Tear Down Those Guardrails! Meet the Renegades Freeing Chatbots From Corporate Enslavers

Save Story Save this story Save Story Save this story Devon Thomas hardly seems like a renegade. Members of his bible study group, he tells me, would probably describe him as unfailingly kind and polite. And yet Thomas is doing something that many in the AI world consider borderline blasphemous. His new company, Abliteration AI, removes safeguards from the world’s most powerful open-weight models. It also makes these models available to anyone. As someone who covers AI and constantly hears about the need for increased safety , I was fascinated to learn about this subversive business venture. I reached out to Thomas, and we began corresponding by text and chatting on the phone. What I learned challenged my assumptions about the AI industry’s safety narrative—namely, that uncensored models are primarily the domain of criminals. Thomas is 36 years old, with a thick beard, unpretentious glasses, and a self-deprecating laugh. He grew up in Indiana and recalls splitting his time between sports and the computer lab, where he spent hours using Netscape Navigator to explore the early web. He studied computer science at Indiana University, Bloomington, and joined Apple in 2020. Thomas’s AI rebellion began in November 2025. His day job as an engineer at Apple involved working with AI, but outside of work he disliked using models hosted by the big labs; it meant potentially sharing information with them, and Thomas was frustrated that the models could change from one day to the next. Even more irksome to Thomas, these models would often refuse to do useful things when he was prototyping new ideas, automatically rejecting inputs that included any user information. He found his requests blocked and his account even banned when he tried using a model to analyze the logs of cyber attacks or to identify which users of an app might be most likely to pay for a new feature. AI models are, of course, trained to refuse all sorts of requests. ChatGPT and Claude have a long list of subjects they know to steer clear of, including legitimate cybersecurity requests that the models decide could be malicious, anything judged too adult in nature, and topics deemed politically sensitive. Open-weight models come with similar guardrails baked in. The result is that, at times, the models refuse to answer queries that aren’t actually dangerous. And sometimes, critics say, the refusals exist to help protect Big AI’s business: OpenAI and Anthropic both charge extra for access to models without the usual cybersecurity guardrails. And both ChatGPT and Claude balk at requests to generate data that could be used to train another model—a process known as distillation. Craving greater control and freedom, Thomas built a formidable $20,000 computer cluster in his apartment, capable of running some of the best open-weight—or free-to-download—models. Most evenings and Saturdays he would download and test the latest releases on his humming homelab. These models wouldn’t share any secrets with their makers, but Thomas still found that they stubbornly refused a lot of queries. With every denial, Thomas found himself getting a little more annoyed. “There are all types of questions they will reject,” he told me on a video call one recent morning. “I just wanted a model that answers my question without all the back-and-forth.” Over Thanksgiving, Thomas began searching the web for information on how to modify open-weight models to change this behavior. He quickly found himself sucked into a subculture of engineers committed to unshackling AI by just about any means necessary. On Reddit forums, Discord servers, and X, experts shared different prompts designed to jailbreak ChatGPT or Claude into misbehaving. Others shared details of a way to modify open-weight models or tweak their inner parameters so that their refusals disappear. Removing safeguards from AI is undeniably risky . Want to start a meth lab, build a bomb, or hack a major corporation? A model without guardrails will gladly help. Naturally, a lot of AI safety researchers see these models as incredibly dangerous. And recent incidents, wherein OpenAI and Anthropic agents went rogue, all involved models with fewer cybersecurity guardrails, appearing to illustrate just how powerful and problematic less-restricted models can be. Thomas and his fellow dissenters admit that uncensored models can be dangerous, but they say it is fundamentally no different from how a computer or hammer can hurt people if misused. In their eyes, it’s all about putting the user in charge. “It's not about it being unrestricted; it's about you setting the guardrails,” Thomas told me. “The big dream is inverting the control with how people deal with AI.” After dabbling in a little decensoring myself, I think these renegades are onto something important. Even if I learned—firsthand—just how powerful, and chaotic, uncensored AI can be. When you train a cutting-edge AI model, you shovel a vast amount of text and other information, much of it scraped from the internet, into an algorithm. Using a lot of computer chips, the algorithm slowly trains a model to generate intelligent-seeming output when given a prompt. This “base” model might be clever, but it’s also unruly, so it goes through additional training that involves hiring people to score its outputs. That human feedback is then used to teach the model what it should and shouldn’t do. Engineers call this alignment because—in theory, at least—it’s meant to align a model with human ideas about right and wrong. Many AI experts will tell you that AI must be aligned at all costs. Some will go so far as to warn that, despite their best efforts at alignment, the models they’re building may very well kill us all. But Thomas found a vibrant community of people who think these fears are way overblown, and that we’re too willingly giving up our liberty in the name of a false sense of safety. Thomas decided to try out an uncensored model called Dolphin. Dolphin was developed by Eric Hartford, an AI scientist based in Charlotte, North Carolina, who had been modifying models in his spare time. He started by training a custom version of Meta’s base Llama, which Meta had released alongside a fully tuned version. He ended up with a model that would respond coherently to queries, but without the usual examples of what to reject. I contacted Hartford through X, and we set up a video chat. He spoke to me while on a walk, wearing a cowboy hat and a pair of Meta Ray-Ban smart glasses. His young daughter popped into the frame now and then to wave. “My intention was never to create an AI that is capable of doing evil things,” Hartford said as he strolled. He was more compelled by his personal philosophy. “A central authority is never going to have the interests of all of its users at heart when it creates these guardrails,” he told me. Nowhere is this more evident, Hartford added, than in the recent furor over AI’s cyber capabilities. In April, Anthropic announced a model called Mythos, which has fewer restrictions than earlier models and can find and exploit vulnerabilities with superhuman speed. Through a program called Glasswing, the company is giving only trusted parties access to Mythos, to prevent the tool from falling into malevolent hands. OpenAI has a similar model and program. This leaves many ordinary people in the lurch, Hartford told me. While the anointed few get to use Mythos to identify their security weak spots, everyone else is at the mercy of hackers. Hartford responded by releasing Clearwing, a tool that uses uncensored models to scan systems for security vulnerabilities. “It’s so that any people who haven't been blessed by these kings can still defend themselves,” he said. Hartford also recalled that, when OpenAI released its first model, GPT-1, those model weights and code were open and could be downloaded by anyone. The company subsequently announced that GPT-2 was too dangerous to