tomasz Tunguz Title: OpenAI Calls Codex a Senior Engineer Feedly Summary: For two years, Silicon Valley repeated the same mantra : AI agents are junior engineers. They need supervision. They handle routine tasks but struggle with complex problems. Then Thibault, OpenAI’s Codex team lead, delivered a line that broke the pattern…

  • Cloud Blog: Want to get building production-ready AI agents? Here’s where startups should start.

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    Kurt Seifried
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    Source URL: https://cloud.google.com/blog/topics/startups/startup-guide-ai-agents-production-ready-ai-how-to/ Source: Cloud Blog Title: Want to get building production-ready AI agents? Here’s where startups should start. Feedly Summary: Startups are using agentic AI to automate complex workflows, create novel user experiences, and solve business problems that were once considered technically impossible. Still, charting the optimal path forward — especially with the integration…

  • Simon Willison’s Weblog: a system that can do work independently on behalf of the user

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/Oct/6/work-independently/ Source: Simon Willison’s Weblog Title: a system that can do work independently on behalf of the user Feedly Summary: I’ve settled on agents as meaning “LLMs calling tools in a loop to achieve a goal" but OpenAI continue to muddy the waters with much more vague definitions. Swyx spotted this one in…

  • Tomasz Tunguz: Data & AI Infrastructure Are Fusing

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    Kurt Seifried
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    Source URL: https://www.tomtunguz.com/data–ai-infrastructure-are-fusing/ Source: Tomasz Tunguz Title: Data & AI Infrastructure Are Fusing Feedly Summary: AI breaks the data stack. Most enterprises spent the past decade building sophisticated data stacks. ETL pipelines move data into warehouses. Transformation layers clean data for analytics. BI tools surface insights to users. This architecture worked for traditional analytics. But…

  • Slashdot: Mira Murati’s Stealth AI Lab Launches Its First Product

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    Kurt Seifried
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    Source URL: https://slashdot.org/story/25/10/01/2226205/mira-muratis-stealth-ai-lab-launches-its-first-product?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: Mira Murati’s Stealth AI Lab Launches Its First Product Feedly Summary: AI Summary and Description: Yes Summary: The text discusses the launch of Tinker, an automated tool by Thinking Machines Lab that simplifies the fine-tuning of frontier AI models for various users including researchers, businesses, and enthusiasts. This innovation…

  • Hamel’s Blog: Selecting The Right AI Evals Tool

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    Kurt Seifried
    in

    Source URL: https://hamel.dev/blog/posts/eval-tools/ Source: Hamel’s Blog Title: Selecting The Right AI Evals Tool Feedly Summary: Over the past year, I’ve focused heavily on AI Evals, both in my consulting work and teaching. A question I get constantly is, “What’s the best tool for evals?”. I’ve always resisted answering directly for two reasons. First, people focus…

  • Tomasz Tunguz: The Future of AI Data Architecture: How Enterprises Are Building the Next Generation Stack

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    Kurt Seifried
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    Source URL: https://www.tomtunguz.com/future-ai-data-architecture-enterprise-stack/ Source: Tomasz Tunguz Title: The Future of AI Data Architecture: How Enterprises Are Building the Next Generation Stack Feedly Summary: The AI stack is still developing. Different companies experiment with various approaches, tools, and architectures as they figure out what works at scale. The complication is that patterns are beginning to coalesce…