I’m skeptical that the same patterns we saw in the early 2000s are going to play out again.

Last time, tech was in its infancy. There was a small universe of people who understood baseline concepts like getting to product market fit, how to measure and implement growth patterns, etc etc.

Today these are practically household concepts, and they have been for years. There aren’t a few hundred other people in SV you are competing against, it’s the rest of the world.

On top of that, there’s a tried and true playbook that large tech companies quickly put to use to capture any remotely adjacent areas of product market fit.

I’m not saying there won’t be startups - there are today of course - but it also seems like there’s a lot of wishful thinking going on. (Among founders, VCs, and billionaires who made their money in the early 2000s too. It shocks me that many of them haven’t realized that the playbook that made them money in 2008 doesn’t make them special in 2023.)

Tech has been professionalized and nothing is nearly as easy as it once was.

I think you underestimate the effects of bureaucracy and sclerosis at large companies like Google, and the upcoming crackdown like the EU's DMA and DSA. Just look at how OpenAI basically stole Google's lunch.

Too early to spike the football over that, OpenAI got outfoxed on Dall-E illustratively and ChatGPT's best chance for monetization remains as a feature for MSFT services, not an independent entity.

You could have said the same about google originally when Yahoo was using google to provide their search services.

You could also have said that about Altavista, and you would’ve been right. Like GP said, it’s too early to tell.

Altavista wasn't a startup, it was a spinoff from DEC, a company that had its own issues with sales at the time, which led to their ignominious takeover by HP.

Perhaps there will be higher quality startups… I don’t know, it feels like prior to 2020, the market was in overdrive and everyone’s ideas were getting funding under the hype growth path to monopoly strategy. And during this time, how many Forbes 30 under 30 people have been found to be incredible frauds, some of the biggest economics has seen? With money not as cheap, I do wonder what will happen. The startup “rules” for 2023+ seem a bit different now and hyper growth tactics may not work as well now (or be incentivized as much until late stage growth rounds…but I’m not an investor). Anyway, I’ll now lean back in my arm-chair…

> There was a small universe of people who understood baseline concepts like getting to product market fit, how to measure and implement growth patterns, etc etc.

I'm a PM and I think veeerrrryyy few people understand this, including many of my fellow PMs.

I think it's like reading a book about how to pitch a baseball. Knowledge and application are entirely different. Someone might be able to regurgitate the theory on how to achieve product-market fit, but put them in the driver seat of a real product and lots of people flounder.

One of the most common mistakes is simply delusion - the believe that your product is 'there' when it's not. I believe there's a cognitive dissonance that impacts the product owner - you kinda have to believe (or at least outwardly project) that your product is doing well.

> I'm a PM and I think veeerrrryyy few people understand this, including many of my fellow PMs.

Preach. And the universe of people who can actually do the work to start something and get it to PMF is a pretty small subset of those who understand the concepts in theory.

I would even go further and say that those who don't understand Product Market Fit but still can build, learn PMF by stumbling, falling.

Same sports analogy- it is better to be someone who can play (but doesn't know the rules) than someone who has encyclopedic knowledge on the said sport but cannot play (physical limitations).

Totally agree. Someone who just understands that you need to go talk to customers and actually try to sell whatever you're building ASAP is going to fare way better as a founder than someone who learned what PMF is during their MBA but doesn't want to get out and do the dirty work.

What do you mean by "better"? There's room for lots of people to have jobs off the field. Think about all of the support staff we never see on TV during the game. Or off the field even during the game. The announcer/sports commentator, the coach, the physical therapists and doctors, the people that work the grounds. Stephen Curry doesn't work in vacuum and neither does Jeff Dean.

> there’s a tried and true playbook that large tech companies quickly put to use to capture any remotely adjacent areas

Hum... The reason why large companies have historically been unable to do that is because nobody in them bothers to do it, not because they don't know how.

And one of the consequences of a series of mass layoffs is exactly that people stop caring about things like this.

Or, to put it succinctly - Google took off because Yahoo didnt particularly want to be a search engine.

Oh, Paul Graham (from this site) has a nice history about their ad-selling team in his articles.

There's another set of large players who have sucked all of the air out of what could have otherwise been thriving, competitive categories with many players. Google with search, Amazon with eCommerce, Facebook with social. Yes there are maybe 1-2 counterpoints in each of these spaces, but they've largely been successful at leaving a lot of would be entrepreneurs avoiding these huge spaces because they know they can't compete.

The same feeling of tech 10-15 years ago is what the current AI scene feels like. There's definitely an emphasis on higher education now, but outside of that look at what hackers have been able to accomplish just solo. It's a burgeoning scene with the potential to be as impactful as software was. Except now instead of if/else, it's going to be inscrutable arrays of numbers representing learned programs :D. It seems super fun and the barrier to entry is a lot lower than people think!

Agreed. The type of employee at big tech today is a lot different than what once was. But given the volume perhaps the output will be similar.

When layoffs happened in the past, they were laying off old school enthusiasts because the companies just weren't working.

Now, they are laying off people that went into tech because it seemed like easy money.

It's not the same caliber of tech person.

This claim is completely un-substantiated. Many people around me who have been laid-off are extremely talented engineers.

Then the company made a huge mistake letting them go, unless the company was just FULl of extremely talented engineers.. which statistically just isn't true.

nicenewtemp84 believes that large companies layoff engineers based on skill.

The truth: Eenie meenie miny moe

ReflectedImage thinks large companies layoff engineers based on a random number picker.

The truth: everyone knows who the underperformers are.

Everyone in a team might know who the underperformers are. But team members and EM are kept out of layoff-related decisions, which are generally done by upper management with the help of external consultants. Those external consultants are about as good as a random number generator.

People are also only fungible to a limited degree. Companies cancel projects, eliminate functions, and so forth. Especially in the middle of a large layoff there's often a limited appetite for finding a new home for someone who may be a high performer in the abstract but doesn't have a job any longer and may not be an ideal match for a position that already has someone doing it.

This is my experience. The last company I worked for that did layoffs while I was there was an example. None of the middle managers had any input in the firing decisions at all. They were just given a list of names by upper management. They were very upset about it, because they couldn't lay off people that were underperforming and were forced to lay off people who were critical or performed very well. Many of them said that it didn't appear that the decision-makers even looked at performance reviews, either. It appeared random.

You are making similar logical errors. You speak as if the most recent layoffs were simply firing the lazy employees.

AFAICT, companies are both jettisoning entire departments related to bad bets (or bad business models) and preparing for anticipated recession-level revenues.

Skills are not perfectly fungible. Managers making layoff decisions based on the roles/skills they need to keep and what budget they can afford. This necessarily means that some underperformers will be retained and many overperformers will be cut.

A lot of people seem to imagine layoffs happening (or that they should happen) according to some well-calibrated stack ranking at the company level. But that's not typical at all.

Sure some employees on PIPs or otherwise considered low performance may be cut regardless of role. But more typically projects get cut/defunded (whether in engineering or elsewhere) and those roles are eliminated or cut back. A good performer may have an opportunity to find a job elsewhere in the company but, in my experience, that's pretty hard given that any open slots were probably also closed as part of the layoff.

I sometimes wonder if the people who think companies are perfectly optimal have ever worked in a company or large organization.

It reminds me a bit of the argument against massive conspiracies to demonstrate how many people have to perfectly as an organization (leaving no evidence behind) and then have to stay quiet indefinitely. The larger the accused conspiracy, the more likely information is to leak.

Companies this profitable and large often actually overhire a small degree to deny the competition talent and to give a layer of people that can be laid off to boost profits quickly to make a board think management is good. Google or FB can lay off 5k people and not even NOTICE a change in productivity, but the boards eat it up.

They might hire to scoop people up, but when they fire, don't they fire based on performance? Or is it purely a random pick?

Cannot say about layoffs in the past, but at the FAANG I am at, the most recent layoffs were absolutely random on the individual level, but not as random on the organizational level in my org.

E.g., "this group of 4 engineering teams responsible for area ABC needs to get cut by 30%, because we are deprioritizing this area"? and then the actual people who get laid off from that group of 4 teams are chosen entirely randomly. It perfectly aligns with the idea that the layoffs are mostly due to major changes in prioritization of projects (due to recession and all), not to just cut "bad engineers." If you are ok with your company's engineering quality overall and just want to cut projects you consider wasteful or deprioritize them to save money, personal-level randomization run against a deprioritized group makes sensez

I believe part of the reason is that randomizing makes it safer for the big companies legally as well, since that makes it much more difficult to successfule sue them for unjust firing or discrimination and other reasons.

Some from every column. In larger companies, firing decisions are often political decisions.

Yep, I've been in companies where it's the whole "every department needs to cut" rather than only cutting dead weight.

That's what you, as an engineer would do if you were to do layoffs starting from first principles, but that's not who's doing the layoffs.

This! AWS was doing this in 2017 and 2018.

Damn, can't imagine a company making a mistake. That clearly just never happens.

Its somewhat substantiated by the fact that getting into modern big tech is pretty much focusing on the interview process, which has almost zero to do with actual real world development.

Furthermore, having worked in big tech, most of the roles that are getting filled are essentially "busy work" - i.e here is a entire proprietary build system, barebones service and deployment pipeline, all you have to do is add logic. Someone who has worked in this type of environment isn't going to succeed at a startup where you have to build systems from scratch.

Ah yes, the just world fallacy of layoffs makes its unsurprising appearance.

Most of the 2022 and 2023 layoffs were for "Non-Technical" or "Tech-Adjacent staff". [0] [1] [2] [3] [4]

The market is still incredibly strong for SV caliber devs, and I see no signal it's going to slow down. If anything, it kept compensation for engineers from cratering by propping up the stocks.

[0] https://interviewing.io/blog/2022-layoffs-engineers-vs-other...

[1] https://www.bloomberg.com/news/articles/2023-01-24/tech-layo...

[2] https://www.computerworld.com/article/3690309/about-those-te...

[3] https://www.gartner.com/en/newsroom/press-releases/2023-03-0...

[4] https://techreport.com/news/3493451/microsoft-layoffs-ethics...

You are out of your depth if you are comparing numbers, try interviewing in this market as a generic web dev and reality will come to you very soon. SV caliber devs leaving US because they can find better paying roles internationally or not even looking due to fat severance/low pay in the bay.

> SV caliber devs leaving US because they can find better paying roles internationally or not even looking due to fat severance/low pay in the bay.

Where are they going? Genuinely curious. Where outside of the US are SV caliber devs getting paid even more than they'd be getting paid here?

I agree that tech today is much more filled with “for the money” types - I’ve been lamenting this repeatedly.

I don’t agree that companies successfully filtered them out via layoffs. If anything it’s the opposite. One of the “skills” that help you avoid being laid off is to be good at office politics and gaining visibility (so the VP making the layoff decision knows your name). That skill seems correlated with ladder-climbing more than tech-enthusiasm.

Most big tech employees are not startup people. That's why they work at big tech.

You can't necessarily reach that conclusion.

Big tech employs more people than startups, which means it's more likely for someone to get a job at big tech than a startup. It's just a law of numbers and has nothing to do with whether they're suited for startup life or big tech life.

In addition, in the US, foreign students who just graduated are more likely to get a job at big tech than startup because more big tech sponsor H1B/Green card than startups. And the fear/circumstances around losing your immigration status means more of them might opt for big-tech than startup

Some of them are startup people, but the ones who have ground through a degree and leetcode before landing a job maintaining an esoteric part of Big G's internal systems assuredly aren't.

I’ve worked at “Big G” and a startup - big tech is a much more sane place to start a career than a startup. If you just graduated, it’s a good place to learn basic skills before considering a startup job.

Google for example is much more rigorous with code reviews and code quality. They maintain a high % test coverage, continuous integration and delivery… etc. startups can’t maintain those same standards and move quickly. learn the rules before you break them.

Losing a job, like any major life event, can cause a rethink on this sort of thing. The average age of a successful startup founder is 45 for a reason. Most of them spent some time employed in the industry of the startup. Before that, they probably bounce between a job and trying to make it on their own.

Our statements don't exclude each other.

Not all big tech employees want to deal with the hustle required at a startup. That's why we're in big tech. Most of my teammates work to live, we don't live to work.

>not all Big Tech employees can deal with the hustle required at a startup

Thank God for that. Who better to look at broken processes draining productivity and then say “oh, we solved this with X, when I worked at Y” ?