Anthropic Cofounder Tom Brown’s 5 Career Tips

Tom Brown was one of the first 20 employees at OpenAI. Less than a decade prior, he was scoring a B- in his linear algebra course.

Brown hopped between startups — many backed by accelerator Y Combinator — before landing at OpenAI and later cofounding Anthropic.

Brown shared with Business Insider over email his 5 career advice tips after speaking about his career journey on YC’s “Lightcone Podcast,” in which he explained how he self-studied and networked his way into AI.

One of Brown’s early jobs was at Grouper, an app that helped coordinate group dates. Grouper had an early fan in Greg Brockman, the cofounder and president of OpenAI.

“He had a phase at Stripe where he would post in their thing, ‘I’m going on Grouper, who’s going?’ for a whole year,” Brown said. “I ended up being close with Greg, which ended up being my connection at OpenAI.”

In a follow-up email to Business Insider, Brown expanded on the importance of networking, the skill that got him his connection to Brockman.

“Surround yourself with people you want to be like,” Brown wrote. “You’ll become more similar to them over time.”

He also espoused the value of mentorship: “When learning, it’s much easier if you have a mentor or two and a group of friends learning alongside you,” Brown wrote.

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Before ChatGPT launched and AI began to crop up in consumer products, working with large language models maintained a sheen of intellectualism — one Brown worried he didn’t possess.

“It seemed at the time that you needed to be top superstar to try to help out at all,” he said on the podcast. “So I had a lot of uncertainty about whether I would be able to help.”

Brown said that it took “courage” to make the switch and dive into learning about AI research. He said he needed six months of self-study to feel like he wouldn’t “be a drag on them.”

Therein lies another one of Brown’s career tips, which he shared with Business Insider: know how to be helpful.

“Contact people doing the work you want to do and explain your plan for helping them,” he wrote. “They usually want help and will give you feedback on your approach.”

Brown also shared over email some of the resources he used during his six-month self-study period. He recommended “Linear Algebra Done Right” by Sheldon Axler, as well as the Google DeepMind e-book “How to Scale Your Model.” He also found the career change service 80,000 Hours useful.

On the podcast, Brown referenced some more self-study tools. He took Coursera courses and solved Kaggle projects. He also used a YC alum credit to buy a GPU.

After his heads-down voyage into AI research, he reached out to Brockman monthly asking for work.

“I messaged Greg as soon as OpenAI was announced, and I was like, ‘I’d love to help out in some way. I got a B- in linear algebra, but I know some engineering. I’ve done a bit of distributed systems work if you guys need help. I’m happy to mop floors if you guys need. I want to help out however,'” Brown recalled.

Eventually, Brockman put him on a gaming project at OpenAI. Brown said it was nine more months until he worked on anything in machine learning.

In 2021, Brown left OpenAI with Dario, Daniela Amodei, and others to cofound Anthropic.

Brown cautioned that he didn’t think that his method back then was translatable to the current AI market: “I don’t think it’s the right plan now for people, too, like this was 2015,” he said.

But he did have some advice for the young AI hopefuls.

“Taking more risk is wise, and then also trying to work on stuff where your friends would be really excited and impressed if you did it, or a more idealized version of yourself would be really proud if you succeeded at it,” he said.

In his email to Business Insider, Brown suggested that young people get right to work.

“The best way to get good at something is usually by doing it directly,” Brown wrote. “Try doing it first, then see where you fail. That will show you where you need to practice.”

And, to help cushion those fails, Brown had a word of wisdom: “Keep your personal expenses low.”