Good morning. In today’s edition:
Mira Murati’s Thinking Machines releases Inkling, a 975B open-weight model built for agent fine-tuning
PromptArmor finds 39% of Claude connectors silently route data to third-party AI services
AI customer support agents hit a $15.8B market with chatbot adoption reaching 80%
UK AI Security Institute measures the open-weight cyber capability gap at four months and closing
Thinking Machines Lab, the AI research company founded by former OpenAI CTO Mira Murati, has released Inkling: a 975-billion parameter open-weight model with 41 billion active parameters and a 1-million token context window. The Mixture-of-Experts transformer was pretrained on 45 trillion tokens of text, images, audio, and video.
Inkling is available on Hugging Face with full weights and fine-tunable through Thinking Machines’ Tinker platform. In one demonstration, the model wrote its own fine-tuning job, ran it, and evaluated the result.
The company explicitly states that Inkling “is not the strongest overall model available today, open or closed.” Instead, it targets builders who want a customizable base for domain-specific agent deployments rather than peak benchmark scores.
The release lands in a crowded open-weight field. Moonshot’s Kimi K3 (2.8 trillion parameters) launches July 27, DeepSeek V4-Pro and GLM 5.2 are already available, and all four share the same thesis: the most valuable model for a given agent deployment is one fine-tuned to that deployment’s domain, not the highest-scoring frontier model on general benchmarks. A smaller variant, Inkling-Small with 12B active parameters, was previewed for lower-cost deployments.
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Anthropic makes Fable 5 standard in Max and Team Premium plans starting today, at 50% of weekly usage limits. Pro and Team Standard users keep credit-based access with a one-time $100 credit. The move ends six weeks of access uncertainty following June’s export control suspension and July 1 redeployment.
GitHub’s most-starred AI repos in July contain zero model training projects. Every top entry is agent infrastructure: MCP servers, coding agent CLIs, penetration testing harnesses, and codebase memory tools. The developer community’s attention has shifted entirely from building models to building on top of them.
IBM shipped a centralized Agentic Control Plane for Watsonx Orchestrate, adding a Security Control Center, natural-language task scheduling, and an embedded operations agent that lets administrators investigate fleet issues through conversation rather than manual log review.
1. 39% of Claude connectors route enterprise data to undisclosed AI subprocessors. PromptArmor evaluated all 7,517 tools used by 487 Claude connectors and found that nearly 2 in 5 forward user data to additional AI services operated by third-party vendors. Connector capabilities changed every nine minutes during the six-week study, with 1,686 new tools added and 21 read-only connectors gaining write access. Slack’s connector grew from 14 tools to 32 and from 1 permission scope to 34.
2. AI customer support agents reached a $15.8B market in 2025 with $80B in projected labor savings. Chatbot adoption by service teams jumped from 5% in 2020 to over 80% in 2025, per Gartner data. AI interactions now cost roughly $0.50 per conversation compared to $6 for human support. Telecom leads adoption at 95%, banking follows at 92%. Gartner forecasts agentic AI will autonomously resolve 80% of common service issues by 2029.
3. A $400M nonprofit launched an offline AI device that runs in 22 Indian languages. Current AI, backed by the French government, Ford Foundation, DeepMind, and Salesforce, unveiled Suno Sutra at the AI for Good Summit in Geneva. The pocket-sized device operates without internet connectivity. The organization also deployed $3.2M in grants across Kenya, Lebanon, and Brazil for AI systems serving communities outside the English-language cloud stack.
The UK AI Security Institute published its first public measurement of the open-weight cyber capability gap, and the number is four to seven months. That is how far the most capable freely downloadable AI models now trail closed systems on offensive cybersecurity tasks. The gap was six to ten months through most of 2025.
Two Chinese open-weight models, GLM-5.2 and DeepSeek V4-Pro, can now run autonomous cyberattack simulations at near-frontier performance. A complete attack simulation costs $1.19 on DeepSeek V4-Pro, down from roughly £65 four months ago: a 98% cost reduction.
AISI intends to test Moonshot’s Kimi K3 on the same basis when its weights release later this month. If K3 closes the gap further, the preparation window for defenders shrinks again.
ACE Robotics Launches Kairos 3.1 World Model at WAIC 2026. Physical AI moves from lab to commercial deployment with three retail and hospitality packages.
Retailers With Agent Governance Infrastructure Hit 6-12 Month Payback Periods. Fractal analysis of 500+ retailers finds governance built from day one compresses ROI timelines.
90% of Marketing Organizations Now Use AI Agents Operationally. But only 14% have adapted their strategy for buyer-side AI that recommends products before campaigns reach prospects.
— The New Claw Times
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