AI Tutor – Materials Science Specialist

OpenAI and Handshake launch Codex Creator Challenge for students. You get a month to use Codex, submit your project and possibly score ChatGPT Plus and up to $10,000 in API credits to keep building. - Editor-in-Chief Mar 26, 2026, 4:13 AM EDT OpenAI's developer team is turning thousands of student side projects and late-night experiments into something much bigger: a proper, global challenge to build with Codex, its new AI coding platform. Instead of just talking about AI on resumes, students are being nudged to ship real tools, apps, and websites - then show them off to employers who are actively hunting for people who can actually work with AI, not just hype it. At the heart of this push is the Codex Creator Challenge, a new competition announced by OpenAI Developers and powered by career platform Handshake. The premise is deceptively simple: if you are a currently enrolled university student in the United States or Canada, OpenAI will give you $100 worth of Codex credits so you can turn an idea into a working project - and then compete for prizes including up to $10,000 in OpenAI API credits and a year of ChatGPT Plus. The credits sit in your OpenAI account as usage credit (roughly 2,500 Codex credits), so you can try prompts, iterate, break things, and push the system as far as your imagination goes before you ever have to think about paying. The mechanics are straightforward but designed to mimic a real product cycle rather than a one-off hackathon. The challenge kicked off on March 24, 2026, and runs through April 30, 2026, giving students just over a month to ideate, build, and polish something they'd actually want to stand behind in front of employers. Finalists will be notified in early May and invited to a virtual showcase on May 20, where they'll have a three-minute slot to present their project live before winners are chosen and prizes awarded. For a lot of participants, that three-minute window may be the first time they pitch an AI product to an audience that looks a lot like the hiring managers they want to impress next. What's striking about Codex - and a big reason this challenge feels accessible - is that OpenAI and Handshake are very explicit: you don't need to be a traditional coder to get started. Codex is built to interpret natural language prompts and turn them into working code, handle common software tasks, and even refactor or debug existing codebases. On the student side, that shifts the skill requirement from "I know four programming languages" to "I know how to describe a problem clearly, iterate on prompts, and understand whether the output is good enough to ship." For non-CS majors - design, business, humanities - this is almost an invitation to skip the gatekeeping and go straight to building something tangible. Handshake and OpenAI are also doing a lot of hand-holding to remove friction at the very beginning. Eligibility runs through a verification step (OpenAI uses student verification to ensure participants are currently enrolled at a degree-granting university in the US or Canada), but once that's done, you gain access to both the Codex credits and a growing ecosystem of onboarding resources. Handshake is positioning this as more than just a giveaway: there are live events, tutorials, and examples designed to help even complete beginners go from "I've never shipped software" to "I have a working AI-powered side project I can link on my profile." The examples they highlight are deliberately grounded in daily student life. One prompt: build a tool you wish existed to manage your day-to-day routine - think automated time-blocking assistants, habit trackers powered by AI, or bots that coordinate group projects and deadlines for you. Another idea is a course registration planner that factors in not just class times, but commuting, part-time work, clubs, and downtime, all balanced by a Codex-driven scheduler that can reason about constraints more flexibly than a static timetable. Other suggestions include building a personal website that actually feels dynamic - maybe with AI-generated case studies, interactive demos, or live portfolio search - or a "study sidekick" that converts messy lecture notes into flashcards, summaries, or quick-hit study guides on demand. Underneath the marketing, there's a clear labor-market story. Across tech and non-tech roles alike, demand for AI skills has shot up dramatically since generative AI hit the mainstream. Research based on job-posting data shows that roles requiring AI skills more than doubled within a year in some markets, with postings mentioning generative AI, prompt engineering, and tools like ChatGPT growing at triple-digit rates. By 2025, AI skills were appearing in vastly more job descriptions across software, marketing, data roles, and even traditionally non-technical fields such as sales and chemistry, and workers with AI knowledge were already seeing significant pay and opportunity premiums. The message baked into the Codex Creator Challenge is that the fastest way to convert "I used ChatGPT once" into something an employer respects is to ship a concrete project that demonstrates those skills in context. Handshake, which already sits in the middle of early-career recruiting for over a million employers, is using its new AI showcase to turn these Codex projects into visible signals for recruiters. Students are encouraged to attach what they build directly to their Handshake profiles, essentially turning the challenge into a structured way to produce portfolio pieces, not just one-off contest entries. For employers faced with hundreds of similar resumes, a live Codex-powered study assistant or workflow bot is instantly more interesting than a generic line that says "familiar with AI tools." The prize structure is also tuned toward ongoing experimentation rather than a single big payday. A year of ChatGPT Plus and up to $10,000 of OpenAI API credits is less like a scholarship and more like a runway: it gives student teams a budget to keep running their apps, test new features, and potentially onboard users long after the challenge ends. In practice, that could turn a class-project-style prototype into a subscription study app, a niche scheduling startup, or a productivity tool for a specific community on campus. Even if nothing becomes a full-blown company, participants walk away with hands-on experience integrating AI into real workflows - experience that is increasingly hard to fake in job interviews. Culturally, OpenAI Developers have been very open about the tone they want students to bring into the competition. In posts announcing the challenge, they lean into the chaos of early experimentation: "Try new tools. Have fun. Break things. Repeat," as one social media teaser framed it, with the $10,000 API credit pool presented less as a prize pot and more as a booster pack for the most ambitious builders. That vibe matters; it reframes AI experimentation not as a high-stakes, perfection-only exercise, but as a sandbox where rough ideas are welcome - as long as they're real, testable, and grounded in actual user needs. There's also a broader educational undercurrent here. Universities have been scrambling to figure out how to teach AI: whether to ban tools like ChatGPT, embrace them, or redesign curricula around them. This program quietly sidesteps that debate by going straight to students: if your institution is slow to adapt, you can still build the skills employers now expect, on your own time and with official backing from one of the most visible AI labs in the world. For some students, the Codex Creator Challenge will look less like a contest and more like an independent course in applied AI - one where the final exam is a working product rather than a written test. For now, the opportunity is tightly scoped: currently enrolled university students, verification required, with the geographic limitation to the United States and Canada. But it fits into a broader pattern of AI providers courting the next generation of builders early, before they've picked long-term tools, stacks, or employers. If the Codex Creator Challenge succeeds, it won't just produce a handful of prize-winning apps; it will graduate a cohort of students who can say, with receipts, that they know how to ship with AI - exactly the kind of line that tends to stand out when your application lands in a hiring manager's overflowing inbox.

AI data labelling startup Handshake has acquired Cleanlab, a data label auditing company, in a talent-focused deal. The acquisition adds nine Cleanlab employees, including three MIT PhD co-founders Curtis Northcutt, Jonas Mueller and Anish Athalye, to Handshake's research organisation. Founded in 2021, Cleanlab had raised $30 million from investors including Menlo Ventures and Bain Capital Ventures. The startup developed algorithms that flag incorrect data without human reviewers. Cleanlab received acquisition interest from multiple AI data labelling companies but chose Handshake because competitors like Scale AI and Surge use Handshake's platform to source human experts. Handshake, valued at $3.3 billion in 2022, serves eight major AI labs including OpenAI and is targeting annualized revenue in the "high hundreds of millions" this year.