ENTERPRISE

Why Anthropic bet on adult supervision for tokens

Anthropic just launched adult-in-the-room controls for CFOs and CIOs freaking out about AI costs.

Claude Enterprise has rolled out a trio of new features to help both organizations and employees track, monitor, and control token usage, ROI, and budget utilization. Since Anthropic has established itself as the preferred AI platform among US enterprises due to its focus on safety and privacy, this is a big deal. 

As a result of executives pressuring employees to adopt AI, tokenmaxxing dominated the first half of 2026, but the backlash has clearly begun as AI inference costs have run out of control, and organizations are now moving to rein in token spending. 

Uber was one of those companies that incentivized employees to use AI by launching internal leaderboards that ranked workers by how many AI tokens they used. And then the company reportedly burned through its annual AI budget in the first four months of the year. I've heard other CTOs and executives report similar challenges.

"Every organization is super worried about the costs going through the roof," said Databricks CEO Ali Ghodsi last month at the Databricks Data + AI Summit. "It's completely unsustainable for the organizations out there… People's hair is on fire." 

And of course, a lot of these organizations are using Claude. New Ramp data from July 6 shows that 77% of organizations that have adopted frontier LLMs use Anthropic models, up 40 percentage points in the past year. 

So it's not surprising that Anthropic is working to help organizations normalize their spending. The new features in Claude Enterprise to assist with this are: 

• Spend alerts: Admins are now notified when the org reaches 75% and 90% of its usage limit, so they can raise the cap before everything gets locked down and work stops. Employees receive notifications at 75% and 95% of their personal limit and can request an increase from their manager from directly within the Claude app.

• Costs vs. outputs: As part of the richer analytics in the platform, admins can now view what was produced by Claude alongside what it cost in order to do more granular ROI analysis.

• Model defaults: Admins can now set the default model that new conversations and tasks start with for Claude, Claude Code, and Claude Cowork, so employees can start with less expensive models and only upgrade to more expensive ones when needed. This can be set based on role or across the entire org. 

IT professionals and leaders in organizations running Claude Enterprise and Claude Teams can access these new features in the analytics section inside settings in Claude. They can set the default models in the organizational settings.

No AI lab has benefited more than Anthropic from out-of-control AI inference and token costs so far in 2026. Anthropic's annual revenue run rate jumped from $9 billion at the end of 2025 to $47 billion last month. So it might seem counterintuitive that the company would want to do so much to help its customers control costs and spend less on Claude tokens. However, out-of-control inference costs have turned into such a crisis, as Ghodsi noted, that Anthropic needed to do something to maintain trust with its customers. In this case, it's taking the long view, working to be a good partner, and betting on its reputation of being the safe, reliable, enterprise-friendly AI lab. Establishing that reputation could be worth far more in the long run if AI lives up to its promises.

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POLICY

How Illinois made AI safety harder to dodge

Illinois has put forth the latest attempt to regulate the rapid pace of model development. 

On Monday, Illinois Governor JB Pritzker signed SB 315, a bill aiming to hold AI companies accountable for the powerful models they develop. The bill was passed unanimously in the Illinois state Senate and House in May, and was supported by both OpenAI and Anthropic. 

"As AI systems become more powerful and the federal government is unwilling to step in, states have a responsibility to protect our people from the dangers of AI while still harnessing the unique potential of the technology," Pritzker said in a statement. 

The bill, which is based on similar laws passed in New York and California in 2025, applies only to large frontier AI developers that generate $500 million or more in revenue. The bill will go into effect on January 1, 2027.

Though it targets a narrow audience, it applies strong safety regulation to some of the most powerful entities in AI, including: 

• Requires these companies to publicly disclose their safety frameworks and take part in third-party evaluations of their safety practices

• Compels them to report their models' critical safety incidents, such as unauthorized theft, model compromise or user deception

• Assesses for catastrophic risks, such as loss of control, use to create weapons, or the ability to carry out large-scale cyberattacks 

• Noncompliance can incur financial penalties, including a $1 million fine for the first violation and $3 million for any subsequent violations

Cesar Fernandez, head of US state and local government relations at Anthropic, said in a statement that the bill represents an "important step" toward the accountability that AI demands, as it pairs both transparency requirements with independent evaluations. "Anthropic is proud to have been the first AI lab to support this bill." 

The bill comes as AI companies navigate a minefield of US government intervention in the release of their increasingly powerful models. After the rocky rollout of Anthropic's Mythos and Fable models, and OpenAI preemptively holding back its most recent model, GPT-5.6, the government's regulatory power over these companies' model releases is far from set in stone. 

However, these companies may be working with the government on a solution: Last week, The Financial Times reported that many major AI firms are in talks with government officials to create a voluntary set of standards for releasing advanced models.

What sets the Illinois bill apart from predecessors in California and New York is that it requires independent, third-party evaluation of model safety. Without an unbiased party to audit model behavior, users must place their trust in the internal evaluations and standards to which AI companies hold themselves. Additionally, SB 315 and similar bills go a step beyond any standards that the federal government could muster because they are required, rather than voluntary. While it's good that the federal government is trying to create a unified standard for model releases, these state laws go further by holding these companies legally accountable for any potential harm they cause.

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CONSUMER

Reddit turns to AI for content cleanup

AI gave the internet a new plague: endless, low-quality content known as "AI slop." Now Reddit is betting that the same technology can clean things up.

Reddit has been reinforcing its automated spam detection tools with AI — and is seeing results. On Monday, the company shared that it blocks 23 million spam views per day before they reach users, catching 25,000 net new "spammy posts and comments" daily, and revoking nearly 2 million inauthentic votes per day. From January to March, the company says users' exposure to spam dropped by 20 percent. 

Large language models are employed to detect suspicious behavior through "highly subtle, coordinated patterns" that older detectors may have missed, Reddit said. AI is also being used on the platform to curb hate and violence in English content, with the automated system detecting harmful content in under five seconds and with greater accuracy. 

These measures aim to protect the authentic, human-made, community-based content that Reddit is known for, at a time when AI bots and content are filtering through nearly every platform and community. Beyond creating an unpleasant experience for users, AI-generated content is easy to spot, lazy, and altogether unhelpful, and it also poses real threats of spreading misinformation. 

For instance, recent research from the University of Oxford and the University of Potsdam found that when used to write or create social media posts, LLMs altered the meaning of posts on contested topics, introducing bias even when explicitly told to preserve the original meaning. Taken together, the study found that these small changes could accumulate to affect overall public opinion.

The most interesting part of the Oxford study was that the researchers recreated Grok's "explain this post" feature, which is intended as a positive tool that provides users with more context about what they're reading. However, the study found that the simulated system was more supportive of "pro-life" leaning posts than "pro-choice" when discussing abortion issues, which could steer collective opinion over time. This highlights not only the risk of using AI to solve a problem AI itself created, but also how much impact even the slightest bias can have in the long run. Reddit holds a unique position in this AI content machine. While it uses AI to combat spam on the platform, it also has several lucrative deals with AI companies that license its content to train AI models, potentially perpetuating the issue.

LINKS

• XAI rebrands to SpaceXAI, unveils new logo

• Nvidia delays release of next-generation AI server rack to 2028

• Anthropic signs $19B, 20-year TeraWulf data leases

• AI won't give people a four-day work week, NYT Opinion

• Microsoft cuts 4,800 roles due to restructuring

• Mercor hits over $2 billion in gross annualized revenue

• ChatGPT: OpenAI's flagship model is now available directly in PowerPoint. 

• Sarvam MCP Server: Gives coding agents a standard way to discover and build with Sarvam

• Tencent Hy3: A 295-billion-parameter Mixture-of-Experts model available under the Apache 2.0 license.

• Cadence: An AI screen recorder that works confidentially and accurately.

• Reflection: Member of Technical Staff - Safety

• Meta: Linguistic Engineer

• Anthropic: Security Software Engineer, Detection & Response Platform

• TikTok: Research Scientist, Intelligent Editing and AI Agent

GAMES

A QUICK POLL BEFORE YOU GO