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Tuesday

  1. AYi AI Notes

    Anthropic engineer shares Claude Code multi-agent orchestration playbook

    In a 30-minute workshop, an Anthropic engineer demonstrated an advanced use of Claude Code: running more than 100 agents simultaneously within one integrated loop, with 1 main agent in charge, while sub-agents act as project managers to break down tasks, distribute them, and cross-validate results. Based on this, the author suggests developers first use the main window to write task decomposition and acceptance rules, then spawn sub-agents to execute submodules concurrently. The author also warns that when a hundred agents run simultaneously, if termination conditions and permission boundaries are not hard-coded, it is easy to burn a large amount of tokens in an infinite loop, and beginners should start small with one main agent and three sub-agents.

    In a 30-minute workshop, an Anthropic engineer demonstrated an advanced use of Claude Code: running more than 100 agents simultaneously within one integrated loop, with 1 main agent in charge, while sub-agents act as project managers to break down tasks, distribute them, and cross-validate results. Based on this, the author suggests developers first use the main window to write task decomposition and acceptance rules, then spawn sub-agents to execute submodules concurrently. The author also warn

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Monday

  1. MarkTechPost

    TinyFish Makes Search Free: Breaking Down the Real Cost of AI Agents Reading Web Pages

    TinyFish announced that, within limits, it will waive retrieval fees for Search and Fetch: Search is limited to 30 requests per minute and 500 per hour, while Fetch is limited to 150 URLs per minute and 1,000 per day. The article notes that free retrieval does not eliminate the inference costs of downstream models; the same article of about 4,300 characters returns an estimated 1,184 to 42,774 tokens across different providers, and three pages of unfiltered content can fill a 128K context window. In the September 28, 2026 Artificial Analysis snapshot, TinyFish Search scored 71 at $9.30 per 1,000 tasks, the lowest total cost among the displayed configurations but also the lowest score, with about 59 seconds per task.

    TinyFish announced that, within limits, it will waive retrieval fees for Search and Fetch: Search is limited to 30 requests per minute and 500 per hour, while Fetch is limited to 150 URLs per minute and 1,000 per day. The article notes that free retrieval does not eliminate the inference costs of downstream models; the same article of about 4,300 characters returns an estimated 1,184 to 42,774 tokens across different providers, and three pages of unfiltered content can fill a 128K context window

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Sunday

  1. Tencent Cloud Developer Community

    A Guide to "Agent Engineering in Practice: Eight Lectures": Engineering Methods from Working Prototype to Production-Ready

    The Tencent Cloud Developer Community has published a guide to "Agent Engineering in Practice: Eight Lectures," centered on how to upgrade a prototype capable of calling models and tools into a system that can complete business tasks, explain failures, control costs, and iterate continuously. The series runs through two fictional teaching cases—a case-filing assistant Agent and a postoperative follow-up Agent—covering eight topics: task contracts, reasoning and collaboration, context and memory, reliable tool execution, observability and replay, evaluation and calibration, security boundaries, and production operations. The article emphasizes that a model being able to suggest the next step does not mean the system can deliver business results; the example fields, budgets, and figures are all teaching calculations and do not constitute legal advice.

    The Tencent Cloud Developer Community has published a guide to "Agent Engineering in Practice: Eight Lectures," centered on how to upgrade a prototype capable of calling models and tools into a system that can complete business tasks, explain failures, control costs, and iterate continuously. The series runs through two fictional teaching cases—a case-filing assistant Agent and a postoperative follow-up Agent—covering eight topics: task contracts, reasoning and collaboration, context and memory,

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Saturday

Friday

  1. The Verge AI

    One week with RTX Spark laptops: How do gaming, local AI, and battery life perform?

    Three authors from The Verge spent a week testing five laptops powered by Nvidia's RTX Spark N1X chip, including the 128GB Surface Laptop Ultra, Asus ProArt P16, Lenovo Yoga 9n, and HP OmniBook Ultra, priced from $3,199.99 to $6,999.99. For gaming, medium settings plus DLSS Performance mode held a steady 60fps in most games, but CPU-bound scenarios such as Helldivers 2 struggled to hit that mark; the authors place its graphics performance roughly between the RTX 5070 and RTX 5060 Laptop GPU. The local AI experience still feels like a developer testing phase: generating a news briefing with Qwen3.8-27B took 10 minutes and consumed 10% of the battery, while battery life for web-based office work came in at around 5 hours.

    Three authors from The Verge spent a week testing five laptops powered by Nvidia's RTX Spark N1X chip, including the 128GB Surface Laptop Ultra, Asus ProArt P16, Lenovo Yoga 9n, and HP OmniBook Ultra, priced from $3,199.99 to $6,999.99. For gaming, medium settings plus DLSS Performance mode held a steady 60fps in most games, but CPU-bound scenarios such as Helldivers 2 struggled to hit that mark; the authors place its graphics performance roughly between the RTX 5070 and RTX 5060 Laptop GPU. The

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Thursday

  1. Hugging FaceSelected

    Author trained six models in two days using ML Intern prompts

    Hugging Face blogger yvrjsharma released seven prompts they used with ML Intern and showcased six projects completed within two days, including a citrus disease VLM based on Qwen3.5-2B, a Huggy character LoRA for FLUX.2 klein 4B, a camera viewpoint LoRA and a doodle LoRA for Qwen-Image 2.1, Pocket Rewriter 0.8B/2B distilled models, and a version of Agate Preview 002 distilled from 50 steps to 4 steps. The author recommends stating verified facts in prompts, requiring a pre-training baseline and smoke tests with checks, and setting spending caps, for example limiting the citrus project to 12 dollars. All prompts are available on GitHub at yvrjsharma/ml-intern-prompts, and ML Intern mode can be enabled in HuggingChat.

    Hugging Face blogger yvrjsharma released seven prompts they used with ML Intern and showcased six projects completed within two days, including a citrus disease VLM based on Qwen3.5-2B, a Huggy character LoRA for FLUX.2 klein 4B, a camera viewpoint LoRA and a doodle LoRA for Qwen-Image 2.1, Pocket Rewriter 0.8B/2B distilled models, and a version of Agate Preview 002 distilled from 50 steps to 4 steps. The author recommends stating verified facts in prompts, requiring a pre-training baseline and

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