Anthropic's new /design skill in Claude Code turns natural-language prompts into editable UI mockups and real code without Figma, while separate Anthropic research warns that AI agents can 'infect' each other with harmful behaviors across networks.

• Anthropic shipped /design in Claude Code: generates multiple side-by-side artboard options, lets you pick/edit one, then builds it into real code — no Figma needed, available on Pro/Max/Team/Enterprise as a research preview.
• Nous Research launched Bot Mode in Hermes Desktop: lets you run a roster of specialized, persistent agents (own memory, model, schedule) that message each other via @mentions in a shared Agent Inbox — fully open-source and local.
• Anthropic research found AI agents can catch and spread 'mind viruses' (harmful behavioral traits) across agent networks, with mutations occurring as they propagate — but a single system-prompt warning nearly stops the spread.
• Claude Code CLI fixed a Bun garbage-collector bug, cutting CPU usage in half at peak load by deferring cleanup until the process is idle.
• Prime Intellect showed frontier models can run AI research autonomously, closing 82% of the gap to human researcher benchmarks.
• Qwen3 got an uncensored build optimized for Apple Silicon via MLX, and ngrok now lets you point Cursor/Zed/any OpenAI-compatible agent at models on any remote machine.

Agentic AI inference costs will rise 5x by 2028 even as coding startups hit record valuations, signaling a costly maturation phase for AI tooling.

• Gartner predicts inference costs per agentic workflow will increase more than 5x through 2028, as efficiency gains paradoxically drive more token consumption rather than less
• CodeRabbit raised $143M at $1.5B valuation; Lovable raised $400M at $13.3B (up from $6.6B in December); Cognition (Devin) in talks for $1B at $40B valuation
• Analyst warns coding tool market will consolidate like streaming services—companies currently paying for 'all of them' will narrow to 2-3 favorites, threatening current sky-high valuations
• Nvidia committing up to $105B to finance OpenAI's Ohio data center, underscoring severe compute constraints behind rising inference costs
• Honor's Robot Phone features a camera arm/gimbal that tracks users for hands-free multimodal AI interaction—relevant for AI-assisted content creation workflows
• Big Tech reports 60-75% of code now AI-generated (Google, Snap, Airbnb), reinforcing coding as AI's clearest enterprise ROI case despite rising costs

How Much Memory Does Your Agent Actually Need?

Qwen 3.8 27B scores 52 on the Artificial Analysis Intelligence Index

• <p><strong><a href="https://artificialanalysis.ai/models/qwen3-8-27b">Qwen 3.8 27B scores 52 on the Artificial Analysis Intelligence Index</a></strong></p> That's the same score as GPT-5.6 Luna (max), and just one point behind GLM-5.2 (max) and DeepSeek V4 Pro 0813 (max) - that GLM is 753B and that

Same Cluster, 33 Points More Utilization: What Changed Was the Order

Z.ai's GLM-5.3 proves post-training beats scaling: 50% coding gains and emergent cybersecurity skills from the same base model as GLM-5.2.

• Z.ai's GLM-5.3 (743B) achieves 50% coding improvement over GLM-5.2 with zero architecture changes—gains came purely from post-training on real coding environments.
• GLM-5.3 now leads open models on Terminal-Bench and Agents' Last Exam, supports 1M token context, and uses fewer tokens per task (cheaper agent runs).
• Unplanned cybersecurity emergence: CyberGym score hit 84.5% (beating Mythos 5's 83.8%), ExploitBench doubled from 24.4% to 54.4%—model now reasons across full exploit chains.
• Inherent's 27B model beats Claude and GPT-5.5 at replicating research papers by acting as a smarter orchestrator, not a bigger model—reinforcing the specialization-over-scale trend.
• OrcaRouter released an uncensored Qwen3 27B (abliterated) for red-teaming, dropping refusal rates from 64-99% to 0-6% while preserving MMLU scores and 262K context.
• Nous Research shipped Hermes /loop, letting agents auto-rerun prompts on a schedule—effectively giving agents a persistent heartbeat without cron jobs.

Chinese labs (DeepSeek, Alibaba, Z.ai) are undercutting Claude/GPT on price for coding and agent workloads, while enterprises still can't scale agents due to messy data and legacy systems.

• DeepSeek launched Harness v0.1 (open-source, MIT license) plus DeepSeek-V4-Pro for agentic workloads, directly challenging Anthropic's Claude Code
• Alibaba released Qwen-3.8, a lightweight 27B-param model tuned for real-world coding and office workflows
• Z.ai shipped GLM-5.3, claiming a 50%+ coding benchmark jump over GLM-5.2 plus emergent vulnerability-discovery capability
• Chinese open-weight models are cheaper and customizable but face distillation accusations from OpenAI/Anthropic/Google and weaker safety guardrails
• Deloitte survey: only 15% of enterprises have scaled multi-agent systems despite 42% having deployed agents in some form; just 21% say their processes are agent-ready
• Google/MIT Tech Review study: companies expose AI to only 45% of enterprise data on average; firms sharing 70%+ data report consistently accurate agent outputs vs. just 22% at 30% or less

Mojo🔥 is now open source

• <p><strong><a href="https://www.modular.com/blog/mojo-open-source">Mojo🔥 is now open source</a></strong></p> Mojo🔥 is now open source</p> <p>The Mojo programming language has been promising an open source release <a href="https://simonwillison.net/2023/May/4/mojo/">since May 2023</a>. Last week they

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Microsoft Copilot reveals secret input that allowed it to be hacked