I'm a software engineer who spent nearly 7 years at Twitter before joining OpenAI. Here's how I got hired and why I love it.
I was working at Twitter for almost seven years and was looking for a change in general. Twitter was a big tech company, and it was handling millions of users already. I wanted to join a company that was a bit smaller scale and work in a startup-like environment.
When ChatGPT launched, software engineers were in awe. So I was already using it before joining OpenAI. I was fascinated by the product itself. There was definitely that connection with the product that, as a software engineer, you often don't feel.
I could also see there was a huge opportunity and huge impact to be created as part of joining OpenAI in general. And I think if I look back at the past two years of my journey, I think that's mostly true. It's been exciting seeing the user base grow over two years. I got to work and lead some critical projects, which was really great for my own professional development.
And you're always working with smart people. OpenAI hires probably the best talent out there. You're contributing while also learning from different people, so there's exponential growth in your professional career as well.
Building up the right work experience is key
My career at Twitter and before that had been focused on infrastructure capabilities and handling large-scale distributed systems, which was something the team was looking for when I interviewed with OpenAI.
When I joined OpenAI, there were a lot of challenges with respect to scaling infrastructure. So my expertise has helped steer some of those challenges in the right direction. Having that relevant experience helps when you're interviewing for any team. So one of the best things is to find the right team that has the closest match for you.
Having public references, for me, helped. I had some discussions and conference talks and met a lot of people as part of that conference networking. That also helps you stay on top of state-of-the-art technological advancements, which helps in whatever work stream you're working with.
I think OpenAI is probably one of the fastest-growing companies in the world, so you really need to move fast as part of that environment. You're shipping, or delivering, daily or weekly. And as part of that, I think you really need to have that cultural fit with the company. When you're interviewing, I think you need to be passionate about working at OpenAI and solving hard problems.
In general for professionals, it's important to have a good career trajectory so that they can showcase how they have solved real, hard problems at a large scale. I think that goes a long way.
Starting your career at a startup or a larger tech company are both fine. It's up to the students' interests and cultural fit as well. OpenAI is not just a place for experienced engineers. OpenAI also hires new grads and interns. I've definitely seen people entering as part of that pipeline. And it's amazing to see how they enjoy working at OpenAI and how they come up with new ideas and new capabilities and new suggestions.
But whichever place you end up in, I think it's important to have good growth aspects professionally and also for you to ship products. At any company you can create impact for the company and yourself, and be able to have that career trajectory.
OpenAI still feels like a startup
One of the most exciting things is that I think OpenAI still operates like it operated two years ago. It still feels like a startup, even though we may have scaled the number of engineers, number of products, the number of user bases.
It's still very much like a startup environment and there's a big push for productivity and collaboration. The velocity and the productivity you get working at OpenAI is definitely much higher than some of the other companies that I've worked with.
That makes things really exciting because you get to ship products on a continuous basis, and you get into that habit of shipping daily rather than weekly or monthly or yearly.
It feels great to be working in AI right now. In addition to having a connection with the product, it makes things very interesting when you are able to work from within the company, shaping the direction of a product that will be used by the entire world.
With GPT-5, for instance, we had early access to it and could steer the direction of its launch. Every engineer is empowered to provide feedback that will help improve the model, add new capabilities, and make it more usable and user-friendly for all the different 700 million users out there. I think that's pretty amazing and speaks to the kind of impact you can make as part of the company.
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This Year Will Be the Turning Point for AI College
A college senior returning to classes this fall has spent nearly their entire undergraduate career under the shadow—or in the embrace—of generative AI. ChatGPT first launched in November 2022, when that student was a freshman. As a department chair at Washington University in St. Louis, I witnessed the chaos it unleashed on campus. Students weren't sure what AI could do, or which uses were appropriate. Faculty were blindsided by how effectively ChatGPT could write papers and do homework. College, it seemed to those of us who teach it, was about to be transformed. But nobody thought it would happen this quickly. Three years later, the AI transformation is just about complete. By the spring of 2024, almost two-thirds of Harvard undergrads were drawing on the tool at least once a week. In a British survey of full-time undergraduates from December, 92 percent reported using AI in some fashion. Forty percent agreed that 'content created by generative AI would get a good grade in my subject,' and nearly one in five admitted that they've tested that idea directly, by using AI to complete their assignments. Such numbers will only rise in the year ahead. 'I cannot think that in this day and age that there is a student who is not using it,' Vasilis Theoharakis, a strategic-marketing professor at the Cranfield School of Management who has done research on AI in the classroom, told me. That's what I'm seeing in the classes that I teach and hearing from the students at my school: The technology is no longer just a curiosity or a way to cheat; it is a habit, as ubiquitous on campus as eating processed foods or scrolling social media. In the coming fall semester, this new reality will be undeniable. Higher education has been changed forever in the span of a single undergraduate career. 'It can pretty much do everything,' says Harrison Lieber, a WashU senior majoring in economics and computer science (who took a class I taught on AI last term). As a college student, he told me, he has mostly inhabited a world with ChatGPT. For those in his position, the many moral questions that AI provokes—for example, whether it is exploitative, or anti-intellectual, or ecologically unsound—take a back seat to the simple truth of its utility. Lieber characterized the matter as pragmatic above all else: Students don't want to cheat; they certainly don't want to erode the value of an education that may be costing them or their family a small fortune. But if you have seven assignments due in five days, and AI could speed up the work by tenfold for the cost of a large pizza, what are you meant to do? In spring 2023, I spoke with a WashU student whose paper had been flagged by one of the generally unreliable AI detectors that universities have used to stem the tide of cheating. He told me that he'd run his text through grammar-checking software and asked ChatGPT to improve some sentences, and that he'd done this to make time for other activities that he preferred. 'Sometimes I want to play basketball,' he said. 'Sometimes I want to work out.' His attitude might have been common among large-language-model users during that first, explosive year of AI college: If a computer helps me with my paper, then I'll have more time for other stuff. That appeal persists in 2025, but as these tools have taken over in the dorms, the motivations of their users have diversified. For Lieber, AI's allure seems more about the promise of achievement than efficiency. As with most students who are accepted to and graduate from an elite university, he and his classmates have been striving their whole life. As Lieber put it, if a course won't have 'a tangible impact on my ability to get a good job,' then 'it's not worth putting a lot of my time into.' This approach to education, coupled with a ' dismal ' outlook for postgraduate employment, justifies an ever more ferocious focus on accomplishment. Lieber is pursuing a minor in film and media studies. He has also started a profitable business while in school. Still, he had to network hard to land a good job after graduation. (He is working in risk management.) Da'Juantay Wynter, another rising senior at WashU who has never seen a full semester without AI, told me he always writes his own essays but feels okay about using ChatGPT to summarize readings, especially if he is in a rush. And like the other students I spoke with, he's often in a rush. Wynter is a double major in educational studies and American-culture studies; he has also served as president of the Association of Black Students, and been a member of a student union and various other campus committees. Those roles sometimes feel more urgent than his classwork, he explained. 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Whether or not this is realistic, students have internalized the message that they should be racking up more achievements and experience: putting in clinical hours, publishing research papers, and leading clubs, for example. In response, they seek ways to 'time shift,' Abdelmoity said, so they can fit more in. And that's at an elite private university, he continued, where the pressure is high but so is the privilege. At a state school, a student might be more likely to work multiple jobs and take care of their family. Those ordinary demands may encourage AI use even more. In the end, Abdelmoity said, academic-integrity boards such as the one he sits on can only do so much. For students who have access to AI, an education is what you make of it. If the AI takeover of higher ed is nearly complete, plenty of professors are oblivious. It isn't that they fail to understand the nature of the threat to classroom practice. 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The truth is that many professors would like to make this change but simply can't. A lot of us might want to judge students on the merits of their participation in class, but we've been discouraged from doing so out of fear that such evaluations will be deemed arbitrary and inequitable —and that students and their parents might complain. When professors take class participation into account, they do so carefully: Students tend to be graded on whether they show up or on the number of times they speak in class, rather than the quality of what they say. Erin McGlothlin, the vice dean of undergraduate affairs in WashU's College of Arts & Sciences, told me this stems from the belief that grading rubrics should be crystal clear in spelling out how class discussion is evaluated. For professors, this approach avoids the risk of any conflicts related to accommodating students' mental health or politics, or to bureaucratic matters. 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NBC News
4 hours ago
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Criminals, good guys and foreign spies: Hackers everywhere are using AI now
This summer, Russia's hackers put a new twist on the barrage of phishing emails sent to Ukrainians. The hackers included an attachment containing an artificial intelligence program. If installed, it would automatically search the victims' computers for sensitive files to send back to Moscow. That campaign, detailed in July in technical reports from the Ukrainian government and several cybersecurity companies, is the first known instance of Russian intelligence being caught building malicious code with large language models (LLMs), the type of AI chatbots that have become ubiquitous in corporate culture. Those Russian spies are not alone. In recent months, hackers of seemingly every stripe — cybercriminals, spies, researchers and corporate defenders alike — have started including AI tools into their work. LLMs, like ChatGPT, are still error-prone. But they have become remarkably adept at processing language instructions and at translating plain language into computer code, or identifying and summarizing documents. The technology has so far not revolutionized hacking by turning complete novices into experts, nor has it allowed would-be cyberterrorists to shut down the electric grid. But it's making skilled hackers better and faster. Cybersecurity firms and researchers are using AI now, too — feeding into an escalating cat-and-mouse game between offensive hackers who find and exploit software flaws and the defenders who try to fix them first. 'It's the beginning of the beginning. Maybe moving towards the middle of the beginning,' said Heather Adkins, Google's vice president of security engineering. In 2024, Adkins' team started on a project to use Google's LLM, Gemini, to hunt for important software vulnerabilities, or bugs, before criminal hackers could find them. 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The shift is only starting to catch up with hype that has permeated the cybersecurity and AI industries for years, especially since ChatGPT was introduced to the public in 2022. Those tools haven't always proved effective, and some cybersecurity researchers have complained about would-be hackers falling for fake vulnerability findings generated with AI. Scammers and social engineers — the people in hacking operations who pretend to be someone else, or who write convincing phishing emails — have been using LLMs to seem more convincing since at least 2024. But using AI to directly hack targets is only just starting to actually take off, said Will Pearce, the CEO of DreadNode, one of a handful of new security companies that specialize in hacking using LLMs. The reason, he said, is simple: The technology has finally started to catch up to expectations. 'The technology and the models are all really good at this point,' he said. Less than two years ago, automated AI hacking tools would need significant tinkering to do their job properly, but they are now far more adept, Pearce told NBC News. Another startup built to hack using AI, Xbow, made history in June by becoming the first AI to climb to the top of the HackerOne U.S. leaderboard, a live scoreboard of hackers around the world that since 2016 has kept tabs on the hackers identifying the most important vulnerabilities and giving them bragging rights. Last week, HackerOne added a new category for groups automating AI hacking tools to distinguish them from individual human researchers. Xbow still leads that. Hackers and cybersecurity professionals have not settled whether AI will ultimately help attackers or defenders more. But at the moment, defense appears to be winning. Alexei Bulazel, the senior cyber director at the White House National Security Council, said at a panel at the Def Con hacker conference in Las Vegas last week that the trend will hold, at least as long as the U.S. holds most of the world's most advanced tech companies. 'I very strongly believe that AI will be more advantageous for defenders than offense,' Bulazel said. He noted that hackers finding extremely disruptive flaws in a major U.S. tech company is rare, and that criminals often break into computers by finding small, overlooked flaws in smaller companies that don't have elite cybersecurity teams. AI is particularly helpful in discovering those bugs before criminals do, he said. 'The types of things that AI is better at — identifying vulnerabilities in a low cost, easy way — really democratizes access to vulnerability information,' Bulazel said. That trend may not hold as the technology evolves, however. One reason is that there is so far no free-to-use automatic hacking tool, or penetration tester, that incorporates AI. Such tools are already widely available online, nominally as programs that test for flaws in practices used by criminal hackers. If one incorporates an advanced LLM and it becomes freely available, it likely will mean open season on smaller companies' programs, Google's Adkins said. 'I think it's also reasonable to assume that at some point someone will release [such a tool],' she said. 'That's the point at which I think it becomes a little dangerous.' Meyers, of CrowdStrike, said that the rise of agentic AI — tools that conduct more complex tasks, like both writing and sending emails or executing code that programs — could prove a major cybersecurity risk. 'Agentic AI is really AI that can take action on your behalf, right? That will become the next insider threat, because, as organizations have these agentic AI deployed, they don't have built-in guardrails to stop somebody from abusing it,' he said.
