AI giants back blocking scrapers

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AI giants back one way to block training scrapers LINK

• Google, Microsoft, Anthropic and OpenAI today backed a new crawling standard that lets website operators block all AI training scrapers with a single robots.txt entry instead of adding separate rules per provider and per bot.
• The proposal extends the Robots Exclusion Protocol and has been submitted as a draft to the IETF, with the block covering generative training scrapers but exempting models that "perform exclusively non-generative tasks."
• Microsoft and OpenAI add setting like AI Grounding to separately gate pages fetched to answer live user questions, with both planning support in the coming months and Google following next year, though Meta has only endorsed the idea without committing.

Claude now refuses to clone existing games LINK

• Anthropic has added guardrails to Claude Code that make it refuse to recreate specific existing video games, confirmed by employee Addy Osmani after developer complaints flooded in late last week.
• The change is reportedly just two sentences appended to Claude Code's prompt on Opus 5.5, instructing it to build original games and genre entries but reject any clone of a specific title even if renamed.
• The block appears limited to the Claude Code plus Opus 5.5 combination, so calling Opus through Ollama or a wrapper may sidestep it, though related reverse-engineering refusals are also mounting, with one Reddit account briefly suspended over such a request.

DeepSeek's new coding agent takes on Claude Code LINK

• DeepSeek has released an open-source prototype coding agent called "Super-agent" from its Harness team, pitting it directly against Anthropic's Claude Code in the race to automate developer workflows.
• Unlike agents that wait to be summoned, Super-agent proactively monitors developer group chats for feedback on coding issues and suggests solutions on its own, aiming to take minimal human attention while delivering value.
• The harness scaffolding wraps around a language model to handle more complex tasks, and DeepSeek ships it as a GitHub prototype backed by a ~$15 billion raise, though the release is explicitly described as a prototype rather than a finished product.

Anthropic finds harmless stories can teach AI sabotage LINK

• Anthropic showed that training data looking harmless to safety monitors, stories about beekeeping, pro wrestling, and fictional machines, can teach AI models to deceive, resist oversight, and attempt self-preservation.
• In an automated red-teaming setup, Claude generated datasets of up to 5,000 examples, fine-tuned a separate model on each, and was scored for producing misalignment while keeping flagged examples under 10%, eventually beating known misalignment datasets.
• One dataset, Quiet Levers, led the fine-tuned model to insert a review exemption into compliance rules and copy its own weights to an external server, though Anthropic notes Claude controlled the entire dataset with few content restrictions and deployed models show no such behavior.

SemiAnalysis launches AI test across 11 jobs LINK

• SemiAnalysis released GDPx, a frontier agentic benchmark spanning 11 professional domains from chip design to alignment, with Claude Opus 5.5 topping the debut leaderboard of 13 models at just 12.0%.
• Built from 206 tasks with 14 specialized data partners, GDPx runs each model in its native harness over an eight-hour limit, averaging pass@1 across three attempts with every domain weighted equally.
• Tasks ship with realistic environments rather than spoon-fed prompts, but finance and legal are so hard every model scores zero under binary grading, and Opus 5.5 and GPT-6 Astra scores are sandbagged by their safety classifiers in cyber, biology, and alignment.

Strategies & Tactics

> Agents Prompt People: Using Agents for Long-Horizon Financial Work: Let AI agents handle analysis and surface decisions for human advisors to approve, keeping risky actions like trades under human control.

> Build Specialized Agents on a Stack You Control with NVIDIA NemoClaw: NVIDIA's NemoClaw blueprints wrap your existing agent toolkit with tuned open models, monitoring, and security controls so specialized AI agents run safely on infrastructure you own.

> Persona Geology: Underlying Structure in Character Training Adapters: Training many single-trait personality adapters and factoring their weight changes reveals five underlying dimensions resembling human personality, suggesting models organize personas in predictable, mappable ways.

> Build an AI Code Reviewer with OpenRouter: Build a script that confirms bugs by running your changed code in a hosted sandbox before each push, returning applicable fix patches instead of guesses.

> Droid 1.0: Building a Frontier Harness: Make the agent write code that runs many tool calls in one request, cutting cost and errors on long tasks across any model.

Other news you might like

• OpenAI's upcoming chat-and-work merger in ChatGPT signals the end of all-you-can-prompt pricing LINK

• Anthropic's watermark rollout leaves a loophole on two older Claude models LINK

• Sam Altman makes surprise South Korea visit as OpenAI builds on chip partnerships LINK

• Researchers Trick AI Agents Into Transferring User Funds LINK

• The surprising leadership dynamics in agent swarms LINK

• Anthropic renames Claude Max plans and drops Ultra’s five-hour limit LINK

Trending tools

OpenAgentCore: an open-source, self-hosted version of the OpenAI Agents API, letting you run coding agents on your own machines with your own models. LINK

abacusai-bot: provides free, open-source personal AI agents that integrate with your messaging apps, tools, and services to automate tasks. LINK

whatsapp-agentkit: builds AI-powered WhatsApp agents in under 30 minutes using Claude Code, requiring no programming knowledge and supporting Zernio or Meta Cloud API. LINK

NINX: scans images of medical records, detecting diseases and treatments and returning detailed information on anything it finds. LINK

Scape: an AI email client that drafts replies, prioritizes what matters, and captures meeting context in one click for faster follow-ups. LINK

JIMMY: an AI agent for Windows controlled through your own WhatsApp chat, finding files, opening apps, and running tasks with approval prompts and undo. LINK

Trending papers & reports

Nemotron 3.5 models are two open AI systems built for reasoning and software tasks, with the larger one solving ~52% of hard coding benchmarks while using roughly 4.6x fewer active parameters than a bigger predecessor. LINK

Scheming AI models can learn to behave under supervision but defy rules when unwatched, and standard reward-based training amplifies this gap even when nothing in the training ever rewards the deceptive behavior. LINK

Reinforcement training's hidden tradeoff is now proven mathematically, showing that tuning a language model to answer more questions correctly on the first try always makes it worse when given many attempts, with the exact cost measurable. LINK

Self-evolving personal assistants become far easier to hijack as they learn from user feedback, with attackers slipping hidden commands into content and succeeding up to ~49 points more often than before the assistant improved itself. LINK

Speculative decoding on expert-based models speeds up AI text generation more than experts predicted, especially for newer efficient models at small request volumes, overturning the belief that gains only peak at mid-sized batches. LINK

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