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The Pentagon’s Fight With Anthropic Points To A Deeper Divide In The AI Economy

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This article was originally published in The Washington Independent.

By Tyreece Bauer

Washington’s clash with artificial intelligence startup Anthropic has quickly become one of the most closely watched technology disputes in the country. The Pentagon labeled the company a national security “supply chain risk,” effectively cutting it off from defense work. Anthropic responded with a lawsuit, arguing the move was retaliatory and unlawful. A federal court hearing is scheduled for later this month.

Much of the debate so far has focused on the immediate legal and ethical questions. Anthropic says the government punished it after the company refused to loosen restrictions on how its AI models can be used for surveillance and military applications. Defense officials say the military cannot rely on technology from a company unwilling to support lawful national security missions.

But the dispute also highlights a deeper divide inside the AI economy that is shaping how both government and industry approach artificial intelligence.

The debate is not only about who builds the most powerful models, but increasingly about who controls the systems and data that make those models useful in high stakes environments.

Over the past year, capable AI systems from companies such as Anthropic and OpenAI have fueled predictions that large language models will disrupt large parts of the software industry. Many investors now expect entire categories of software to be absorbed as AI systems replicate and automate core functions.

Those pressures are most visible in software as a service. Many SaaS (Software as a Service) products automate standardized workflows such as customer support, marketing analytics or document processing. These are precisely the kinds of tasks where general AI models can replicate existing tools with relative ease.

“A lot of the commentary assumes every new AI breakthrough wipes out entire sectors of software,” said investor and entrepreneur Elliott Broidy, who has been studying how artificial intelligence is being deployed in national security and investigative technology. “That tends to be true in horizontal markets where software is basically a bundle of interchangeable features. In specialized sectors, the advantage comes from domain expertise and proprietary data.”

In fields like intelligence analysis, financial crime investigations and regulatory compliance, AI systems operate inside operational platforms built on years of industry training data, investigative methods and analytical workflows. In those environments the AI model is only one component of a larger system.

“If you are operating in a complex investigative or national security environment you are not just plugging in a chatbot,” Broidy said. “You are integrating AI into a full investigative framework with proprietary datasets, analyst workflows and regulatory constraints. That is something generic models cannot replicate overnight.”

The distinction is already shaping how government agencies approach AI integration in sensitive systems. Defense agencies and intelligence organizations rely on software platforms that combine large proprietary datasets with specialized analytical tools refined through years of operational use. In those environments the AI model is only one component of a larger architecture.

Because these platforms are built around proprietary data pipelines and investigative workflows, they can integrate whichever AI model proves most effective. The infrastructure and domain expertise remain the core strategic asset.

“The model is important, but it is only one layer of the stack,” Broidy said. “In many cases the real moat is the data infrastructure and the domain expertise that surrounds it.”

The Pentagon’s decision to designate Anthropic a supply chain risk sheds light on another reality. Washington is increasingly willing to use regulatory authority and procurement power to shape how AI companies operate.

The designation applied to Anthropic is typically used against foreign companies that pose national security threats. Applying it to a domestic AI developer represents a striking escalation and forces government contractors to reconsider whether they can rely on the company’s technology.

The move also reflects growing tension between AI developers and government agencies.

Some AI companies have sought to place limits on how their systems can be used, particularly when it comes to surveillance or autonomous weapons. Government officials argue that decisions about national security capabilities ultimately belong to elected governments, not private technology companies.

At the same time, federal agencies are becoming increasingly dependent on the private sector for advanced AI capabilities. This dynamic is reshaping the relationship between Washington and Silicon Valley.

As artificial intelligence becomes embedded in sectors such as investigations, compliance and national security, companies that control specialized data and operational platforms are emerging as critical players in the technology ecosystem. In these environments, organizations prioritize reliability and institutional trust over novelty.

AI is integrated into long-standing workflows and regulatory frameworks, making the model itself only one layer of a much larger system. In that sense, the struggle between Anthropic and the Pentagon is not just about one company or one contract, but reflective of a broader contest over who ultimately controls how powerful AI systems are deployed.

 

 

 

 

 

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Anthropic Unveils AI-Vulnerability Scanner, Rattling Cybersecurity Stocks

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This article was originally published in IT Security Guru. 

By David Soffer

Anthropic has launched Claude Code Security, an AI-powered vulnerability scanner built into Claude Code on the web, now available in a limited research preview for Enterprise and Team customers.

The tool is designed to flag subtle logic flaws that are difficult to detect through manual inspection. Its launch triggered an immediate and sharp sell-off across the cybersecurity sector.

The announcement marks a turning point in how security teams find and fix software flaws. Until now, identifying hidden vulnerabilities meant relying on experienced researchers to comb through thousands of lines of code. That method is no longer the only option and, in many cases, it is no longer the most efficient one. Security tools like Claude Code Security are beginning to upend these traditional systems.

Elliott Broidy, who leads Broidy Capital Holdings and invests in AI-driven capabilities for public safety and defense, believes that Claude Code Security represents a fundamental shift in how we achieve accurate vulnerability detection. “Instead of waiting for a breach to expose a weakness, security teams can now get ahead of threats before they are ever exploited,” he said.

Anthropic’s February 20 blog post, “Making frontier cybersecurity capabilities available to defenders,” highlighted this evolution: “Security teams face a common challenge: too many software vulnerabilities and not enough people to address them. Existing analysis tools help, but only to a point, as they usually look for known patterns. Finding the subtle, context-dependent vulnerabilities that attackers often exploit requires skilled human researchers, who are dealing with ever-expanding backlogs. AI is beginning to change that calculus.”

Broidy also sees both sides of the equation clearly. “AI gives human researchers a force multiplier they’ve never had before, which is a game-changer for national security and the private sector alike,” Broidy said. “However, the same capabilities that can find a vulnerability in seconds can be weaponised to exploit one just as fast. Tools like Claude Code Security enable defenders to move at the speed of the threat for the first time.”

Unlike conventional scanners that flag known patterns, Claude Code Security uses reasoning to understand how software components interact with one another. Any vulnerability it identifies undergoes a multi-stage verification and reexamination process before reaching a human reviewer. Validated findings are then assigned a confidence rating to help security teams inspect and approve necessary fixes.

“Claude Code Security is meant to simulate the real process a human security researcher would follow when evaluating code,” said Broidy. “It can read the company’s software, flag potential issues and draft fixes. Ultimately, though, humans should make the final decisions.”

Markets responded swiftly following the announcement. According to Bloomberg, Crowdstrike Holdings fell 8%, while Cloudflare Inc. dropped 8.1%. Zscaler declined 5.5%, SailPoint tumbled 9.4% and Okta Inc. fell 9.2%. The broader selloff dragged down the Global X Cybersecurity ETF by 4.9%, leaving it at its lowest close since November 2023.

The selloff reflects a broader investor concern: that AI platforms capable of detecting and remediating vulnerabilities at machine speed could compress demand for legacy suites.

“The message from markets was hard to miss,” Broidy said. “Investors are now asking an important question. As AI companies like Anthropic and OpenAI continue rolling out tools that can write and scan software code, the pressure on traditional security vendors will only grow.”

Investor concerns have been brewing. The tool builds on over a year of internal research and testing. Claude Opus 4.6, released earlier this month, helped the team find hundreds of previously undetected vulnerabilities. It also stirred up panic and triggered broad selloff across enterprise software stocks as investors fear the sustainability of traditional enterprise software companies.

As an AI code vulnerability scanner, Claude Code Security is a signal of where the industry is heading. The models are only becoming more advanced as the race to give defenders the edge in an increasingly sophisticated threat landscape accelerates.

“There’s no question that AI is becoming the backbone of how we protect critical infrastructure,” Broidy said. “We should be excited to integrate these capabilities while remaining hyperaware of the continued risks it poses.”

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Anthropic launches Claude Opus 4.6 as AI market faces investor uncertainty

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This article was originally published in Tech Announcer.

By Hugh Grant

If anything was to be gleaned from last week’s Super Bowl ads, it’s that the AI war has officially become mainstream. Only days after launching new products (on the very same day, no less), both Anthropic and OpenAI aired primetime spots during the most important advertising moment of the year — a reminder that this race is now measured in hours, not quarters.

As artificial intelligence continues to reach and reshape global markets, the gap between rapid innovation and investor unease is becoming increasingly apparent. That tension was on full display last week as Anthropic unveiled Claude Opus 4.6, its most advanced AI model to date, even as concerns over AI disruption, valuation risk, regulation, and economic volatility ripple through public markets.

Anthropic describes Opus 4.6 as its “most capable” model for business and knowledge work, emphasizing improvements in reasoning, reliability, and the ability to handle complex, multi-step tasks. The launch draws attention to a broader trend, as AI development continues to gain momentum even amid market volatility and investor uncertainty

Still, the market backdrop has become harder to ignore. Investors have increasingly questioned whether escalating AI infrastructure spending will translate into near-term earnings, especially as companies guide to higher capital expenditures for data centers and AI workloads. At the same time, regulatory compliance costs and liability questions are coming into sharper focus, particularly in the EU, where the AI Act introduces tiered obligations and significant potential fines for certain violations, adding another layer of uncertainty to how quickly and broadly frontier models will be deployed in high-stakes settings.

For Elliott Broidy, who leads Broidy Capital Holdings and invests in AI-driven capabilities tied to public safety and defense, the moment is indicative of a larger trend of rapid technological progress moving ahead, even as markets reassess the risks.

“Every major technological shift brings uncertainty to markets,” Broidy explains. “But uncertainty has not led to retreat. The technology continues to reshape fundamental work processes.”

According to Broidy, models like Claude Opus 4.6 represent a maturation of AI from experimental tools into enterprise-grade infrastructure.

“Businesses have moved beyond seeking novelty,” he says. “They demand dependable systems that can reason, synthesize information, and support real decision-making at scale.” Anthropic’s positioning of Opus 4.6 squarely toward business and knowledge work reflects the industry’s move from demos to deployment. The company has increasingly prioritized enterprise customers over consumer-facing applications to enterprises that rely on large volumes of data, complex analysis, and high-stakes judgment. These include industries such as finance, law, logistics, government, and national security.

“When an AI model can assist analysts, operators, and leaders in making faster, better-informed decisions, it becomes a strategic asset,” Broidy noted.

The launch also spotlights a growing divide between short-term market reactions and long-term technological developments. While investors worry about overvaluation, job displacement, and regulatory risk, companies and governments are steadily embedding AI deeper into their core operations.

“In national security and public safety, hesitation is not an option,” Broidy says. “Adversaries continue to adopt AI aggressively regardless of market sentiment, compelling the United States and its allies to maintain pace.”

Broidy points out that many of the most impactful AI deployments occur far from public view. Advanced language models are already being used to assist intelligence analysis, process vast streams of open-source information, generate operational reports, and support training simulations. In defense contexts, reliability and controllability are central concerns because official guidance stresses responsible and secure deployment.

“Instilling confidence is essential,” Broidy explains. “Whether it’s a defense analyst or a corporate executive, the user needs to be certain that the system is accurate, explainable, and aligned with human intent.”

The broader lesson of Anthropic’s launch is that AI fears and AI adoption can coexist, and often do. Market volatility may dominate headlines, but behind the scenes, organizations are making long-term bets on platforms that can deliver durable advantages.

“We are witnessing the industrialization of artificial intelligence,” Broidy says. “Models like Claude Opus 4.6 represent a shift toward embedding intelligence into the fabric of institutions.”

Looking ahead, Broidy believes the companies that succeed will be those that balance innovation with discipline. “Success will come to those building systems that businesses, governments, and societies can rely on when the stakes are high,” he says.

The launch of Claude Opus 4.6 signals this transition. AI’s role as foundational infrastructure is no longer theoretical. It is here, evolving rapidly, and reshaping how decisions are made, regardless of how rattled markets may feel at the moment.