오픈AI가 코딩 도구 코덱스(Codex)를 개조한 '챗GPT 워크(ChatGPT Work)'를 월 20달러 최저 구독권에서 제공하며, 회계사·투자자·의사 등 비개발자 직군으로 AI 에이전트 확산을 노립니다. 내부 직원 사용률은 98%에 달하지만 외부 조직 구독자는 17%, 개인 구독자는 1% 미만에 그쳐 확대가 과제입니다. 에이전트는 토큰 소비가 커 수익성도 높아, 오픈AI와 업계 전체에 중요한 승부처입니다.
번역된 본문
여러분은 자신의 디지털 삶에 대해 LLM(대규모 언어모델)에게 얼마나 많은 통제권을 넘길 의향이 있나? 모델에서 최대한의 가치를 얻으려면 열쇠를 넘겨야 한다. 통제에 민감하거나 AI를 꺼리는 사람에게는 그것이 상당한 부담으로 보인다. 하지만 오픈AI 데스크톱 앱 수석 엔지니어 앤드류 앰브로시노(Andrew Ambrosino)에게는 미래를 테스트하는 유일한 방법이다. 그래서 그 앱은 현재 그의 수신함, 슬랙 계정, 휴대폰, 노션(Notion)과 피그마(Figma) 같은 앱 등에 접근하고 통제한다.
“문서 작성을 요청할 때 그 주제와 관련된 비밀 DM(개인 메시지)에서 내용을 끌어와서, 일부 정보를 공유하면 안 된다는 것을 모를 가능성이 있나? 그렇다”고 앰브로시노는 테크크런치에 말했다. “업무를 위해 그렇게 하겠다. 필요하다면 개인적으로 손해를 감수할 것이다. 다행히 아직까지 그런 일은 없었다.”
앰브로시노는 지난달 출시되어 회사의 최저 구독 등급인 월 20달러로 이용 가능한 오픈AI의 가장 큰 승부수인 ‘챗GPT 워크(ChatGPT Work)’를 개발하고 있다. 이 제품은 화이트칼라 노동자들이 AI 에이전트를 활용하도록 하려는 것이다. 즉, 회계사, 투자자, 의사 등 일상이 컴퓨터에 지배되는 모든 이들이 사용하는 디지털 워크플로에 LLM을 연결하는 것이다. 오픈AI의 마케팅 문구는 목표를 간결히 정리한다: “인공지능이 질문에 답하는 것을 넘어 모두가 자신의 가장 큰 아이디어를 현실로 만들도록 돕는 세상.”
소프트웨어 개발자들에게는 이 전환이 이미 일어나고 있지만, 다른 부문으로 확산되는 것은 더뎠다. 챗GPT 워크는 회사의 코딩 도구인 코덱스(Codex)를 변형한 버전이다. 엔지니어가 아닌 사람들에게도 소프트웨어 엔지니어가 이미 에이전트로부터 얻는 것과 동일한 기능, 즉 단순히 질문에 답하는 것이 아니라 다단계 프로젝트를 스스로 완수하는 AI 도구를 제공하는 것이 목적이다.
“이 새로운 요소에서 챗GPT는 매우 복잡한 작업 전체를 만족스럽고 안전한 방식으로 완전히 자율적으로 수행할 수 있다”고 워크를 포함해 오픈AI의 핵심 제품 업무를 이끄는 티보 솔티오(Tibault Sottiaux)가 테크크런치에 말했다. “이것이 바로 오픈AI의 미션, 즉 모두를 함께 데려가는 것이다.”
상업적으로 이는 매우 중요하다. 더 오래 작동하는 에이전트는 더 많은 토큰을 소비하므로 사용자당 오픈AI에 더 수익성이 높다. 새로운 직업군에 도달하는 것은 오픈AI뿐 아니라 업계 전체에 결정적이다. 코딩이 AI 연구소들에게 수익성 있는 영역으로 입증됐다 하더라도, 이 회사들이 훈련과 컴퓨팅에 대한 막대한 투자를 정당화하려면 여전히 AI 도구가 지원해야 하는 전문 업무 중 극히 일부에 불과하다.
연구소들이 소프트웨어 엔지니어에 집중하는 동안, 법률 분야의 하비(Harvey)와 영업 분야의 클레이(Clay) 같은 수직 특화 경쟁사들은 모델 중립적 접근 방식, 즉 그 시점에 가장 잘 작동하는 AI를 무엇이든 연결하는 방식으로 이 고객들을 쫓아왔다.
업계 애널리스트들은 이를 오픈AI와 경쟁사들이 직면한 주요 과제 중 하나로 본다. “연구소들이 시장에서 AI를 확장하는 데 필요한 핵심 보완 자산을 신속히 확보하지 못하면, 가치는 다른 곳으로 쏠릴 것”이라고 크리스천 카탈리니(Christian Catalini)는 a16z의 ‘Time to Build’ 블로그에서 썼다.
소프트웨어 엔지니어가 아닌 사람들을 위해 AI 앱이 작동하게 하려면 더 많은 손잡아 이끌기가 필요하다. 커뮤니케이션팀과 재무팀 같은 오픈AI의 비엔지니어 직원들은 코덱스가 “그들에게 실제로 적대적이던 시기”에 사용하기 시작했다고 앰브로시노는 말했다. 코덱스는 코드에 대해 질문하고 “이 항목에 대한 diff(변경 사항)가 비어 있다”는 식으로 소프트웨어 변경용 기술 정보를 보여줬다는 것이다. “그래서 우리는 2월부터 지금까지 이를 더 범용적으로 만들기 시작했다.”
오픈AI의 지원을 받은 연구에 따르면 6월 기준 오픈AI 직원의 98%가 코덱스를 사용했지만, 기업 구독자의 17%, 개인 구독자의 1% 미만만이 이 에이전트 코딩 도구를 사용하고 있다. 회사 내부의 거의 완전한 채택과 외부의 미미한 채택 사이의 이 격차가 회사에 있어 도전이자 기회다. “사용자를 위해 더 많은 가치와 효용을 창출할수록, 사람들은 그 효용의 일부에 대해 더 많이 지불할 의사가 있을 것이며, 그것이 바로 우리가 지금까지 (성장해온 방식이다)”라는 것이다.
How much control are you willing to give an LLM over your digital life? Getting the most value from a model means giving it the keys. For a control freak or the AI hesitant, it seems like a lot. For Andrew Ambrosino, the lead engineer for OpenAI’s desktop app, it’s the only way to test the future, which is why that app now has access to, and control over, his inbox, his Slack account, his phone, apps like Notion and Figma, and more. “If I'm asking it to write a document, is there a possibility that it's going to pull from a private DM on that subject and not know that it's not supposed to share some info? Yes,” Ambrosino told TechCrunch. “I'll do it for the job. I will take the personal hit here and there if I have to. And I haven't had to.” Ambrosino works on OpenAI’s biggest bet, ChatGPT Work, which was released last month and is available on the company’s lowest subscription tier, for $20 a month. The product is intended to allow white collar workers to field AI agents – hooking LLMs up to the digital workflows used by accountants, investors, doctors and everyone else whose day-to-day is dominated by their computer. OpenAI’s marketing copy puts the goal succinctly: A world where “where [artificial] intelligence goes beyond answering questions to helping everyone turn their biggest ideas into reality.” For software developers, that shift is already happening, but it’s been slow to spread to other departments. ChatGPT Work is a modified version of the company’s Codex coding tool. It’s meant to give non-engineers a version of the same functionality that software engineers already get from agents: an AI tool that doesn’t just answer questions, but completes multistep projects on its own. “In this new factor, ChatGPT can actually do entire, very complicated tasks for you all autonomously in a way that is delightful and safe,” Tibault Sottiaux, who leads OpenAI’s core product work, including Work, told TechCrunch. “It's the very mission of OpenAI—to bring everyone along.” Commercially, that matters a lot. Agents that work for longer stretches burn through more tokens, which makes them more lucrative for OpenAI on a per-user basis. Reaching new professions is crucial – not just for OpenAI, but for the industry at large. If coding has proven lucrative territory for AI labs, it’s still a tiny subset of the professional work AI tools need to enable if these companies are to justify their massive investment in training and computation. While labs have been focused on software engineers, vertical-specific competitors like Harvey (for law) and Clay (for sales) have been chasing those customers with a model-agnostic approach, meaning they’ll plug in whatever AI works best at the time. Industry analysts see this as one of the major challenges facing OpenAI and its competitors. “If the labs cannot rapidly get ahold of the key complementary assets needed to scale AI in the market, value will accrue elsewhere,” Christian Catalini wrote on a16z’s Time to Build blog. Making the AI apps work for people who aren’t software engineers requires more hand-holding. OpenAI’s non-engineering workforce, like the communications and finance teams, started using Codex “at a time that it was actively hostile to them—asking them about code and showing them, ‘oh, you have an empty diff for this thing,’” Ambrosino said, referring to a technical readout meant for software changes. “So, we started to make it more general purpose between February and now.” An OpenAI-backed study found that in June, 98% of OpenAI employees were using Codex, but just 17% of organizational subscribers and less than 1% of individual subscribers were using the agentic coding tool. That difference between near total adoption inside the company and negligible adoption outside it is the challenge and opportunity for the company. “The more value and the more utility that we generate for users, the more they will be willing to also pay for some part of that utility, and that's how we've always seen ChatGPT as well,” Sottiaux said. “You sit there and you're like, ’of course I want to pay $20 bucks a month for this,’ because the value that you get is so much more.” How to make AI intuitive To understand that disconnect, it helps to understand what OpenAI’s engineers are building. Every LLM requires what engineers call a “harness”—the software wrapped around a model that decides what information it sees, what tools it can use, and how it presents its answers back to you. If you want that model to do stuff—to become an agent—the harness gives it tools and instructions for using them on long-term tasks. For developers, a command-line interface (CLI) that enabled LLMs to code was enough to change the way software was built and deployed. But most people aren’t using CLIs; there’s a reason Windows replaced DOS. An agentic product that goes beyond software engineering is “going to be something that plays with the messy world of your life and your tools and websites that were built in 1995 and never updated,” Ambrosino told TechCrunch, explaining that the experiences his team is building are vital to expanding access to useful AI. Consider apps like Claude Code and Codex: They unleashed “vibecoding” by abstracting away all the actual software writing, and letting users just tell the model what they want in a program. Now, OpenAI wants to make functionality found in tools like OpenClaw, which coders use to put LLMs to work, as easy as prompting. “Without these products in front of the model, experts would know how to get the same results, but you wouldn't get to a billion people using the thing,” Ambrosino said. That trade-off between what power users need and what mainstream adoption requires plays out in internal debates at OpenAI, where some employees argue that a button is unnecessary if users can just ask the model directly. “We push back on [that]— because it's very early,” Ambrosino said. “Discoverability matters in this phase, and at some point we won't have the button.” Work has a few more buttons for selecting projects and plugins, but it aims for the same magic box interface as other OpenAI products.He compares it to skeuomorphism, the fading practice of making digital tools look like the physical objects they replaced, like a calculator app made to look like a pocket calculator. “That stuff wasn't just cringe design. That actually helped get people into this [and] make the transition,” Ambrosino said. OpenAI wouldn’t say how many people used Work versus Codex, but the joint app is used by just 20 million people, compared to more than a billion users the company says are prompting ChatGPT online. Giving ChatGPT a license to skill For now, OpenAI is pitching this tool as best suited for routine, data-intensive coordination tasks. Its employees are setting up weekly metrics reports , for example, and making spreadsheets into planning tools . I’ve spoken to VCs using agents to assemble relevant communications and analysis about companies into investment memos, and ops teams spinning up bespoke dashboards and data visualizations. Sam Altman is using it to plan his vacations . One OpenAI engineer described asking the program to look at a Slack conversation about an engineering problem and “make some charts,” then receiving back a series of insightful plots. “There is a deluge of information for the average worker or employee of any of these companies, including myself,” Akshay Nathan, who leads the product engineering team at OpenAI, said. “We're actually quite limited by our ability to parse everything that's available to us, and then take action on it. That information lives in all these system records tools [like, Salesforce…the value of ChatGPT is you already have access to this, but now you truly have access to it.” This, then, could be the digital personal assistant that AI evangelists dream about. As with Claude Cowork or Perplexity AI browsing agent, ChatGPT Work links agents to your existing workspace