2 Sources
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Companies Are Making Claude and Codex Talk Like Cavemen to Stop AI's Soaring Costs
A senior OpenAI employee has contributed code to the project, simply called 'caveman.' Companies are deliberately making their AI tools speak like cavemen in an attempt to stop burning through AI tokens and curb their massive expenditure on AI, 404 Media has found. The tool turns the usually verbose outpost of LLMs like Claude Code, Codex, or Gemini into a much more to the point answer. Think less "you're right to push back, I was wrong," and more "Hulk smash." Use of the caveman plugin is in direct response to the skyrocketing and unpredictable cost of AI. As 404 Media previously reported, companies are scrambling to stop spending so much on AI, with consulting giant Accenture finding much of the "soaring token spend" is thanks to people using AI to convert PDFs to presentations. People using caveman include developers at OpenAI, Nvidia, and GitHub, according to the tool's creator. A senior OpenAI employee has even contributed code to the project, adding support for OpenAI's Codex tool.
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Companies Hope To Save On AI By Talking Like Cavemen
After training the likes of Claude to mimic intelligent human speech patterns, it's becoming more affordable to dumb these computers down The world of AI is ratcheting up costs all over the place. Consumer technology, computer parts and gaming are experiencing the hardware crunch, but if it makes you feel any better the AI firms aren't in the clear either. In recent weeks, many of the most popular AI firms have altered their subscription model from a flat rate to a per use one. It reflects the prohibitively expensive upkeep of these services and forcing many major companies who embraced AI to become more conservative. Some companies believe they've found a new solution to the rising costs: Make it talk like Tarzan. According to 404 Media, a new plugin is making the rounds at companies looking to reduce their token usage. In their report, staff at multiple companies, including OpenAI itself, have turned to 'Caveman,' which instructs the likes of Claude to talk less like SNL's Master Thespian and more like SNL's Caveman Lawyer. "I made Caveman back in early April because I was using Claude Code heavily and noticed a lot of my token spend was going to unnecessary prose," Caveman creator Julius Brussee tells 404, "pleasantries, hedging, transitions, and chatty language that does not really matter." With the plugin, responses that are often humanized, familiar and fishing for conversation by design are reduced to curt barks and grunts. Less friendly advice, more marching orders. Brussee attests that by reducing the IQ of AI, his token usage has reduced down some 65 percent. So much about AI feels like a metaphor wrecking havoc, but you can't help but laugh that after years of campaigning on the human-like intelligence of these chat bots, bean counting is forcing a frontal lobotomy. Much of the AI world and quest for investments has leaned heavily on pop cultural understandings of machine learning. They've gone to absurdist lengths to anthropomorphize language learning models. Now that the bottom line actually matters, things have rapidly changed in the space. Maintaining these AI services is prohibitively expensive, and none of the major firms have found a way to be naturally profitable. Earlier this year OpenAI shuttered Sora, their video generator bleeding a million a day, complicating an otherwise lucrative deal with Disney.
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Developers at OpenAI, Nvidia, and GitHub are using a 'caveman' plugin that strips verbose AI responses down to bare essentials. The tool, created by Julius Brussee, reduces token usage by 65% as companies scramble to curb rising AI costs. A senior OpenAI employee has even contributed code to the project, highlighting the industry's urgent need for cost-saving measures.

A growing number of companies are turning to an unconventional solution to tackle escalating AI costs: making their large language models communicate like cavemen. The tool, simply called 'caveman,' transforms the typically verbose responses from Claude, Codex, and Gemini into stripped-down, essential-only answers
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. Developers at OpenAI, Nvidia, and GitHub have adopted the caveman plugin, with a senior OpenAI employee contributing code to add support for OpenAI's Codex tool1
.Creator Julius Brussee developed the tool in early April after noticing that excessive token consumption was driving up his bills while using Claude Code. "I made Caveman back in early April because I was using Claude Code heavily and noticed a lot of my token spend was going to unnecessary prose," Brussee explained, citing "pleasantries, hedging, transitions, and chatty language that does not really matter"
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. By implementing simplified language output, Brussee reports achieving a 65 percent reduction in token usage2
. Instead of receiving friendly, conversational responses designed to mimic human interaction, users get direct, no-nonsense instructions that accomplish the same task with far fewer tokens.The adoption of cost-saving measures for AI reflects mounting financial pressure across the industry. In recent weeks, major AI firms have shifted from flat-rate subscription models to per-use subscription models, acknowledging the prohibitively expensive upkeep of these services
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. Consulting giant Accenture identified that much of the "soaring token spend" stems from mundane tasks like converting PDFs to presentations1
. The financial strain is real: OpenAI shuttered Sora, their video generator that was bleeding a million dollars a day, complicating what could have been a lucrative deal with Disney2
. None of the major firms have found a path to natural profitability, making tools that curb rising AI costs essential for survival.Related Stories
The caveman approach marks a stark reversal from years of efforts to anthropomorphize AI and showcase human-like intelligence. Companies invested heavily in making large language models sound conversational and empathetic, only to discover that this verbose output significantly inflates operational expenses. The fact that a senior OpenAI employee actively contributed to a tool that reduces their own models' verbosity signals how seriously the industry takes the need to reduce AI model token usage
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. As AI adoption spreads across enterprises, expect more companies to prioritize efficiency over personality. The trend suggests that future AI development may focus on delivering value with minimal computational overhead rather than maximizing human-like interaction. Watch for similar optimization tools to emerge as the industry grapples with the reality that maintaining conversational AI at scale remains financially unsustainable without significant innovation in how these systems operate.Summarized by
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