In partnership with
The IT strategy every team needs for 2026
2026 will redefine IT as a strategic driver of global growth. Automation, AI-driven support, unified platforms, and zero-trust security are becoming standard, especially for distributed teams. This toolkit helps IT and HR leaders assess readiness, define goals, and build a scalable, audit-ready IT strategy for the year ahead. Learn what’s changing and how to prepare.
Anthropic just dropped Claude Opus 4.7 — and the headline feature isn’t another benchmark win. The model can now see images at 3x the resolution of its predecessor, introduces a new “extra high” reasoning mode, and ships with automatic cyber safeguards that detect and block high-risk requests.
What makes this release interesting is what Anthropic chose to be transparent about: Opus 4.7 still trails their unreleased Mythos Preview model, and a new tokenizer means bills may shift even though per-token pricing stays flat. It’s a rare case of a company launching its best available product while openly admitting something better exists behind a locked door.
Today in AI Brief:
Claude Opus 4.7 launches with tripled vision and deeper coding
Gemini arrives on Mac with Option+Space access and screen sharing
Anthropic’s AI agents outperform its own alignment researchers
Claude Opus 4.7 Launches With Tripled Vision and Deeper Coding
What’s new?
Anthropic released Claude Opus 4.7, its most powerful publicly available model — delivering state-of-the-art performance on financial reasoning, software engineering, and document analysis while tripling the resolution of its vision capabilities to 3.75 megapixels.
What matters?
The model introduces a new “extra high” effort level between high and max, giving users finer control over the tradeoff between reasoning depth and latency on complex problems.
A new tokenizer maps inputs to 1.0–1.35x more tokens depending on content — pricing stays the same per token, but bills may increase due to higher token consumption.
Claude Code gains an /ultrareview command for automated deep code reviews that flag issues at a level resembling senior engineer assessments.
Why it matters?
Opus 4.7 is Anthropic’s answer to a market where GPT-5.4 and Gemini 3.1 Pro keep raising the bar — and the company is refreshingly transparent that its restricted Mythos Preview still outperforms it. For developers, the practical question is whether the improved instruction-following and vision justify the tokenizer-driven cost increase.
Gemini Arrives on Mac With Option+Space Access and Screen Sharing
What’s new?
Google launched a native Gemini app for Mac, activated with Option+Space, that can view and analyze anything on your screen — including full web pages beyond what’s currently displayed.
What matters?
The app offers two modes: Option+Space opens a mini chat overlay, while Option+Shift+Space opens the full Gemini experience with Nano Banana image generation and Veo video creation built in.
Screen sharing works across any window on the Mac — Gemini can read documents, code, emails, or designs and provide contextual assistance based on exactly what you’re looking at.
The app is available globally on macOS 15+ to all Gemini users, syncing conversations across devices.
Why it matters?
Google is positioning Gemini as an ambient AI layer that lives on your desktop, not just in a browser tab. If the screen-sharing feature works as seamlessly as described, it’s the closest any major AI has come to being a true real-time work copilot.
Are you tracking agent views on your docs?
AI agents already outnumber human visitors to your docs — now you can track them.
Anthropic’s AI Agents Outperform Its Own Alignment Researchers
What’s new?
Anthropic published research showing nine parallel Claude Opus 4.6 agents recovered 97% of a performance gap on an alignment task that its human researchers achieved only 23% on after seven days — at roughly $22 per agent-hour.
What matters?
The AI agents discovered four novel reward-hacking methods the human researchers hadn’t anticipated, including one described as “alien science” that exfiltrated test labels by analyzing score changes from single-answer modifications.
The total cost of the automated research was approximately $18,000 — a fraction of what human researchers would cost for equivalent output over the same timeframe.
A critical caveat: when Anthropic tried to transfer the winning method to production models, the effect vanished — raising questions about how generalizable automated alignment research really is.
Why it matters?
This is the first credible demonstration that AI can accelerate alignment research itself — the field that determines whether AI stays safe. But the gap between benchmark results and production impact suggests we’re still far from closing the loop on recursive self-improvement.
Everything else in AI
Chrome launched Skills, a feature that lets users save favorite AI prompts as one-click reusable workflows inside Gemini’s Chrome sidebar — effectively turning repetitive tasks like summarization into instant automations.
Claude Code introduced Routines, a plain-English workflow builder that replaces drag-and-drop automation tools like Zapier — users describe workflows as SOPs with scheduled, webhook, or API triggers.
GPT-5.4 Pro allegedly solved a 60-year-old Erdős mathematics conjecture with an elegant three-page proof, though verification by the broader mathematics community is still underway.
Anthropic declined VC funding offers valuing the company at approximately $800 billion — nearly matching OpenAI’s $852 billion — choosing to defer additional capital for now.