9-9-6: What is Means and Why Everyone is Talking About It

Live, not from Schenectady, New York. It's the Metrics Brothers, Growth and CAC.

But I'm still Growth, better known as Ray Reich, founder and CEO of Benchmarkit.

And I'm still CAC, better known as Dave Kellogg, EIR at Balderton Capital, independent consultant— easy for me to say— and the author of Kellogg.

And together we are the Metrics Brothers.

And we go together like the parts of an English breakfast, Ray.

Ah, eggs, tomatoes, sausage, black pudding, baked beans, mushrooms. You must be in London again, huh, Kaq? And by the way, my taxi driver told me this in Dublin. What in the heck is black pudding anyway?

Well, yes, I am in London, Growth Brother Ray. And no, you don't want the answer to that question. So I believe you also are on the road here, judging by us both wearing headsets, doing the grind in the land of Guinness and Jameson. Is that correct?

Yeah, you are much better than English breakfast, but I'm having a great time here at SAS Stock in Dublin where I just presented in their finance track a session on private SaaS benchmarks versus public SaaS benchmarks versus AI software benchmarks. It was fun.

Awesome. Well, speaking of topics, let's talk about today's topic. We're going to do another episode on kind of work ethic broadly defined following our recent episode on Grind Score, the new work-life balance to Company Culture Outlook Metric. Easy for me to say because this topic is very topical today. Specifically, we're going to talk today about 996, what it means, why people are talking about it, what happened as a result of my recent Topline newsletter contribution that included a discussion of 996, and more.

Well, before we get into 996, let's hear a word from our sponsor. The Metrics Brothers is proudly sponsored by Benchmarkit, the B2B AI and software industry's largest, broadest, and most contextualized benchmarking index. Dave Kellogg and Ray Grothright have put the Metrics Brothers podcast on hiatus for the remainder of 2026. All episodes we have ever recorded are still available on your favorite podcasting app. You can reach Dave @Kellogg and Ray on LinkedIn @RayReich. Thank you so much for listening to the Metrics Brothers podcast. Okay, Dave, what is 996?

Okay, for those who've not been paying attention to their social media channels because it's getting a lot of coverage in social media these days, 996 is shorthand for— first of all, it's about work Ethos, I'd say, more than work ethic. And this is shorthand for 9 a.m. to 9 p.m. So work 12-hour day. Those are the 2 9s. Work from 9 a.m. to 9 p.m., 6 days a week. So, it's basically shorthand, I would say, for kind of grind culture. Like, are you grinding? Are you working hard? Hey bro, are you 996-ing it? Right? So, that's the colloquial usage.

Well, I love it. It says you should be working 72 hours a week. And it made me actually think about that. I think this term originated in China and actually became popular at first when Jack Ma, who was the, you know, founder of Alibaba, in 2019 he actually said 996 was a blessing, and he received so much backlash from the younger generation.

So I did not know that, Ray. That is, uh, I've learned something already on today's episode. I thought VCs kind of invented it, but—

Well, speaking of that, beyond Jack Ma talking about it first in 2019, who's talking about it today mostly?

Well, look, you see a lot today in the tech media. They're certainly writing all this, TechCrunch and the various blogs out there writing about it. Certain thought-leading VCs, either for or against, by the way.

Do you think it's kind of a way for startup founders almost guilt-shaming employees? Hey, you've got to grind if you want to be part of a successful company.

Yeah, look, I think there's an underlying point here. Certainly, look, I think the reason it's so controversial is I think as soon as you say the word 996, some people think you're saying, thou shalt work 996 or thou art a bad employee. And that certainly is controversial. It's certainly not what I'm saying. But it's what a lot of people hear when they hear the term. And look, I think the reason— but the question is not— it's less about what the term means and like, why are we talking about it? And the reason we're talking about it, in my opinion, is that we're at the start of a major industry disruption cycle. caused by AI. These cycles happen, if you're lucky, 2, maybe 3 times in your career. Like, they're once every 20-year things. Ray and I both hit one with client-server, I'd say, in the '80s, with the internet in the 2000s. And now I think we're hitting our third one, which is AI here in the mid-2020s. So, and when these cycles hit, they're very, very important. And if there ever were a time to grind 996, It's at the start of one of these cycles.

But yeah, and I'll tell you, Dave, it reminds me of the culture back in the, you know, that dot-com era. And I was at Netscape and I was leading the e-commerce group there. And I remember we had this new product. It was a sell-side e-commerce product. And we had a client signed up that said, hey, if you can deliver it by X date, I'm going to pay you. It was a 7-figure deal. So, we had a team of 37 engineers, product managers, and Little old me, we spent 37 days in a row, night and day, to get this product out. And at the time, it wasn't about Jim Barksdale or anyone saying, you've got to work, you know, 7 days a week to do this. It was the team kind of esprit de corps, like, we want to do this. We're changing the world. And I look back on it with very fond memories, even though at the time, it was exhausting, Dave.

Okay, well, that's an interesting story, Ray. I'm not sure it was 37 engineers for 37 days. Is it really 37 squared, Ray?

Oh, thank you for calling me out. It was a team of about 8 to 10 people, Dave.

Okay, got it. I was like, I think that's unlikely.

No, 8 to 10.

So Ray did the grind back in the day. And look, the reason, again, the reason we're talking about this at all is because people who kind of are paying attention get that these disruptions first come very infrequently, right, on the order of every 20 years. And when they come, they create the opportunity to create kind of generational leading companies that can be worth tens to hundreds of billions of dollars. So, they create new enduring leaders that are hard to dislodge, right? So, we all remember, not all of us, but many of us remember the internet bubble. And there was wreckage everywhere. There were startups going out of business left and right in the early 2000s. And from the wreckage of the internet bubble and Webvan and Pets.com and 100 other dot-coms sprung eBay, Amazon, Google, Salesforce, right? So, that's the reason people are so excited right now. That's the reason that many people are working so hard right now because they're realizing, wait a minute, it's 1999 and we're at Google, which I think was founded actually in 2000. But we're in 1999 and we work at Amazon. This is a chance to create a generational leader in e-commerce. So, that's actually the driving trend here. It's not an overreaction to COVID and just going, oh, we don't think anyone's working hard enough. Get back into the office. This is not about that, in my opinion.

No, it's defining the next era of software. And I still remember, once again, when I was in the middle of this during that internet era, our CEO said, you know, we're here trying to do something very, very special. But if you can't run with the big dogs, go ahead and stay off the porch.

Okay, there you go. That'll be in the episode summary, right?

So, but is this really just about working hard?

So look, I don't think the 996 message is go work hard. I think the message is go work hard because these are critical times. And the thing I'd add to it is it doesn't apply automatically to all startups and markets. To me, this applies specifically to what I'm going to call winner-take-all Or winner-takes-most, because there is some gray here, markets. And the point actually isn't, at least my point is not work hard. I don't care how hard you work. I never ask founders how hard they work. It's to win. The reason you want to work hard is because working hard is one of the things one should do if you want to win in one of these greenfield winner-take-all markets. And that's why this is so topical. And that's why I have— look, my position is confused on this per the little mini drama around my Topline newsletter contribution, where it was kind of asserted that I was saying, oh, everyone go work 996, which is not what I was saying. I was saying, if you're in this situation, in a winner-take-all greenfield market, and you're one of 4 vendors competing to win, you need to win.

Well.

And 996, Ray, is just part of that.

Right?

You need to raise the most money. You need to get the most market share. You need the best partners. You need the biggest ecosystem. And yeah, that might be a lot of hard work. Back to you, Rick.

But Dave, winning is the key, especially in these new, not even category, but software era creations. And it reminds me of one of my favorite business authors is Geoffrey Moore. He wrote Crossing the Chasm, which is all about technology lifecycle adoption curve, which I think still fits today. But he wrote a book called The Guerrilla Game. And The Gorilla Game was about how you create dominance in enterprise software and new technology markets. And his argument was basically this: we're going to have 3 types of winners in new markets. And one's the gorilla. This is that market leader that captures a disproportionate share of a new market and is often 50 to 70%. An example of this is Microsoft with the Windows OS and their Office suite. or Salesforce in cloud CRM, or AWS in cloud infrastructure. And quite frankly, and arguably, OpenAI is trying to be that in AI as a platform. So you want to win and be that gorilla. But after the gorilla, you still got 30%, 40% of the market. And that second category that Geoffrey talked about is the chimps. And the chimps are secondary players, but they can't unseat that gorilla. Some examples might be ServiceNow versus Salesforce in the cloud, or Microsoft Azure versus AWS. Or maybe Anthropic versus Claude today. And then there's the, what Geoffrey called the third category, which is the monkeys. And it's the long tail, smaller competitors. These are the niche players that you might never heard about. I mean, honestly, it's companies like right now SalesLogic, Pivotal, and Goldmine and App were to Salesforce. And these are companies that a lot of our listeners probably haven't even heard about because they were just the monkeys.

So, so Ray, Correct me if I'm wrong. So, so as you know, I love Geoffrey Moore's work as well. Um, I basically— I'm calling these kind of lazily winner-take-all markets. Geoffrey Moore breaks it down more precisely, which is, hey, there's a gorilla, which is also known, um, by the Play Bigger guys as the category king, right? It's the same concept. Um, then there are the chimps, and then there are the monkeys. Uh, but it's all the same idea that the spoils go highly unfairly to the gorilla, the category king, what I just call the winner in the market. Do you remember if Geoffrey Moore talked about how much of the market cap goes to each group, or was that the Play Bigger guys? I can't remember. I thought he did.

No, that was Play Bigger guys. What he said in this book was the market share would be 50 to 70% for the king or the gorilla.

This is why I like Geoffrey Moore, because he— important distinction. He's using market share because that's what a good business builder and a good marketer cares about. When you take the investor profile, which is what Play Bigger did, Play Bigger was arguably written for investors. Investors, not operators. And they're talking about, here's how much of the eventual market cap, i.e., if you sum up the market capitalization, the value of these companies, here's how much of it goes to the winners. And my general rule of thumb is that first place is worth 10 to 100 times second, second place is worth 10 to 100 times third, which means the prize for third is typically on the order of a thousandth to maybe even less of first, right? For second, you're going to get 1/10 to 1/100 of first. And I have a lot of examples that kind of bear that out. So the main point of all this, if you want to know why people are even talking about 9/6, is because of these kind of power laws that if you're in these situations, that most of the value is going to go to the winner. So you need to go win, basically. Yeah.

But in this kind of winner-take-most category, it's not just your revenue growth and your market valuation. There were some of the day-to-day unfair advantages. I think you have 2 or 3 of those that we were talking about, such as—

Yeah, I can pick it up, Ray. It's called increasing returns, right, in economics. And in my mind, what's driving both the category king thing and the gorilla theory is the underlying driver is increasing returns. And enterprise software markets show strong increasing returns to market leadership. And what does that mean? It means it's a market where the mere fact that you are a leader increases your odds of winning more deals going forward. Simply put, the rich get richer, right? Well, why is that? Let's just talk about that for a minute. Like, what does that mean? And how can the rich get richer? Well, like first, just say you sell financial software. CFOs hate making mistakes. So, the leader is safer. It's not going to be— and by the way, if I'm going to make a mistake, kind of herd theory, I want to make it with everybody else.

Right.

Well, I wasn't the only CFO who bought this accounting system. We all bought it, right? But the other practical reasons why the rich get richer in enterprise software markets is that first, buyers are mistake-averse and different buyers more so than others. Second, committees are definitely mistake-averse. As soon as you make it a committee decision, you're going to get very conservative. Then practically speaking, the leaders tend to have the biggest ecosystems. So the most partners, the most integrations, the most employees in the market. So it's easier to hire people who know Oracle than who knew Sybase. Because there's just more of them. And also super important in determining this is switching costs. The higher the switching costs, the more you want to avoid making mistakes, the less risk you'll take. For example, switching a database system is like a heart transplant, or switching a general ledger system is like a heart transplant. Switching a planning system like IRAN, kind of a knee replacement. It's still surgery, but the switching costs are a lot lower than switching out your heart. Yeah.

You know, Dave, you know what FOMO is, right? Not FOMO, but FOMO.

No, what's FOMO?

It's why buying committees love market leaders because they have a fear of messing up. And in AI, they don't want to mess up.

In anything, they don't want to mess up. And this is probably— if I had to just teach people one thing about enterprise software, it's that buyers are mistake-averse and committees are mistake-averse. So you need to be very much— because everyone's like, oh, it's about business value. Like, yeah, it kind of is. is. But the dominant thing is, let's not make a mistake. And that alone drives the increasing returns of market leadership, which in turn drives some of the insanity we're seeing now. Because notionally, if my math is correct, you should be willing to spend anything to get from 3rd to 2nd and spend almost anything to get from 2nd to 1st because you're going to get a massive return on that investment. Go ahead.

Yeah, one of the things I wanted to say though is kind of investing to get that market leadership. And that's a capitalistic kind of behavior. This is different than what a monopoly is, right, Dave?

So, look, there's some semantics here about are these natural monopolies or not. Like, the textbook example of natural monopoly was telephone poles. Like, we as a country don't want 4 different companies putting up telephone poles and telephone wires. That makes no sense. It would make the landscape ugly. We don't want that. So, the argument was always that the telephone company back when telephones needed wires, was a natural monopoly because we collectively only wanted one set of telephone poles with one set of wires on them, right? That to me was the definition of a natural monopoly. I don't know if you consider these natural or not, right? I guess I kind of think they are. They're kind of modern-day natural monopolies because the market— basically, the lower in the stack you are, the more you're a platform, The more the market wants one or a few winners. The market doesn't want 17 winners. So, because there's too much entropy at lower levels in the stack. So, I think that's what's going on here. Look, most tech markets end up oligopolies, a few strong leaders, not monopolies.

Mm-hmm.

Some don't, but you'll tend to find the more fragmented a market at steady state, the higher it is in the stack. Thoughts, Ray?

No, I totally agree. And I think we've seen this multiple times. I mean, heck, even in the database world, we had this same phenomenon happen, right?

Well, the databases clearly happened, and the database is a pretty low-level technology, right? So, um, yeah, I mean, look, the original 4 relational databases, most people won't know 3 of them, but it was Oracle and Ingres and Formics and Sybase, right? You don't even know of them anymore. The technology has lived on. Ingres is now in Postgres. Sybase is now SQL Server, right? So, the technology kind of lived, but those companies are long since dead. And then, of course, Oracle, I always say they won round 1 and got to compete in round 2 against IBM's DB2 and Microsoft, right? So, but the fact of the matter is, the lower in the stack, the more the market wants a monopoly, an oligopoly, let's just say. They want few choices. They want to minimize entropy. BI is an example of being higher in the stack, where the BI market had, where I was there, Cognos, MicroStrategy, Business Objects, Brio, And the market tolerated more choices because there were less of a platform. So I'd say there were still some forces in place that drove people towards basically increasing returns on market leadership, but not all of them.

And we have same thing in those financial stacks, right? The mid-market, NetSuite's the clear market leader, and the SMB space, Xero's a market leader.

Yeah, look, I think one of the— and this is going to sound bad, but I think I don't like it when founders tell me, oh, there'll be multiple leaders in the category. Because yeah, you're right. But go read Geoffrey Moore because one's going to be a gorilla, one's going to be a chimp. There won't be multiple leaders. There'll be multiple survivors. I think there'll be one or maybe 2 winners, right? And they'll basically— Geoffrey Moore had it right. There'll be a gorilla or 2, usually one. There'll be a handful of chimps. And then there'll be a bunch of monkeys. And just remember that the thought, the part the Play Bigger guys did well was say roughly, the gorilla's worth 10 to 100 times A chimp's worth 10 to 100 times a monkey.

Well, once again, when I get into these topics that I just love talking about so much, time flies. But to kind of wrap up here, one of the things I wanted to talk about was back to 996. We're talking about it because these stakes are so high. That's the real issue, right?

Yeah, that's a good way to knit it out, Ray. The reason people are talking about this is because when these disruptive transformations happen, the stakes are high, higher than I think people understand. Certainly, when I was at Ingress, I don't think our executives knew how high the stakes were in the game we were playing. I think it's one of the reasons we lost. So look, if you want to win, winning, which I would argue is essential if you're in one of these markets. And again, what does these mean? It means kind of greenfield and it means fairly low-level platform, i.e., people are building stuff on it, not just using it. That means you have a very big opportunity. It means the returns of leadership, the increasing returns of market leadership will be strong. Therefore, in my opinion, you have to win. And what does winning take? It's not just 996-ing. Like, you could 996 for a crappy company with a bad strategy, and all you're going to do is get sick and tired, right? The point is not to work hard. The point is to win. And to win, usually you need aggressive leadership, aggressive capital raising, aggressive growth plans. If you raise all the money but don't plan to spend it to grow, it doesn't matter because Geoffrey Moore has it right. The real answer is measured market share points, not market cap, right? Market share will lead market cap, not the other way around. Aggressive product roadmap, understanding of the situation and the stakes, basically doing what it takes to win.

Yeah, and I will tell you, Dave, I've always been an athlete, or at least I used to be when I was younger. And it wasn't always the best athletes who won. It often, almost always, was the best athletes who invest the most to be the best at their craft. And I'll tell you, the one thing I walk away from my experience going through one of these major transitional eras, the internet, I had to make some tough choices on work-life and family. Right? And when I was early in my career, I would do anything to build that foundation. But it had to be a conscious choice. And then later in life, I had to make different choices. And if you make the choice to be part of this creating something special, it does take a lot of hard work.

Yeah. To me, Ray, it's a choice. I agree with you. Work-life balance is hard. I think we're both very happy with the choices we individually made. I think the real moral here, Ray, is there's only one wrong answer, which is 996-ing it in a bad situation, right? If you're going to be at Netscape in the 2000s or me at Business Objects, In the same time frame. 996-ing it was fun and rewarding and great. And no, I didn't work exactly 72 hours a week. It's probably more like 60, but I traveled a lot too. Never know how to count that. So I don't think you have Dave and Ray here arguing that everyone— hey everyone, go work 72 hours a week. I think we're saying, first, understand what people mean when they say 996. Second, I translate 996 to mean work hard. And my belief is If you're in one of these amazing opportunities, then it makes sense to go grind it hard. If you're not, it makes sense to work hard anyway because you want to be successful, but not like push-it mode. And the only losing answer in my mind, Ray, is giving your personal all, sacrificing your health and family and everything for a company that has a bad strategy in a crap situation. That's the only one that actually makes me sad.

Dave, I think that's a perfect way to end it. If you make the choice to be in this 996-type environment, choose wisely where you're going to allocate that energy and effort.

Well put, Ray.

Okay, thank you, Dave. That's a fun one.

See you. Thanks. The Metrics Brothers AI, SaaS, and More is a production of The Metrics Brothers Growth and CAC and a member of the Benchmarket Podcast Network. By accessing this podcast, you acknowledge that The Metrics Brothers make no warranty, guarantee, or representation as to the accuracy or sufficiency of the information provided Or the humor content of the jokes told, Ray. Information, opinions, and recommendations presented are, according to our spouses, probably wrong and provided for information purposes only. This podcast should not be considered professional or, for that matter, unprofessional advice. We disclaim any and all liability for any direct, indirect, undirect, misdirect, incidental, special, ordinary, consequential, inconsequential, or other damages arising out of any use of or. God help you, relies upon the information presented here. Ray Grothreich is based in New York City and available on X @rayreich. Dave Kellogg is based in Silicon Valley and available on X @kelblog. Schedectady, which is French for unspellable, is not our actual production location. Thanks for listening.