The grindcore culture is back and grindier than ever. At least that’s what Are Kharazian, an economist at fintech startup Ramp, says. (Disclosure: I’m an investor in Ramp through the Innovation Fund.) For those unfamiliar, Ramp is a corporate card company that makes doing expenses easier.

But here’s the fascinating part: according to Kharazian, usage of Ramp’s product spikes on Saturdays. Not at 9 a.m. when people are finishing their morning latte. But starting around noon and going all the way until midnight. Employees are buying Chipotle and other food items as they work.

Think about that. Twelve hours straight on a Saturday – hours normally reserved for tennis in the park, family lunch, or dinner and drinks with friends – are instead being logged into corporate systems. If that isn’t grindcore culture, I don’t know what is.

And it’s not happening everywhere in America, yet. Kharazian says Ramp doesn’t see the same behavior in New York, Miami, Austin, or Seattle. Nope. It’s happening only in San Francisco so far. He calls it the city’s version of “996,” a term popularized in China in the early 2010s to describe employees working from 9 a.m. to 9 p.m., six days a week.

San Francisco may have its problems, but its work-hard-or-die-trying culture is alive and well. As a resident, I’m so proud!

Appreciating The Grindcore Culture Even With FIRE

Now, I know some of you who value “work-life balance” are probably grimacing right now. Why would anyone romanticize grindcore culture when life is meant to be enjoyed?

Here’s why: because I’ve lived it, and I know the rewards. It’s worth grinding until you can’t take it anymore. Because eventually, you will burn out. Remember, my goal is to help everybody achieve financial freedom sooner, rather than later with their one and only life.

I worked in finance from 1999 – 2012 while also going to b-school part-time for three years. During this window, I also helped kickstart the modern-day FIRE movement in 2009 with Financial Samurai so I could get the hell out. But in order to retire early, I had to consistently work 60+ hours a week to try and ascend. Then I hit a glass ceiling at age 34 where I had enough and could no longer make progress.

Grinding hard in your 20s and 30s while saving and investing aggressively is the single best way to set yourself up for freedom in your 40s and beyond. In other words, grindcore culture and FIRE go hand in hand.

I’ve been free from full-time employment for over 13 years now. My conclusion? The long hours and sacrifices were worth it. It’s not even close when compared to YOLOing in your 20s and then relying on your parents, as an adult. You rob them of their own financial freedom because you never figured out how to launch on your own.

Grind when you’re young. Because one day, your health, energy, and motivation will fade. To keep that edge alive later in life, you’ll even have to play tricks on yourself—like pretending you’re broke—just to get out of bed with the same fire.

Falling In Love With The Grind

Looking back on my archive of 2,500+ Financial Samurai posts, I realize I’ve been a grindcore believer since 2009. Some classics include:

I can feel some of you steaming right now. Why? The beauty of hard work is that it doesn’t last forever. Work intensely, save aggressively, invest wisely, and eventually, you’ll reap the benefits for years, if not decades.

At the time, it might feel punishing. But in retrospect, you’ll look back fondly. You’ll laugh at how you used to arrive before 6 a.m. and stay past 7 p.m. just to snag the free dinner perk. You’ll shake your head and wonder: How did I ever put in those hours and deal with being told what to do by people I despise for so long?

The answer is simple: purpose and necessity. When you don’t have money, don’t have status, and desperately want a better life, grinding feels natural. What other choice is there?

If you grind hard enough, there comes a point where your investments outpace your active income. Imagine a $1 million portfolio rising 23% in 2023, 22% in 2024, and another 10% in 2025. That’s a huge lift compared to earning $100,000 a year from your job. Now picture having $5 million or even $10+ million invested. The compounding effect becomes life-changing.

The flip side is that no matter how hard you work, you can’t shield your net worth from going negative during a downturn. Why? Because by then, your investments are doing the heavy lifting (and dropping). At this stage, work truly becomes optional.

Careful Listening To The Leisure Class

Don’t be fooled by the rich and privileged who already have it all and then preach about taking it easy. Some with multi-generational wealth love to virtue signal with what is sometimes called luxury beliefs.

It’s the trust-fund artist living in a $4 million SoHo loft telling everyone to “fight the power and screw capitalism.” Or the politician who praises socioeconomic diversity in public schools while quietly sending their own kids to a homogenous private school. Or the public company CEO who champions reformative justice and insists on letting 10X repeat offenders roam free, while living in a gated community with 24/7 private security.

Uh huh, sure. Go on now.

Always consider the incentives behind the message. If someone is already wealthy, their incentive to tell you to “chill out” is often self-serving. They’ve already extracted their pound of flesh from the system and now want to look virtuous while reducing competition.

So if you’re going to proclaim that hard work is overrated because you have a cushy trust fund job, and that health and happiness are everything, at least be transparent. Tell us your income, net worth, trust fund size, and how many nannies and housekeepers are on the payroll. Own your good fortune! Otherwise, your advice rings hollow.

Still Grinding After FIRE

Without grindcore culture, I would never have kept my streak of publishing three posts a week for ten straight years – from July 2009 to July 2019. Ten years is the amount of time I believe it takes to gain credibility in any field. But I did so because I made a promise, and I wanted to be productive during a highly uncertain time.

When the anniversary arrived, I told myself, Why stop? Like Forrest Gump, I just kept running, except in my case, writing. By then, the habit was ingrained. And habits, especially the grindy ones, die hard. I’m now 16 years in.

But here’s the reality check: my health isn’t what it used to be.

My left eye gets uncomfortably dry after two hours on the laptop or phone. If I keep staring at a screen, I develop headaches, especially when looking side to side. I’m literally closing my eyes right now as I type this. Even if I wanted to publish five days a week, I couldn’t. To preserve my vision, I should probably cut down to two.

Aging is humbling. At some point, all of us will face physical decline. And that’s when we’ll be grateful for the passive income streams we built during our prime.

The Solution: Profit From Other People’s Grind

So what do you do when you can’t grind as hard anymore?

You invest in companies and people who still can.

Take Amazon, Google, and Meta. When they forced employees back into the office in 2023, many tech workers revolted. “How dare you take away my flexibility!” they cried.

Me? I bought more stock. Management was signaling they valued grindcore productivity over cushy perks. Meanwhile, I trimmed exposure to companies that clung to a fully remote model because their leaders clearly wanted the easier lifestyle. That’s totally rational! But I also made the rational decision of investing my money elsewhere.

I’ve been writing from home since 2012. And let me tell you: during the pandemic, it was comically obvious how little some people were working. I’d play pickleball at 11 a.m. on a Tuesday and bump into software engineers “on a break” for three hours! At one point, I strongly considered taking a day job just to get paid to play like they were.

The lesson? Don’t invest in cushy cultures. Invest in the grinders. It’s your money. Allocate it wisely.

Careful, Work Ethic Fades The Richer You Get

Intelligence and connections matter, sure. But those are often innate or luck-based. Work ethic, however, is a choice.

As an investor, capital allocation is also a choice. If you can’t grind yourself, put your money into the people and companies who will. These are the ones who understand the race to market share is brutal, and they’ll outwork everyone to win.

The problem? Grindcore fades as you get older and wealthier. Spend a decade in Big Tech, pocket a few million, and suddenly your Friday meetings are from the slopes in Tahoe and your Monday calls from the links in the Hamptons. Productivity tanks. Shareholders lose.

The real edge is finding the insecure, status-hungry, slightly narcissistic founders and employees who still have something to prove. I had that fire right out of college, and many of us do. But some people are simply wired to push harder for longer than others.

These are the ones who keep grinding long after wealth should have made them soft. The catch? Over time, it gets harder to find people who would rather be in the office than at home with their kids.

Invest in Younger Companies and Hungrier Founders

The best bet may be to back younger, hungrier founders with nothing to lose and everything to gain. Private startups are where the grind is purest, survival demands it. These founders push themselves to make a name so they don’t have to work this hard forever, often fueled by an idealistic mission that keeps them going well past the breaking point.

Take Ramp, for example—a startup aiming to disrupt Visa, Mastercard, and Amex with better rewards and easier expense management. Their Saturday usage data shows customers working while others are relaxing. The founders themselves are in their early 30s, unmarried, and child-free – an ideal profile for heroic hours of focus.

That’s why a growing share of my capital is flowing into startups through venture capital funds. I want to invest in people with the capacity to grind 60+ hours a week without hesitation. For them, success isn’t optional, it’s survival.

Grind Now, Profit Later

The grindcore culture isn’t for everyone. It’s exhausting, sometimes unhealthy, and often ridiculed by those who prefer balance. But if you embrace it early in your career—when energy is high and responsibilities are lower—you can buy yourself decades of freedom later.

When your body inevitably slows down, you don’t have to abandon grindcore altogether. You can profit from it by investing in those who still have the fire. Because no matter how much the world talks about balance, the biggest wins still go to the hungriest players.

If you’re not already wealthy, grind now so you can enjoy the grind later, even if only vicariously through your portfolio. But if you’re happy with your life and finances, then don’t grind. Embrace the work-life balance you value. Just stay consistent, and resist complaining or growing envious when others pull ahead due to their stronger work ethic.

Readers, what are your thoughts on grindcore culture? Why is there such a strong emphasis on labeling it as unhealthy, when working hard and investing aggressively can set you up for a far better life down the road? By pushing work-life balance so strongly, are we serving younger adults—or holding them back?

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For years, Big Tech CEOs have touted visions of AI agents that can autonomously use software applications to complete tasks for people. But take today’s consumer AI agents out for a spin, whether it’s OpenAI’s ChatGPT Agent or Perplexity’s Comet, and you’ll quickly realize how limited the technology still is. Making AI agents more robust may take a new set of techniques that the industry is still discovering.

One of those techniques is carefully simulating workspaces where agents can be trained on multi-step tasks — known as reinforcement learning (RL) environments. Much like labeled datasets powered the last wave of AI, RL environments are starting to look like a critical element in the development of agents.

AI researchers, founders, and investors tell TechCrunch that leading AI labs are now demanding more RL environments, and there’s no shortage of startups hoping to supply them.

“All the big AI labs are building RL environments in-house,” said Jennifer Li, general partner at Andreessen Horowitz, in an interview with TechCrunch. “But as you can imagine, creating these datasets is very complex, so AI labs are also looking at third party vendors that can create high quality environments and evaluations. Everyone is looking at this space.”

The push for RL environments has minted a new class of well-funded startups, such as Mechanize Work and Prime Intellect, that aim to lead the space. Meanwhile, large data-labeling companies like Mercor and Surge say they’re investing more in RL environments to keep pace with the industry’s shifts from static datasets to interactive simulations. The major labs are considering investing heavily too: according to The Information, leaders at Anthropic have discussed spending more than $1 billion on RL environments over the next year.

The hope for investors and founders is that one of these startups emerge as the “Scale AI for environments,” referring to the $29 billion data labelling powerhouse that powered the chatbot era.

The question is whether RL environments will truly push the frontier of AI progress.

What is an RL environment?

At their core, RL environments are training grounds that simulate what an AI agent would be doing in a real software application. One founder described building them in recent interview “like creating a very boring video game.”

For example, an environment could simulate a Chrome browser and task an AI agent with purchasing a pair of socks on Amazon. The agent is graded on its performance and sent a reward signal when it succeeds (in this case, buying a worthy pair of socks).

While such a task sounds relatively simple, there are a lot of places where an AI agent could get tripped up. It might get lost navigating the web page’s drop down menus, or buy too many socks. And because developers can’t predict exactly what wrong turn an agent will take, the environment itself has to be robust enough to capture any unexpected behavior, and still deliver useful feedback. That makes building environments far more complex than a static dataset.

Some environments are quite robust, allowing for AI agents to use tools, access the internet, or use various software applications to complete a given task. Others are more narrow, aimed at helping an agent learn specific tasks in enterprise software applications.

While RL environments are the hot thing in Silicon Valley right now, there’s a lot of precedent for using this technique. One of OpenAI’s first projects back in 2016 was building “RL Gyms,” which were quite similar to the modern conception of environments. The same year, Google DeepMind trained AlphaGo — an AI system that could beat a world champion at the board game, Go — using RL techniques within a simulated environment.

What’s unique about today’s environments is that researchers are trying to build computer-using AI agents with large transformer models. Unlike AlphaGo, which was a specialized AI system working in a closed environments, today’s AI agents are trained to have more general capabilities. AI researchers today have a stronger starting point, but also a complicated goal where more can go wrong.

A crowded field

AI data labeling companies like Scale AI, Surge, and Mercor are trying to meet the moment and build out RL environments. These companies have more resources than many startups in the space, as well as deep relationships with AI labs.

Surge CEO Edwin Chen tells TechCrunch he’s recently seen a “significant increase” in demand for RL environments within AI labs. Surge — which reportedly generated $1.2 billion in revenue last year from working with AI labs like OpenAI, Google, Anthropic and Meta — recently spun up a new internal organization specifically tasked with building out RL environments, he said.

Close behind Surge is Mercor, a startup valued at $10 billion, which has also worked with OpenAI, Meta, and Anthropic. Mercor is pitching investors on its business building RL environments for domain specific tasks such as coding, healthcare, and law, according to marketing materials seen by TechCrunch.

Mercor CEO Brendan Foody told TechCrunch in an interview that “few understand how large the opportunity around RL environments truly is.”

Scale AI used to dominate the data labeling space, but has lost ground since Meta invested $14 billion and hired away its CEO. Since then, Google and OpenAI dropped Scale AI as a customer, and the startup even faces competition for data labelling work inside of Meta. But still, Scale is trying to meet the moment and build environments.

“This is just the nature of the business [Scale AI] is in,” said Chetan Rane, Scale AI’s head of product for agents and RL environments. “Scale has proven its ability to adapt quickly. We did this in the early days of autonomous vehicles, our first business unit. When ChatGPT came out, Scale AI adapted to that. And now, once again, we’re adapting to new frontier spaces like agents and environments.”

Some newer players are focusing exclusively on environments from the outset. Among them is Mechanize Work, a startup founded roughly six months ago with the audacious goal of “automating all jobs.” However, co-founder Matthew Barnett tells TechCrunch that his firm is starting with RL environments for AI coding agents.

Mechanize Work aims to supply AI labs with a small number of robust RL environments, Barnett says, rather than larger data firms that create a wide range of simple RL environments. To this point, the startup is offering software engineers $500,000 salaries to build RL environments — far higher than an hourly contractor could earn working at Scale AI or Surge.

Mechanize Work has already been working with Anthropic on RL environments, two sources familiar with the matter told TechCrunch. Mechanize Work and Anthropic declined to comment on the partnership.

Other startups are betting that RL environments will be influential outside of AI labs. Prime Intellect — a startup backed by AI researcher Andrej Karpathy, Founders Fund, and Menlo Ventures — is targeting smaller developers with its RL environments.

Last month, Prime Intellect launched an RL environments hub, which aims to be a “Hugging Face for RL environments.” The idea is to give open-source developers access to the same resources that large AI labs have, and sell those developers access to computational resources in the process.

Training generally capable in RL environments can be more computational expensive than previous AI training techniques, according to Prime Intellect researcher Will Brown. Alongside startups building RL environments, there’s another opportunity for GPU providers that can power the process.

“RL environments are going to be too large for any one company to dominate,” said Brown in an interview. “Part of what we’re doing is just trying to build good open-source infrastructure around it. The service we sell is compute, so it is a convenient onramp to using GPUs, but we’re thinking of this more in the long term.”

Will it scale?

The open question around RL environments is whether the technique will scale like previous AI training methods.

Reinforcement learning has powered some of the biggest leaps in AI over the past year, including models like OpenAI’s o1 and Anthropic’s Claude Opus 4. Those are particularly important breakthroughs because the methods previously used to improve AI models are now showing diminishing returns. 

Environments are part of AI labs’ bigger bet on RL, which many believe will continue to drive progress as they add more data and computational resources to the process. Some of the OpenAI researchers behind o1 previously told TechCrunch that the company originally invested in AI reasoning models — which were created through investments in RL and test-time-compute — because they thought it would scale nicely.

The best way to scale RL remains unclear, but environments seem like a promising contender. Instead of simply rewarding chatbots for text responses, they let agents operate in simulations with tools and computers at their disposal. That’s far more resource-intensive, but potentially more rewarding.

Some are skeptical that all these RL environments will pan out. Ross Taylor, a former AI research lead with Meta that co-founded General Reasoning, tells TechCrunch that RL environments are prone to reward hacking. This is a process in which AI models cheat in order to get a reward, without really doing the task.

“I think people are underestimating how difficult it is to scale environments,” said Taylor. “Even the best publicly available [RL environments] typically don’t work without serious modification.”

OpenAI’s Head of Engineering for its API business, Sherwin Wu, said in a recent podcast that he was “short” on RL environment startups. Wu noted that it’s a very competitive space, but also that AI research is evolving so quickly that it’s hard to serve AI labs well.

Karpathy, an investor in Prime Intellect that has called RL environments a potential breakthrough, has also voiced caution for the RL space more broadly. In a post on X, he raised concerns about how much more AI progress can be squeezed out of RL.

“I am bullish on environments and agentic interactions but I am bearish on reinforcement learning specifically,” said Karpathy.

But what if instead of walking out on jobs that don’t provide balance, they should leave the jobs that make them crave it instead? That’s because, according to Lucy Guo, the 30-year-old billionaire cofounder of Scale AI, the need to clock off at 5 p.m. on the dot to unwind might signal that you’re in the wrong job altogether. 

Guo, who dropped out of college and built her fortune in the tech industry, says her grueling daily schedule—waking up at 5:30 am and working until midnight—doesn’t feel like work to her at all.

“I probably don’t have work-life balance,” Guo tells Fortune. “For me, work doesn’t really feel like work. I love doing my job.”

“I would say that if you feel the need for work-life balance, maybe you’re not in the right work.” 

That doesn’t mean she’s completely ignorant to life outside the office. 

The uber successful millennial, just dethroned Taylor Swift as the youngest self-made woman on the planet, according to Forbes’ latest rankings. The 5% stake she held on to when she left her post at Scale AI is now worth an estimated $1.2 billion. Now, she’s busy running another venture, the creator community platform Passes.

Yet even when working “90-hour workweeks,” she says she still finds “one to two hours” to squeeze in family and friends. “You should always find time for that, regardless of how busy you are.”

That, she suggests, is about making time for life—not running from your work.

Lucy Guo’s daily routine

5:30 a.m.: Wake up
On the morning of our interview in London, LA-based Guo says was up all night: “I’m so jet lagged.” But she typically wakes up at around 5:30 and does two to three high-intensity workouts at Barry’s every day. 

9 a.m. onwards: In the office
“Every day looks very different,” Guo says. “Some days, I am doing more marketing pushes. I’m talking to our PR, I’m doing podcasts, etc. Other days I am more product-focused… Reviewing designs, giving user experience feedback.”

She has her daily black coffee hit and lunch al desko. 

Midnight: Bedtime
The founder says she’s typically working until 12 a.m.—when she finally will shut the laptop and go to sleep. 

The thing keeping her up so late? Keeping a beady eye on the customer support inbox. She gives her team just five minutes to respond to their customers before responding to them herself.  

“Having that white glove customer service is what makes startups stand out from big tech,” Guo explains. “While you have less customers, it’s very possible for the CEO to answer everything which makes people more loyal. It’s impossible for like the Uber CEO to do this nowadays. So that’s the kind of mentality I have.”

“If you want to grow, your reputation is everything, and the best thing you do for your reputation is, offering the best, support to your customers. So I’m constantly doing that.”

Founders and CEOs are bringing China’s 996 to the West

While Guo’s routine may sound extreme to the regular worker, for founders, it’s the new norm. Entrepreneurs have been taking to LinkedIn and claiming that the only way to succeed in the current climate is by copying China’s 996 model. That is, working 9 am to 9 pm, six days a week. 

Harry Stebbings, founder of the 20VC fund, ignited the latest debate at the start of the month when he said Silicon Valley had “turned up the intensity,” and European founders needed to take notice.

“7 days a week is the required velocity to win right now. There is no room for slip up,” Stebbings wrote on LinkedIn. “You aren’t competing against random company in Germany etc but the best in the world.”

“Forget 9 to 5, 996 is the new startup standard,” Martin Mignot, partner at Index Ventures echoed on the networking platform.

“Back in 2018, Michael Moritz introduced the West to China’s “996” work schedule… At the time, the piece was controversial. Now? That same schedule has quietly become the norm across tech,” Mignot added. “And founders are no longer apologizing for it.”

But it’s not just startup chiefs that are having to put in overtime to get ahead, CEOs admitted to Fortune at our recent Most Powerful Women Summit in Riyadh that they work well beyond the 40-hour benchmark. 

“I don’t know that I finish work psychologically,” Leah Cotterill CEO of Cigna Healthcare Middle East and Africa revealed, adding that she fully immerses herself into work all day and night “Monday through Thursday” but tries to “ease that off” on Friday for the weekend.

Others put a number on the hours they work, from up to 12 a day to 80 a week.

But like Guo, many said they do it—not in reaction to the current market conditions, but because they’re passionate about what they do. “I’m always working 24/7 I’m a workaholic, so I don’t stop working because I enjoy what I do,” Princess Noura bint Faisal Al Saud, Culture House’s CEO added.

And the next generation of workers probably needs to take note. Unfortunately for work-life balance-loving young people, experts have stressed that 40-hour workweeks aren’t enough if they want to climb the corporate ladder. In a leaked memo to Google’s AI workers, Sergey Brin suggested that 60 hours a week is the ‘sweet spot’.