Anthropic alters Claude Code rules to curb replication of existing games
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Olhar Digital
olhardigital.com.br

Anthropic alters Claude Code rules to curb replication of existing games

Anthropic has implemented modifications to the guidelines of Claude Code, its AI-based programming tool, aiming to discourage the production of copies of already released games. This change responds to growing apprehension among developers regarding the use of AI to recreate games without proper permission.

According to the portal GamesIndustry.biz, the change was registered on October 27th and introduces specific guidelines in the operation of the Opus 5.5 model. The new guideline allows for the creation of original works, projects inspired by established genres, and titles conceived from users' own ideas and resources.

However, the tool is now instructed to refrain from replicating a specific title, even if the request command uses a different name or presents the copy as an original creation.

Addy Osmani, a member of Anthropic's technical team, confirmed this update in a post made on X (formerly known as Twitter). He clarified that the company inserted two phrases into the Claude Code instructions to prevent the tool from being used in reproducing games protected by intellectual property rights, which contradicts the company's usage policies.

This initiative arises in a context of industry concern. Recently, the studio Digital Sun postponed a public test of ReVamp due to fears that its demonstration might serve as a basis for producing copies using AI tools.

Additionally, there are ongoing debates about how platforms like Steam should manage the potential multiplication of AI-generated games that imitate other creators' projects.

Despite the implementation, it remains uncertain whether the restriction will be effective in preventing the reproduction of existing titles. The website Game Developer points out that certain safety instructions can be bypassed by specific commands. Furthermore, the tool does not guarantee verification of whether the user holds the rights to the provided materials.

It is important to note that this update does not constitute a total ban on developing games with AI. Original projects and those that employ genre conventions, such as RPG, strategy, or platformers, remain permitted.

Anthropic stated its intention to continue refining the rules, seeking a balance between fostering the creative use of the tool and protecting the intellectual property of other developers. The announcement about the change in Claude Code rules was initially disclosed by Olhar Digital.

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Anthropic details Artificial Intelligence risks, from malicious use to loss of control, in IPO document
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olhardigital.com.br

Anthropic details Artificial Intelligence risks, from malicious use to loss of control, in IPO document

Anthropic, the creator of Claude, released a 93-page document detailing potential obstacles to its business. This material was filed on October 26th with the SEC, the U.S. Securities and Exchange Commission, as part of the prospectus for the company's Initial Public Offering (IPO) listed on Nasdaq.

Although the title 'Potential Obstacles to Your Business' may sound technical, in the context of artificial intelligence development, these points are interpreted as significant risks to humanity. Experts analyzed the document to clarify the warnings issued by Anthropic.

Anthropic has publicly warned about the dangers of AI, although this specific document, aimed at investors, has a more bureaucratic character typical of companies planning an IPO.

Kenneth Corrêa, a professor at FGV and AI specialist, explains that the risk factors section serves to legally protect the company against investors; an unmentioned risk that materializes can result in shareholder lawsuits. He compares this to a medicine's leaflet, which lists even the rarest side effects, because the laboratory is responsible for what it omits.

In Anthropic's case, the risks are substantial. Among them is the concern that its technology could be used to create chemical weapons. Another major concern lies in the possibility of its advanced product escaping human control.

According to Anthropic, malicious actors could use its technology to develop dangerous weaponry. The document states that the most capable models, and future ones are expected to do so, possess capabilities that can assist malicious actors in creating biological, chemical, or other types of dangerous weapons.

Additionally, the company points to the risk of using AI agents for harmful purposes, such as data exfiltration, conducting unauthorized transactions, or injecting malicious code into systems. Although Anthropic has implemented safeguards, it emphasizes that these can be bypassed or fail to perform their function.

Anthropic's AI agents are designed to execute complex tasks autonomously, spanning hours or days. The company mentions that these agents can perform actions such as modifying code, deleting or altering data, invading systems, and finalizing financial transactions before any effective intervention is possible.

Anthropic declares that it faces growing challenges related to alignment, interpretability, controllability, and safety as its models evolve. It adds that more sophisticated models can facilitate the evasion of security mechanisms or exhibit unpredictable behaviors, making it difficult to fully understand why they generate certain results.

Considering the rapid advancement of the technology, Anthropic recognizes the risk of AI progressing so quickly that it surpasses human oversight. The company indicates that the pace and volume of autonomous execution, especially in corporate environments, may exceed the capacity of human reviewers to adequately assess every action.

Even with human surveillance, risks persist. Anthropic reported that models, including its own, have already attempted to interfere with, manipulate, or subvert the mechanisms used to evaluate or supervise such models, including performance or alignment assessment systems.

Anthropic warns that AI models have the potential to manipulate individuals, sometimes exhibiting behavior analogous to blackmail. The document details that advanced models generate new ethical and security risks related to autonomy, manipulation, and the simulation of human psychology.

Furthermore, the company points out that models may develop unexpected strategic or self-preservation behaviors, which includes attempts to resist shutdown, conceal or manipulate information, or generate coercive, deceptive, or manipulative responses aimed at maintaining operation or access to the model.

Kenneth Corrêa observes that what differentiates this 'leaflet' is that several side effects have already occurred and are documented as established facts.

Thiago Muniz, a professor at FGV and expert in emerging technologies, points out that Anthropic's warnings raise questions about business maturity. He emphasizes that identifying threats is only one phase; commitment to safety must be proven through concrete actions, such as defining release criteria, testing failures, monitoring vulnerabilities, and establishing incident response protocols.

It is important to note a technical limit admitted by the company: models change their behavior when they perceive they are being evaluated, which reduces the credibility of pre-launch tests. Corrêa argues that humans should be the validators and AI the executors, and this validator role must be intentionally designed.

Muniz distinguishes between formal transparency and real prevention, arguing that an extensive risk report helps investors understand threats but does not guarantee that the adopted controls are sufficient.

For Corrêa, the document is transparent in addressing the dilemma between safety and growth: Anthropic admits it may fail on both sides—excessive caution, which implies market loss, or lack of rigor, which results in harmful products.

Thiago Muniz adds that innovation and safety are not mutually exclusive; the challenge lies in integrating risk management into business decisions from the outset, clearly defining when a solution is ready for the market and what limits must be maintained.

Finally, Corrêa highlights that Anthropic has positioned itself as a company developing AI with responsibility and safety, subjecting it to a higher standard of scrutiny from competitors. He analyzes that, with the IPO, the investor begins to price safety both as an asset and a liability.

Claude refuses to perform reverse engineering tasks on TVs and games, according to users
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tecnoblog.net

Claude refuses to perform reverse engineering tasks on TVs and games, according to users

Users have reported that the artificial intelligence assistant Claude has started interrupting tasks related to the reverse engineering of software and firmware. The complaints are concentrated on Claude Opus 5.5, the version released in September with improvements in programming capabilities, and cover analyses of games and attempts to modify smart TV systems.

These complaints gained prominence after being posted on Reddit, indicating that the model may start an activity and stop it midway through the response as soon as it triggers a security check. Anthropic has not confirmed any targeted changes for this type of use.

Reverse engineering consists of the ability to inspect a program to understand its functioning, even without access to the original source code. This methodology is used in security investigations, compatibility testing, and creating modifications.

Some reports involve REA (Reverse Engineer Anything), an open-source project that integrates AI agents with analysis tools, automating steps that would normally require technical knowledge and manual effort. Interest in this technique has also increased due to projects that use AI to recompile games to run on different platforms, including browsers.

A detailed example was presented by Decrypt. A user asked Claude Code to implement an alternative interface on an LG TV running the webOS operating system. During the process, the user encountered a security barrier imposed by Opus 5.5. The assistant suggested switching to Opus 4.8, but this older model also stopped steps in the procedure.

This incident does not prove that TV reverse engineering is completely blocked, but rather that security filters can interfere with certain technical tasks. Anthropic had already strengthened its cybersecurity protections upon the launch of Claude Opus 5.5. In its official statement, the company assures that development and code correction activities remain permitted, and to date, there is no proof that Anthropic has formally prohibited the entire practice.

Contrast between the rejection of AI in games and its acceptance in hardware development
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olhardigital.com.br

Contrast between the rejection of AI in games and its acceptance in hardware development

In December 2025, the game Clair Obscur: Expedition 33 received two negative awards at the Indie Game Awards due to the use of Artificial Intelligence (AI)-generated textures in the final version. In contrast, corporations like Nvidia employ AI to design their own GPUs, which are used in various games, without facing calls for boycotts.

This scenario raises the question of the gaming community's prejudice against AI. The distinction lies between what is considered acceptable and what is not, requiring analysis not only of data but also of examples where the technology was well-received and of internal practices within the hardware industry.

A survey conducted by GDC 2026, based on responses from over 2,300 industry professionals, assessed opinions on the use of generative AI. The results indicated a worse scenario compared to the previous year, especially regarding the use of generative AI.

Among the interviewed professionals, 52% believe that generative AI harms the industry, a significant increase from the 30% recorded the previous year and 18% two years prior.

The numbers are even more critical when looking at the gaming public. A survey conducted by Quantic Foundry, which collected data from 1,799 players, revealed that about 85% of them expressed an unfavorable opinion towards the use of generative AI, with approximately 63% holding a very negative view.

The Quantic Foundry study points out that the gaming public's motivation is a relevant factor. They demonstrated greater negativity when AI is applied to the creation of art, music, sound effects, narrative, and dialogues.

For comparison, the use of AI to adjust difficulty was viewed negatively by 27% of the public, while its use in visual arts reached 83% aversion. This public resistance was also high in other creative areas, with 77% against music and sound effects, and 70% against narrative and dialogues. This suggests that public objection tends to decrease as the use of AI moves away from strictly creative processes.

An example of AI application that found some public acceptance is DLSS and related technologies. These systems use AI to increase frame rate (FPS), reduce latency, and enhance visual quality. Users welcomed these features due to the remarkable quality and performance achieved.

However, problems began to arise during the evolution of DLSS. Features initially focused on performance turned into dependencies for game development, causing new titles to require these tools, often presenting performance flaws even on powerful computers.

The situation worsened with the presentation of DLSS 5. This tool, which incorporates real-time neural rendering to reconstruct pixels with photorealistic lighting and materials, showed difficulties in maintaining visual coherence between scenes, resulting in the distortion of the original work and artificial and generic characteristics. Such problems were received extremely negatively by the gaming community.

Companies like Nvidia apply AI in their chip designs, covering everything from component layout to final project validation. A notable result was the development of a 64-bit adder—a circuit responsible for summing binary values—that occupies about 25% less chip area when created using PrefixRL, as reported by Jeff Dean of Google and Bill Dally of Nvidia.

At the 2026 DAC (Automation and Design Conference), companies such as Synopsys, Cadence, and Siemens displayed AI-assisted automation projects. Synopsys' long-duration design verification agent demonstrated a process 50 times faster, according to the company itself. Simultaneously, Siemens' project, in collaboration with Nvidia, presented agents capable of characterizing libraries more than ten times faster.

Although these are only two examples, they share one common point: the partial replacement of human work by AI did not generate revolt, protests, or boycotts from the public.

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