Anthropic's Copyright Crackdown: The Saga of Claude Code vs. Codex CLI

In recent years, the AI landscape has witnessed two contrasting paradigms in the realm of licensing and code accessibility, illustrated vividly by the approaches of Anthropic and OpenAI. These two organizations, both pioneers in artificial intelligence, have chosen divergent paths with their respective coding tools, Claude Code and Codex CLI. Anthropic's strict licensing policies are encapsulated in their decision to issue a takedown notice against a developer who attempted to reverse-engineer Claude Code [TechCrunch, 2025]. This move underscores their protective stance over proprietary technology, possibly motivated by security concerns given the beta status of Claude Code.

Conversely, OpenAI has embraced a more open philosophy, showcasing their tool Codex CLI under the Apache 2.0 license. This license not only permits modification and distribution but actively encourages it, promoting a spirit of transparency and collaboration among developers [TechCrunch, 2025]. This openness has been lauded by the developer community, which views OpenAI's approach as fostering a collaborative ecosystem that accelerates innovation and democratizes access to powerful AI technology.

The aftermath of Anthropic's decision reflects broader tensions within the tech community about the balance between safeguarding intellectual property and promoting an open, collaborative development culture. OpenAI's open-source strategy is seen as a potential catalyst for industry-wide shifts towards transparency, where community contributions can drive rapid enhancement and diversity in AI applications. In contrast, Anthropic's protective legal actions, though perhaps justified, are perceived by many as stifling innovation and creating barriers to developer engagement [TechCrunch, 2025].

This dichotomy between Anthropic and OpenAI also highlights critical discourse about the future of AI licensing and intellectual property norms. As AI continues to integrate into various sectors, the decisions made by leading organizations regarding code accessibility will likely set precedents for others to follow. While OpenAI's choice may pave the way for more inclusive and open models, Anthropic's strategy calls for a re-evaluation of how proprietary protections can coexist with the need for developer collaboration and innovation. The ongoing dialogue between openness and restriction in AI development not only shapes the tools available today but fundamentally influences the ethical frameworks and commercial strategies of tomorrow [TechCrunch, 2025].

In a significant development within the AI landscape, Anthropic, a burgeoning player in the field, has issued a takedown notice to a developer who attempted to reverse-engineer its coding tool, Claude Code. This move has sparked substantial discussion, particularly in light of the contrasting approach taken by OpenAI with its Codex CLI, which remains openly accessible to developers under an Apache 2.0 license. The takedown notice has been seen as a reflection of Claude Code's commercial licensing approach, which imposes strict restrictions on modification and distribution without explicit permission. This stands in contrast to OpenAI's strategy of fostering collaboration through open-source licensing, encouraging modifications and improvements from the developer community [TechCrunch](https://techcrunch.com/2025/04/25/anthropic-sent-a-takedown-notice-to-a-dev-trying-to-reverse-engineer-its-coding-tool/).

The issuance of a takedown notice by Anthropic has not only brought to the forefront issues of licensing but also ignited debates about transparency and innovation within the field of artificial intelligence. While the source code of OpenAI's Codex CLI is openly available, promoting community contributions and rapid innovation, Anthropic's approach with Claude Code emphasizes protectionism and confidentiality, likely due to the tool's beta status and potential security concerns. The decision by Anthropic to enforce its restrictive commercial license highlights a broader divide in the AI industry regarding how intellectual property is balanced against the need for innovation and transparency. Anthropic's silence on the matter further fuels these discussions, leaving room for speculations about the intentions behind their restrictive licensing model [TechCrunch](https://techcrunch.com/2025/04/25/anthropic-sent-a-takedown-notice-to-a-dev-trying-to-reverse-engineer-its-coding-tool/).

The industry reaction to Anthropic's takedown notice has been largely negative, particularly among developers who argue that such actions stifle creativity and collaboration, crucial elements for technological advancement. In comparison, OpenAI's openness with Codex CLI not only allows for competitive edge through external improvements but also builds greater goodwill within the developer community. The discontent among developers raises essential questions about the role of open-source initiatives in driving innovation versus the necessity of safeguarding proprietary solutions to protect investments and maintain control over a product's direction and development timeline. These discussions mirror larger, ongoing debates about the future direction of AI development [TechCrunch](https://techcrunch.com/2025/04/25/anthropic-sent-a-takedown-notice-to-a-dev-trying-to-reverse-engineer-its-coding-tool/).

While the immediate impact of Anthropic's legal action may seem confined to its affected parties, the broader implications hint at a potential shift in how AI technologies might be governed and perceived. The discussions propelled by this incident could influence future regulatory measures, with a growing call for policies that favor more open collaboration to prevent technological siloing. As developers continue to voice their preference for an open development model, regulatory bodies might lean towards frameworks that promote transparency and lower barriers to entry for independent developers. This scenario poses a critical juncture for companies like Anthropic, which must weigh the benefits of proprietary control against the potential downsides, such as diminished community involvement and slower innovation rates. These developments could shape the principles of digital cooperation and proprietary rights within the AI industry moving forward [TechCrunch](https://techcrunch.com/2025/04/25/anthropic-sent-a-takedown-notice-to-a-dev-trying-to-reverse-engineer-its-coding-tool/).

The ongoing debate between the open-source model of OpenAI's Codex CLI and the restrictive commercial license of Anthropic's Claude Code illustrates a broader divide in the world of AI development. Anthropic's takedown of a developer who attempted to reverse engineer Claude Code highlights their commitment to a more controlled distribution, ostensibly to protect intellectual property and perhaps safeguard Claude Code's stability during its beta stage. This contrasts starkly with OpenAI’s approach, where Codex CLI’s open-source nature under the Apache 2.0 license promotes transparency and community involvement, inviting a wealth of external feedback and advancements. Such inclusivity is designed to accelerate innovation and enhance the tool's efficacy by leveraging the collective intelligence of the global developer community.

Anthropic's approach has been met with criticism, particularly due to its use of obfuscated code and restrictive licensing, which many developers see as antithetical to the principles of collaboration and innovation. The move to issue takedown notices is seen by some as a protective measure, albeit one that alienates developers who are keen to partake in the creation and refinement of cutting-edge AI solutions. This divide brings to light the significant impact of licensing decisions not just on the pace of technical advancement, but also on the cultural ethos of the developer community, which has increasingly leaned towards open-source ideals as a means of fostering rapid progression and creativity.

OpenAI's strategic pivot towards open sourcing Codex CLI signals a potential sea change in their broader corporate philosophy, possibly influenced by the rapid adoption and communal success witnessed in other projects employing open-source models. The flexibility provided by the Apache 2.0 license allows Codex CLI to incorporate enhancements and innovations, even from competitive platforms, thereby maintaining a dynamic and flexible edge in the turbulent tech landscape. This approach may also align more closely with emerging regulatory trends favoring transparency and competition, potentially swaying governmental policy discussions to favor open-source solutions in AI development.

The economic and social implications of these licensing models extend far beyond immediate business tactics. Codex CLI’s open-source framework potentially increases its uptake and utility across various sectors, fostering a decentralized structure of technological development. This stands in stark contrast to the limitations that Claude Code’s restrictive licensing could impose, potentially curtailing its own market penetration and innovation. The closed nature of Claude Code might result in less spontaneous adaptability and a narrower scope of applications, as developer input and communal testing are relatively restricted. In this light, the success of AI tools is integrally linked to their ability to engage openly with an expanding, resourceful developer community.

Public reactions to Anthropic's licensing decisions reflect a preference for accessible and transparent development processes. The developer community, vocal on platforms such as social media and forums, has largely criticized Anthropic for stifling innovation by keeping Claude Code under wraps. Meanwhile, OpenAI's Codex CLI enjoys widespread approval for its open-source model which encourages an ecosystem of shared knowledge and rapid iteration. The discourse between these two approaches shapes future perceptions of AI governance, pressing the necessity for a balance between protecting intellectual property and ensuring the collaborative spirit that fuels technological advancement.

Anthropic's stance on licensing versus OpenAI's open-source model may dictate broader industry standards and influence future legislative frameworks. As AI continues to integrate into diverse industries, the line between proprietary control and public accessibility becomes increasingly significant. The debate over the proper balance of these interests might not only determine the future of AI coding tools but could also set precedents that impact other technological innovations, highlighting the delicate interplay between regulation, corporate strategy, and developer engagement. The industry’s ability to reconcile these differing philosophies will shape how technologies continue to evolve and who gets to shape their journey forward.

The developer community has been abuzz with reactions and backlash following Anthropic's recent decision to issue a takedown notice to a developer for reverse-engineering their AI coding tool, Claude Code. A sharp outcry has emerged, primarily focused on the restrictive nature of Claude Code's licensing compared to OpenAI's open-sourced Codex CLI. Developers have expressed their disapproval through various forums and platforms, highlighting how Anthropic's approach is seen as a barrier to innovation and collaboration. The takedown notice, reported by TechCrunch, portrays a stark contrast with OpenAI's efforts to engage more openly with the developer community.

Anthropic's decision has not only stirred controversy but has also cast a spotlight on the broader discussion of open versus closed software ecosystems. While OpenAI's Codex CLI is lauded for its open-source Apache 2.0 licensing, which allows for flexible use and community contributions, Anthropic's commercial license for Claude Code is seen as limiting and protective of its intellectual property. Developers argue that such a stance throttles the collaborative spirit necessary for innovation. This development reflects a deep divide in how leading AI companies view their role in the broader technological ecosystem.

Public opinion largely sides with open collaboration, as evidenced by the flurry of negative comments on social media platforms like X and discussions on Reddit. The consensus among many in the coding community is that transparency and open access catalyze technological advancements. The backlash against Anthropic also underscores the importance developers place on contributing to and benefiting from shared projects. As reported by TechCrunch, the open nature of Codex CLI is praised for fostering an inclusive environment where developers can freely modify and enhance the tool.

The backlash serves as a crucial talking point regarding the economic and social impacts of such licensing decisions. OpenAI's decision to open-source Codex CLI has strengthened its rapport with developers, fostering an enthusiastic community and promoting rapid innovation. Meanwhile, Anthropic's restrictive approach has raised concerns about possibly isolating it from the vast potential of developer-driven enhancements. This situation illustrates a practical case of how licensing strategies can influence a tool's market success and developer goodwill. As more companies observe the impacts of these strategic choices, the industry may see a shift towards more open, collaborative development environments.

OpenAI's decision to open-source its Codex CLI marks a significant departure from its previous trend towards proprietary systems. By adopting an Apache 2.0 license, OpenAI not only encourages experimentation and innovation within the developer community but also sets a precedence for inclusivity and collaboration in AI development. This approach is seen as a strategic move to build trust and engagement among developers, potentially increasing the adoption rate of its tools. In a contrast marked by transparency and collective progress, OpenAI positions itself as a facilitator of growth and knowledge sharing within the tech ecosystem.

Anthropic, by issuing takedown notices against those attempting to reverse-engineer Claude Code, highlights its stance on safeguarding intellectual property through restrictive licensing. This approach, while protecting its commercial interests, has drawn criticism for stifling innovation and limiting collaboration among developers. The obfuscation of Claude Code, enforced by a stringent licensing framework, suggests that Anthropic prioritizes control and security possibly due to the tool's beta status. However, this strategy risks alienating developers who are looking for more openness and the capacity to contribute to and enhance the software.

The backlash against Anthropic's restrictive practices, in contrast to OpenAI's open strategy, exemplifies the broader debate in the tech community over licensing and accessibility. OpenAI's model supports the view that open-source is synonymous with progress, encouraging collective problem-solving and accelerating development through shared knowledge and resources. Anthropic’s approach, however, underscores a more conservative view that places economic and security considerations at the forefront, potentially at the expense of community engagement.

As OpenAI and Anthropic take divergent paths regarding their approach to intellectual property and open source, the implications of these choices extend beyond their immediate circle of influence. OpenAI’s strategy might prove influential in shaping future regulatory norms favoring transparency, while Anthropic’s protective measures might prompt calls for stronger IP laws. This dichotomy not only impacts developers and the pace of AI innovation but also potentially informs policy frameworks that balance open collaboration with proprietary security.

The economic landscape of AI tools development is witnessing a significant impact from the divergent licensing strategies adopted by companies like Anthropic and OpenAI. While Anthropic has taken a more conservative approach by implementing a restrictive commercial license for its coding tool, Claude Code, this strategy might inadvertently stifle its economic propulsion. By restricting accessibility and modification through obfuscation and legal layers, Anthropic may see limited external developer engagement, which could slow down innovation and restrict market expansion. This could pose challenges in maintaining competitiveness against more open models like OpenAI's Codex CLI, which operates under an Apache 2.0 license encouraging extensive modification and distribution. As a result, Codex CLI likely enjoys accelerated community-driven enhancements that enhance its economic viability and market presence, as it harnesses a broader developer community working on feature development and implementation improvements.

The market impacts emerging from Anthropic’s and OpenAI’s licensing models are profound, as they directly influence how broadly these technologies are adopted and integrated across various industries. OpenAI's Codex CLI has the potential to revolutionize market penetration thanks to its open-source nature, which fosters a large community of developers who contribute to, iterate on, and refine the tool. This approach allows for swift adaptability to market demands and technological advancements, thus encouraging broader industry adoption. By contrast, Anthropic's closed licensing model around Claude Code might restrict its reach and slow down its integration into diverse market sectors. This could lead to potential under-utilization and affect the financial returns anticipated from launching such an innovative platform.

Furthermore, the choice of licensing strategy profoundly affects the economic ecosystem surrounding AI development. Open-source models like OpenAI’s not only encourage a vibrant developer community but also reduce the barriers to entry for smaller startups and independent developers who can contribute at minimal cost. This inclusivity fosters a competitive technological environment, which is essential for economic growth and innovation in the AI sector. Conversely, Anthropic's strategy might create barriers to entry, privileging established companies that can afford to navigate more restrictive licenses, thereby potentially limiting the diversity of technological solutions and stifling competitive innovation within the market. This can ultimately influence how agile the broader AI industry can be in responding to new challenges and demands.

The economic disparity between these two licensing strategies extends into how each company can manage and sustain ongoing development and maintenance costs. OpenAI's strategy of tapping into a global community of contributors can significantly lower development costs, as updates and new solutions can be innovatively sourced directly from a decentralized group of contributors. This approach not only enhances cost efficiency but also ensures that the Codex CLI remains at the cutting edge of technological advancement. Alternatively, Anthropic may need to invest considerably in internal resources for development and troubleshooting, which could increase operational expenses and reduce financial efficiency. Thus, while ensuring close control over product iterations, Anthropic may face higher costs which could impact the pricing strategies and economic accessibility of its tools.

Ultimately, the contrasting strategies employed by Anthropic and OpenAI can serve as critical insights for potential regulatory frameworks surrounding AI licensing and intellectual property. The economic implications of these licensing decisions might inspire new policies that aim to balance the protection of intellectual property with the benefits of open collaboration. With a growing emphasis on transparency and community-driven development, especially within the high-tech sphere, policymakers may look towards OpenAI’s model when considering regulation that best fosters innovation while protecting key commercial interests. As these discussions evolve, the outcome could play a pivotal role in shaping the future economic landscape of AI technologies and their responsible deployment.

The tech industry stands at a crossroads with the ongoing debate between open-source and proprietary models, as prominently highlighted by Anthropic and OpenAI's differing approaches to their AI coding tools. Anthropic's issuance of a takedown notice for reverse-engineering its Claude Code is a testament to the company's preference for stringent control over its intellectual property. This decision has met with significant backlash from developers who argue that such restrictions stifle innovation and collaboration. On the other hand, OpenAI's Codex CLI, licensed under Apache 2.0, embraces open-source principles, fostering a culture of shared progress and transparency. This contrast reflects a larger cultural divide within the tech industry, where openness is often seen as an engine for innovation and community building [source].

Socially, the implications of these differing licensing strategies are profound. OpenAI's open-source approach is likely to enrich the developer community by encouraging participation from a broader audience, thereby enhancing innovation through diverse inputs and experiences. Developers gain not only from improved tools but also from a supportive network of peers, further embedding the value of collaboration within the industry. Meanwhile, Anthropic's more restrictive practices could lead to a fragmented community where knowledge sharing is limited, potentially isolating developers and reducing the potential for groundbreaking advancements. These cultural dynamics underscore the importance of community engagement in driving technological progress and maintaining an inclusive, collaborative tech ecosystem [source].

Culturally, the choice between open-source and proprietary systems is more than just a technical decision; it's a reflection of deeper values within the tech industry. OpenAI's model aligns with a philosophy that values transparency and collective growth, inviting developers to participate in the evolution of AI technologies. This inclusivity can be seen as a moral stance, advocating for a future where technological advancements benefit a wider audience. In stark contrast, Anthropic's approach reflects a protective stance over its innovations, prioritizing control and ensuring security, especially considering the potential vulnerabilities of a tool still in beta stage. Such divergent philosophies influence not only how companies operate internally but also shape their public perception and ability to attract collaborative partnerships [source].

The intersection of regulatory and political dimensions with intellectual property (IP) rights poses significant challenges in the burgeoning field of artificial intelligence (AI). Companies like Anthropic and OpenAI exemplify contrasting approaches to these challenges through their licensing strategies for AI coding tools. Anthropic's decision to issue a takedown notice for reverse-engineering its Claude Code underscores a defensive posture toward IP that prioritizes commercial confidentiality and security, given the tool's beta status [1](https://techcrunch.com/2025/04/25/anthropic-sent-a-takedown-notice-to-a-dev-trying-to-reverse-engineer-its-coding-tool/). This approach, while protecting the company's proprietary assets, can stifle innovation by limiting developer access and collaboration.

Conversely, OpenAI's open-source strategy with Codex CLI represents a philosophical shift towards greater transparency and community involvement. By adopting an open license, OpenAI not only embraces a collaborative development model but also aligns itself with regulatory frameworks that favor openness and innovation [1](https://techcrunch.com/2025/04/25/anthropic-sent-a-takedown-notice-to-a-dev-trying-to-reverse-engineer-its-coding-tool/). OpenAI's model offers insights into how policy can support technological advancement by fostering an environment conducive to shared learning and progress, potentially influencing future regulatory trends in favor of open-source frameworks.

Regulatory bodies face the complex task of balancing the divergent interests of protecting intellectual property and promoting innovation. As AI continues to permeate various industries, the need for clearer legal frameworks becomes more pressing. These frameworks must address issues of IP rights, fair market competition, and ethical deployment of AI technologies [5](https://opentools.ai/news/anthropic-vs-openai-the-tug-of-war-over-openness). The symbolic tug-of-war between Anthropic's defensive licensing and OpenAI's open-source approach provides a critical narrative for understanding the evolving landscape of AI regulation.

Political influences on AI licensing are increasingly prominent as governments seek to regulate an industry fraught with potential for abuse and inequity. Initiatives such as HarperCollins' partnership with Microsoft for content licensing highlight proactive moves towards compliance and fair usage in AI [1](https://licensinginternational.org/news/what-to-expect-from-ai-in-2025/). As AI tools become integral across sectors, regulatory mechanisms must evolve to ensure intellectual property rights do not impede accessibility and innovation.

This dynamic interplay between IP rights and regulatory frameworks reflects broader societal values about ownership and collaboration. OpenAI's approach, which nurtures community trust and transparency, suggests that an open-source ethos could serve as a guiding principle for future AI development policies. By fostering an ecosystem where developer contributions are valorized, OpenAI promotes a model that might ultimately be more adaptable to fast-changing technological landscapes [11](https://opentools.ai/news/anthropics-takedown-tactic-the-battle-over-ai-code-ownership-escalates).

The landscape of AI development and innovation is rapidly evolving, driven by diverse philosophies and approaches from leading AI companies. As we step into the future, the contrasting strategies of Anthropic and OpenAI serve as a pivotal case study in the broader conversation about openness versus proprietary systems. Anthropic's recent actions, particularly the issuance of takedown notices against developers attempting to reverse engineer their coding tool, Claude Code, underscore a protective stance towards their intellectual property. This protective approach, as seen in their restrictive commercial licensing, stands in stark contrast to OpenAI's more inclusive, open-source strategy with their Codex CLI tool [1].

This dichotomy highlights critical implications for the future of AI, especially in terms of innovation, collaboration, and regulatory developments. OpenAI, through its open-source licensing, fosters a collaborative ecosystem that not only encourages community input but also accelerates technological progression through collective innovation. This approach, by welcoming community contributions, potentially speeds up feature development and allows for a wider application reach. OpenAI's recent commitments to open source reflect a potential shift towards more transparent operations, possibly influencing broader industry standards and regulatory policies that could favor such open frameworks [1].

In stark contrast, Anthropic's closed ecosystem, exemplified by their obfuscation of Claude Code's source code, raises concerns about the limitations imposed on innovation and the potential alienation within the developer community. While such controlled environments may address security and commercial interests, they pose significant challenges to inclusive innovation and may stifle independent experimentation and growth. The criticism faced by Anthropic, particularly on public platforms such as Reddit and social media, signals a growing discontent among developers who favor OpenAI's open-source model [1].

Looking forward, these diverse approaches will shape the economic, social, and political fabric of AI technologies. Economically, OpenAI might gain a competitive edge through rapid community-driven innovation that enhances market penetration. Socially, their open model reinforces community solidarity and shared progress, while politically, it may align with regulatory trends advocating open-source practices. On the other hand, Anthropic’s strategy could result in slower adoption and innovation, calling for more robust intellectual property protections in AI software markets. Both paths have merits and challenges, and their ongoing evolution will likely inform future regulatory and industry practices [1].

The broader implications for AI licensing and intellectual property rights are profound. As OpenAI pushes towards an open-source future, there's potential for a more collaborative, transparent, and innovative AI ecosystem. This could set a precedent for licensing strategies that balance intellectual property protection with a commitment to openness and community engagement. Conversely, Anthropic's current stance highlights the complexities of AI's commercial landscape, prompting discussions on how to best manage intellectual property without dampening innovation. This ongoing debate will be crucial in shaping the policies and practices that govern AI technologies in the coming years [1].

The ongoing dialogue surrounding AI licensing and technology advancements is defined by contrasting philosophies on openness and innovation. Anthropic's recent takedown notice, targeting a developer for reverse-engineering its coding tool Claude Code, underscores a significant tension in the tech industry. This decision highlights Anthropic's commitment to protecting intellectual property through restrictive licensing, which contrasts starkly with OpenAI's open-source strategy for its Codex CLI. OpenAI's approach reflects a more inclusive vision that has been met with widespread approval among developers for promoting collaboration and collective enhancement [TechCrunch](https://techcrunch.com/2025/04/25/anthropic-sent-a-takedown-notice-to-a-dev-trying-to-reverse-engineer-its-coding-tool/).

Anthropic's stringent license model and the subsequent legal actions have ignited debates over intellectual property rights and the role of open-source frameworks in AI development. While the protective measures serve to safeguard Claude Code's proprietary elements, they are perceived by many as stifling potential innovations that could arise from broader community engagement. This sentiment underscores a broader industry challenge: balancing the protection of commercial interests with the benefits derived from an open exchange of ideas and collaborative advancements [TechCrunch](https://techcrunch.com/2025/04/25/anthropic-sent-a-takedown-notice-to-a-dev-trying-to-reverse-engineer-its-coding-tool/).

The economic implications of these licensing strategies are profound. Claude Code's restrictive environment might limit its adaptations and market penetration, potentially narrowing its competitive edge against more open systems like Codex CLI. Conversely, OpenAI's open-source ethos not only enhances the tool's developmental velocity but also aligns with modern trends toward democratizing AI technology. This encourages a more rapid uptake and iterative development cycle driven by a global community of developers, fostering a more adaptive and innovative AI ecosystem [TechCrunch](https://techcrunch.com/2025/04/25/anthropic-sent-a-takedown-notice-to-a-dev-trying-to-reverse-engineer-its-coding-tool/).

Public and industry reactions to Anthropic's stance are indicative of an ongoing shift towards valuing transparency and openness in technology. Although Anthropic's approach ensures high control over its proprietary software, it has faced substantial criticism for potentially hindering innovation and isolating developers from contributing to growth. This critique is further amplified when compared to OpenAI's more open, collaborative ethos with Codex CLI, suggesting a possible realignment of industry values toward inclusivity and shared technological progress [TechCrunch](https://techcrunch.com/2025/04/25/anthropic-sent-a-takedown-notice-to-a-dev-trying-to-reverse-engineer-its-coding-tool/).

Looking towards the future, the divergent paths taken by Anthropic and OpenAI in terms of license strategy and AI development pose significant implications for intellectual property and technological governance. As regulatory frameworks evolve, the outcomes of such corporate strategies will likely influence how AI tools are developed, shared, and secured across the tech landscape. The balance between protecting proprietary technology and fostering a collaborative, open environment is crucial for determining the direction of AI innovation and its integration into wider technological and commercial ecosystems [TechCrunch](https://techcrunch.com/2025/04/25/anthropic-sent-a-takedown-notice-to-a-dev-trying-to-reverse-engineer-its-coding-tool/).