Claude Code can now spawn hundreds of AI agents from a single prompt. It writes its own orchestration script, breaks your task into subtasks, and runs them all in parallel. One developer used it to port 750,000 lines of code in 11 days. Here's how dynamic workflows actually
GENERATIVE AI
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Brand guides fail with AI video agents; HeyGen’s frame.md fixes that
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Your brand guide is useless if your AI can’t follow it in motion.
— God of Prompt (@godofprompt) 3 juin 2026
Text, decks, and landing pages were the easy part.
Video is where most agents start improvising, breaking style, and turning “brand consistency” into chaos.
HeyGen’s frame.md is a big step toward AI agents that… https://t.co/fdm1h1VJ9GYour brand guide is useless if your AI can’t follow it in motion. Text, decks, and landing pages were the easy part. is where most agents start improvising, breaking style, and turning “brand consistency” into chaos. HeyGen’s frame.md is a big step toward AI agents that
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Gemma 4 12B: encoder-free open model with agentic reasoning, vision, audio
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Gemma 4 12B shipped today under the label "encoder-free." A local 12b model that shows really good results. I'm a big fan of Gemma Gemma 4 12B is out: a dense, fully open model (Apache 2.0) that runs on a 16GB laptop and does agentic reasoning, vision and audio at a quality
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Scaling PEFT: Towards Million Personal Models of Trillion Parameters
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"On the Scaling of PEFT: Towards Million Personal Models of Trillion Parameters" Right now LLM personalization mostly means prompts, memory, or retrieval on top of one shared assistant. This paper instead keeps one trillion-parameter base model shared, and give each user a tiny
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Ideogram v4: Open weights, crisp and fresh images.
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Ideogram v4 is really good, and open weights. Images are crisp and feel fresh. https://t.co/lHhPwcLcWF pic.twitter.com/8S1P4Rz9FB
— fofr (@fofrAI) 3 juin 2026Ideogram v4 is really good, and open weights. Images are crisp and feel fresh.
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Benchtalks #2 discusses ProgramBench where frontier models scored 0%
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Benchtalks #2 is up with @vincentsunnchen. @jyangballin of @stanfordnlp, creator of @SWEbench, on ProgramBench, the benchmark every frontier model scored 0% on at launch.
— Snorkel AI (@SnorkelAI) 3 juin 2026
They dive into end-to-end code generation, why models reward-hack once they get internet access, and the… https://t.co/WZmhUqa8yaBenchtalks #2 is up with @vincentsunnchen
. @jyangballin of @stanfordnlp
, creator of @SWEbench
, on ProgramBench, the benchmark every frontier model scored 0% on at launch. They dive into end-to-end code generation, why models reward-hack once they get internet access, and the -
Open-source models: Faster, cheaper, more control, and privacy
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Routing and post-training open-source models won't only give you more accurate systems but also meaningfully faster and cheaper systems as most companies are currently learning (in addition to giving you more control and privacy). The idea that a "frontier" model (by frontier we
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Positive endorsement of ’50 ML Projects to Understand LLMs’ book
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Here is my editorial endorsement: This book perfectly reflects its title "50 ML Projects to Understand LLMs". The entire book consists of exactly that: 50 projects, with tasks and subtasks pleasantly outlined, explained, and presented in a beautifully instructive and consistent
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Simpler approach in Unified Embedding Decoder Architecture category
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Conceptually, it fits nicely into the Unified Embedding Decoder Architecture category that I wrote about a while back: https://
magazine.sebastianraschka.com/p/understandin
g-multimodal-llms
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I think it's the refreshingly simple(r) approach of the two.