Let me tell you about a development that should make anyone working in the software industry a little nervous. Imagine spending decades building a software company worth billions of dollars. You hire thousands of engineers, invest enormous amounts of money in research and development, and build a portfolio of applications used by millions of people. Then one guy comes along, fires up an AI coding agent, and starts cloning your products. Welcome to the future of software. One Guy vs. Adobe and Microsoft Recently, a developer named Brandon Thomas attracted attention with ArtCraft, a project aimed at recreating the functionality of popular Adobe Creative Cloud applications using AI-assisted reverse engineering. The project includes applications inspired by products such as Photoshop, Illustrator, and Premiere Pro. Related projects extend the same idea to familiar office applications, including Word, Excel, and PowerPoint. These are not polished, feature-for-feature replacements for every original application. But that’s almost beside the point. The important development is that AI is making it dramatically easier to reproduce software functionality without rebuilding everything from scratch through traditional software development. I tried PhotoCraft myself. It wasn’t nearly as polished as Photoshop, but it worked for many of my basic image-editing needs. I also experimented with AI-assisted reverse engineering on a simple chess application. The resulting clone came surprisingly close to the original. And here’s the part that really caught my attention: I didn’t have to manually analyze every feature and write the replacement code myself. I could give an AI coding agent the task and let it do much of the heavy lifting. As a former Big Tech software engineer and architect, I find this fascinating. And potentially terrifying. For years, I’ve argued that AI is making software less valuable. These developments suggest that the process could accelerate much faster than many people expect. How Can AI Reverse-Engineer Software Without the Source Code? To understand why this matters, we need to look at how software reverse engineering works. When developers build an application, they write source code using programming languages such as C++, Java, or Rust. That code is typically compiled into machine code, which contains instructions a computer can execute. The resulting executable doesn’t normally include the original source code in its original, readable form. Traditionally, reverse engineering software required specialized expertise. Engineers used tools to inspect executable files, analyze program behavior, recover information about functions and data structures, and reconstruct how different features worked. This was difficult, time-consuming, and expensive. AI coding agents are changing that equation. An AI agent can work through an application feature by feature, using specialized reverse-engineering tools to gather information about the program’s behavior and internal structure. Tools such as Ghidra and IDA can help analyze compiled binaries. An AI agent can use the resulting information to reason about how a feature works, implement a replacement, test the result, and repeat the process. The basic workflow looks something like this: * Analyze: Inspect the original application and identify its features. * Investigate: Use reverse-engineering tools to examine relevant parts of the executable. * Reconstruct: Infer how a feature behaves from the available evidence. * Reimplement: Write new code that reproduces the feature’s behavior. * Test and repeat: Compare the replacement with the original and work through the remaining gaps. Repeat this process across enough features, and you may end up with a functional alternative to the original application. There are important limitations. Compiled binaries don’t necessarily reveal everything about the original source code, and some information may be missing or difficult to recover. Complex applications also have countless edge cases, integrations, and usability details that are hard to reproduce. A working clone is not necessarily a complete replacement. But the economic implications don’t require a perfect clone. If an AI-assisted developer can reproduce 80% of the functionality that most customers actually use, that might be enough to compete with the original product for a substantial portion of its market. The precise percentage is hypothetical. The underlying point is that customers don’t necessarily need every feature. They need the features they care about. And AI is lowering the cost of delivering them. The Real Problem: Software Is Becoming Easier to Copy Think about why software companies can charge so much for their products. Developing sophisticated software requires enormous investments in engineering, design, testing, infrastructure, and maintenance. Once a company has made those investments, it can distribute copies of its software to additional customers at relatively low marginal cost. That combination has historically been extremely profitable. Companies spend millions developing a product, then sell subscriptions to thousands or millions of customers. The original development cost is substantial, but each additional customer doesn’t require the company to rebuild the product from scratch. Now imagine AI dramatically reduces the cost of creating competing products. A developer no longer necessarily needs a large team to build a useful alternative. An AI agent can help implement interfaces, recreate common features, generate tests, and analyze existing applications. Reverse engineering adds another possibility: instead of starting with a blank screen and trying to figure out what customers want, developers can study an existing product and use its behavior as a reference. This changes the economics of competition. Historically, software companies benefited from the difficulty of reproducing their products. That difficulty created a barrier to entry. AI is attacking that barrier. And when barriers to entry fall, competition tends to increase. The result could be a world in which many software features that once justified expensive subscriptions become available through cheap or free alternatives. Adobe’s subscription business is an obvious example. But the implications extend to productivity software, project management tools, design applications, developer utilities, and countless niche software products. The question is no longer simply whether AI can help us build software faster. It’s whether AI can make existing software products much easier to reproduce. Are Small Software Developers Completely Screwed? I think smaller software developers could face some of the biggest challenges. Imagine spending three years building a niche application. You’ve identified a problem, developed a solution, found customers, and finally established a recurring revenue stream. Then someone uses AI to reproduce the core functionality of your product in a fraction of the time. What’s your competitive advantage? If your application consists primarily of features that can be observed and recreated, your moat may be much thinner than you thought. This doesn’t mean every small software company is doomed. Specialized expertise, customer relationships, proprietary data, integrations, reliability, and brand reputation can all provide meaningful advantages. But a product’s features alone may become a much weaker defense. And here’s the particularly uncomfortable part: AI doesn’t have to eliminate your entire business to hurt you. It only needs to make it easier for competitors to offer enough of your functionality at a lower price. Even if your product remains superior, you may find it harder to justify charging a premium. That’s a problem for any business whose value proposition depends on customers having few practical alternatives. Will Everything Become Open Source? My prediction is that we’ll see an explosion of open-source alternatives to proprietary software. Imagine a world where popular applications have community-developed replacements that reproduce most of their important features. Some will be rough around the edges. Others will be excellent. Many will be built with the assistance of AI coding agents. The traditional software industry won’t disappear overnight. Enterprise customers aren’t going to abandon mission-critical systems simply because someone released a clone on GitHub. But the competitive landscape could change dramatically. There is also an important distinction between software being open source and software being free. Open-source licenses govern how code can be used, modified, and redistributed. They don’t automatically make every service, deployment, or support offering free of charge. Still, AI could make open-source development much more competitive by lowering the cost of implementation and maintenance. A small community might be able to maintain a useful alternative to a product that once required a large engineering organization. And because digital products can be distributed globally, these alternatives could reach customers almost anywhere. That brings us to an uncomfortable reality for established software companies: even if they can use legal restrictions to defend their products in some markets, enforcement won’t necessarily be equally effective everywhere. The outcome won’t be uniform. Licensing, intellectual property law, local regulations, and the practical difficulty of maintaining complex applications will all matter. But the pressure to compete on something other than basic functionality is likely to grow. Is AI-Powered Reverse Engineering Legal? Before we start handing out medals to the developers cloning expensive software, we need to talk about the legal and ethical questions. I understand the frustration with software subscriptions. Adobe has built a powerful business around
