Report: WeWork expected to cut 500 tech roles(techcrunch.com)
techcrunch.com
Report: WeWork expected to cut 500 tech roles
https://techcrunch.com/2019/10/08/wework-layoffs-2/
14 comments
It's a classic case of hire engineers first and figure out problems to solve later. This works great if the company already has a massive revenue stream (Google, Facebook etc.) so the engineers can just mess around and once in a while come up with something great. For a company losing $2B+ a year, not so much.
Once WeWork solved its core engineering problems (bookings), engineering job descriptions got more and more abstract - "build the operating system for the workspace", "bridge the gap between physical and digital", "create a sense of community", "humanize through technology" (all copied directly from their engineering website), so it's clear that they are paying thousands of engineers to do nothing.
I know for a fact that they have large data and machine learning teams spread across SF, NYC, Tel Aviv, Shanghai and maybe more that collect and analyze data from all their operations - few hundred offices and few hundred thousand members. At this scale there is zero reason not to use off-the-shelf products (or pay one of the dozens of companies out there that specialize in this), but they decided to custom build all the infra in-house from scratch.
Once WeWork solved its core engineering problems (bookings), engineering job descriptions got more and more abstract - "build the operating system for the workspace", "bridge the gap between physical and digital", "create a sense of community", "humanize through technology" (all copied directly from their engineering website), so it's clear that they are paying thousands of engineers to do nothing.
I know for a fact that they have large data and machine learning teams spread across SF, NYC, Tel Aviv, Shanghai and maybe more that collect and analyze data from all their operations - few hundred offices and few hundred thousand members. At this scale there is zero reason not to use off-the-shelf products (or pay one of the dozens of companies out there that specialize in this), but they decided to custom build all the infra in-house from scratch.
> I know for a fact that they have large data and machine learning teams spread across SF, NYC, Tel Aviv, Shanghai and maybe more
That's going to be an awkward presentation to management when they present their revenue forecasts under different economic scenarios...
That's going to be an awkward presentation to management when they present their revenue forecasts under different economic scenarios...
Maybe they are using all those ML teams to build "self driving offices" (a la uber) or Self-greeting receiption? or predictive room bookings
[deleted]
Could have hired 500 office managers at half the salary and give them a paper daily planner.
Probably need 20 engineers to do that...
And another 480 to change the UI in annoying and unnecessary ways every three days.
And another 480 to change the UI in annoying and unnecessary ways every three days.
I'm struggling to think what of that couldn't be done with off the shelf software, honestly. Hell, most of it could be done with Outlook and Active Directory.
Not in a way that scales or is user friendly. You might be able to use those as a base for something very hackey. I helped build a full suite to do everything in that list for a coworking "start up". It gets complicated pretty quickly and you need a custom ui and good control of the data model for custom business logic. If you want self serve subscription payments and reservations you'll need a few programmers. But not 1000 of them.
So Wework acquired https://www.teem.com/ specifically to do this, well the room booking part at least. They actually approached a different company and were rejected so they bought Teem.
I liked the product, and wanted to purchase it. We Co had so over funded Teem that the sales people couldn't keep up. They were doing demos with experienced Sales Engineers and literally couldn't explain how things worked. We had 2 demos in 2 successive weeks and the product fundamentally looked different both times.
Think about that: Imagine having unlimited eng and product resources and pushing code so fast that your sales team can't keep up sounds good right?
Wrong...we didn't buy Teem we went with their competitor who was behind on a few items, but had a concise product and a concise roadmap that met our needs, not the needs of 1000 coworking spaces tied together.
I liked the product, and wanted to purchase it. We Co had so over funded Teem that the sales people couldn't keep up. They were doing demos with experienced Sales Engineers and literally couldn't explain how things worked. We had 2 demos in 2 successive weeks and the product fundamentally looked different both times.
Think about that: Imagine having unlimited eng and product resources and pushing code so fast that your sales team can't keep up sounds good right?
Wrong...we didn't buy Teem we went with their competitor who was behind on a few items, but had a concise product and a concise roadmap that met our needs, not the needs of 1000 coworking spaces tied together.
WeWork had apps to optimize the space in their office layout for maximum efficiency. They had one of the lowest sqft per paying member in the business.
They also were into custom spaces. They needed software to design the office floor plans for big customers like MixPanel.
Lots of software. Not just booking rooms and events.
They also were into custom spaces. They needed software to design the office floor plans for big customers like MixPanel.
Lots of software. Not just booking rooms and events.
apps to optimize the space in their office layout for maximum efficiency
That sound like some useless bullshit if I've ever heard it.
That sound like some useless bullshit if I've ever heard it.
It's literally the bin packing problem, which is NP-complete. Plus you have another axis entirely on top of the already NP-hard problem: You want to minimize the number of times that you move any given group of people over time as you re-configure the office space to fit the maximum number of groups into it.
This is an algorithmically hard problem, and I'm not surprised that there might be significant benefits to investing in solving it very well.
This is an algorithmically hard problem, and I'm not surprised that there might be significant benefits to investing in solving it very well.
Can you give me an order of magnitude estimate of how many milliseconds you believe solving the 2d bin packing problem with added constraints would take on a commodity PC when n=the max number of clients in any wework building?
The problem is interesting, but it isn't one you need to set up an entire engineering team to solve.
The problem is interesting, but it isn't one you need to set up an entire engineering team to solve.
Actually, yes, I think you would need an entire engineering team to write, maintain, scale, and run a system that solves this problem. For example, my employer has a whole team working on internal tools for booking/managing/re-allocating conference rooms. It's almost exactly the same problem, it's non-trivial, it's complex, and it takes an entire team.
Really? You think optimizing office layout to maximize rental income is ”useless bullshit”?
In fairness, it might actually be. They have a lot of properties, yes, but is it so many that that can't just send a particularly skilled human around to design them?
Binpacking is np-hard but humans still do a very good job of playing Tetris. It is hard to imagine getting a positive return on automating something they (in the long run) will do a few times a year.
Binpacking is np-hard but humans still do a very good job of playing Tetris. It is hard to imagine getting a positive return on automating something they (in the long run) will do a few times a year.
If I understand their business correctly, way more than a few times a year. I think they have problems of the kind
”there’s a team of 5 Monday to Wednesday, one of 7 Tuesday that also have a meeting room, one of 4 Tuesday to Friday, one of 3 for the next three weeks, one of 2 that have to sit side-by-side, …. Figure out who to place where, minimizing the times we have to tell customers to move desk, maximizing the ‘cohesion’ of desks assigned to each group. Oh, and do this knowing that the problem may change at any time”
And all of that, hopefully, in a building with a high occupancy rate, all the time.
”there’s a team of 5 Monday to Wednesday, one of 7 Tuesday that also have a meeting room, one of 4 Tuesday to Friday, one of 3 for the next three weeks, one of 2 that have to sit side-by-side, …. Figure out who to place where, minimizing the times we have to tell customers to move desk, maximizing the ‘cohesion’ of desks assigned to each group. Oh, and do this knowing that the problem may change at any time”
And all of that, hopefully, in a building with a high occupancy rate, all the time.
> It is hard to imagine getting a positive return on automating something they (in the long run) will do a few times a year.
That's totally fair. I think they actually do some other types of more mundane optimization that are geared towards managing the properties. I think a number of the engineers also work on the learning platform for their education services.
That's totally fair. I think they actually do some other types of more mundane optimization that are geared towards managing the properties. I think a number of the engineers also work on the learning platform for their education services.
This sort of software is hugely valuable in things like manufacturing. I don’t know enough about commercial real estate to know if it can drive the same efficiency there but it’s certainly not on its face clearly useless.
In fact it sounds way more useful than most software projects I see.
In fact it sounds way more useful than most software projects I see.
So does most software until you try doing stuff the hard way.
That’s a very weird take. That’s probably one of the highest value problems to solve in the entire economy.
lol here's a hot tip for you: anything with "optimize" in the description is not useless bullshit. like the person said: it's literally an np-complete problem.
Um, ok, so they just put in more chairs than anyone else.
A lot of those are build-once (if you don't buy third party) and do tiny updates later.
Does this justify hundreds of engineers?
No.
And the software to do those things isn't worth billions.
WeWokeUp.
No.
And the software to do those things isn't worth billions.
WeWokeUp.
I kinda wish there was a job for like, DevOps Hatchet Men. I don't want to lay people off, but after they're laid off I feel like I could probably delete about a million dollars a year worth of their AWS bill right now and they'd never even notice the stuff missing.
I sort of did that for a while. The differences between what management thinks they have, what is actually running, what data centers are charging back, what licenses are being invoiced, what finance is depreciating, and what is actually needed for operations can be astonishingly large.
I just took on a project that uses micro service style architecture (8 services total) and runs on AWS, has no customers, and costs more per month than I've seen very high revenue projects spend in over 6 months for hosting. I can't imagine how bad it would be with older projects with more cruft.
I think this space is hotter than ever. Hard to keep juicing profits for Wall Street when you are increasing AWS spend 5% month over month.
There are LOTS of companies spending a million a month or more on AWS.
There are LOTS of companies spending a million a month or more on AWS.
Whoops, apparently I can't read.
That would be $52M per year. I would guess there are under 100 companies with that kind of AWS bill and probably closer to a couple dozen with that kind of spend.
That would be $52M per year. I would guess there are under 100 companies with that kind of AWS bill and probably closer to a couple dozen with that kind of spend.
$12M but sure.
Sounds like a great consulting niche. It's a simple to understand value proposition and I imagine there is somebody powerful at many successful companies that would love to see the huge server cost line item go way down on their P&L.
There are consulting roles like that, but you’ll make more in infosec and it’s an easier sell than arguing why you should capture your share of the value you’re delivering to make it worth your while.
I would never recommend it, but the thought has crossed my mind (definitely more than once) that the scream test could work wonders with cloud infrastructure [0].
[0] https://blogs.msdn.microsoft.com/anitag/2012/06/07/i-scream-...
edit: I suppose Chaos Monkey could be purposed for this task in hindsight.
[0] https://blogs.msdn.microsoft.com/anitag/2012/06/07/i-scream-...
edit: I suppose Chaos Monkey could be purposed for this task in hindsight.
That article took a horrifying left-turn when she started talking about using the scream-test for your test suite itself.
A test is not 'proven unnecessary' if you temporarily disable it, and show that a bug does not arise to fill it up!
A test is not 'proven unnecessary' if you temporarily disable it, and show that a bug does not arise to fill it up!
AWS consultants most definitely exist already.
Why not use the hundreds of software tools that do this automatically?
Because there's a thing called "CYA".
I saw folks do this for Buzzfeed layoffs and Uber layoffs a while back, and I think it was helpful (context here : https://www.businessinsider.com/ex-uber-employee-has-created...)
If you're affected by the WeWork layoffs and looking for a new role, fill this out: https://docs.google.com/forms/d/e/1FAIpQLSdx4TOVN7AdgvyAZGbq...
If you're interested in recruiting ex-WeWork folks, you can look them up here: https://docs.google.com/spreadsheets/d/14CAtBsn3ZTL59tNMVbew...
If you're affected by the WeWork layoffs and looking for a new role, fill this out: https://docs.google.com/forms/d/e/1FAIpQLSdx4TOVN7AdgvyAZGbq...
If you're interested in recruiting ex-WeWork folks, you can look them up here: https://docs.google.com/spreadsheets/d/14CAtBsn3ZTL59tNMVbew...
youre a good person.
If you’ve been inside of a WeWork office, there is a pretty advanced process in place for checking in and alerting different people about you being there. It felt a bit over-engineered when I went there, but I suppose that is the kind of stuff these “tech roles” worked on.
What do five HUNDRED people in tech do at an office rental company?
Without meaning any offense to anyone, I am also genuinely curious how is a company such as Twitter have so many employees? Outsiders like myself know what goes into running GE or Tesla (and is easy to understand), but I would really appreciate someone from silicon valley enlighten about various needs for a company such as Twitter (or WeWork, etc.); what really goes on inside the doors, how are teams organized, what are some of the most challenging problems?
If I were running Twitter, I would freeze the feature creep, have a robust security and site-reliability team, perhaps make small improvements to UI/UX by eliminating friction/impedance. Similar to how Craigslist and surprisingly how Ebay is today - it is pretty much the same experience as 2008, I vividly remember. Instead, engineering resources can be channeled to new ventures (or augmentation projects) for additional growth.
If I were running Twitter, I would freeze the feature creep, have a robust security and site-reliability team, perhaps make small improvements to UI/UX by eliminating friction/impedance. Similar to how Craigslist and surprisingly how Ebay is today - it is pretty much the same experience as 2008, I vividly remember. Instead, engineering resources can be channeled to new ventures (or augmentation projects) for additional growth.
As a company grows, development becomes harder due to the need to interface with so many teams -- a feature that you used to be able to implement a couple days after a lunchtime discussion with your coworkers turns into a detailed design and design review, design revisions to prevent breaking functionality that other teams use, a revised design review and approval, security review and approval, and then finally implementation, but you find that in the 3 months since you started the design, the functionality you were planning on using was changed by yet another team and the affect on your feature was missed during that project's design review.
Plus, the problems you need to solve get more complicated, you have new compliance needs, paying customers are demanding new features that may require changes across your entire stack, performance is more of an issue (saving 3% of your compute costs didn't matter when you were paying $500/month for infrastructure, but saving 3% of 10 million dollars/month starts turning into real money) and writing and deploying software used by hundreds of millions of people is literally orders of magnitude harder than software a few million people use.
Plus, the problems you need to solve get more complicated, you have new compliance needs, paying customers are demanding new features that may require changes across your entire stack, performance is more of an issue (saving 3% of your compute costs didn't matter when you were paying $500/month for infrastructure, but saving 3% of 10 million dollars/month starts turning into real money) and writing and deploying software used by hundreds of millions of people is literally orders of magnitude harder than software a few million people use.
I found this from another front page article about Automattic:
https://automattic.com/about/
If you go to their about page, they show a little table, where they have 163 million monthly active users and only 966 employees. Not sure how good this comparison is with Google and Amazon because the kind of tools Amazon builds vs what Automattic builds (WooCommerce, Wordpress) are totally different.
If you go to their about page, they show a little table, where they have 163 million monthly active users and only 966 employees. Not sure how good this comparison is with Google and Amazon because the kind of tools Amazon builds vs what Automattic builds (WooCommerce, Wordpress) are totally different.
Because at scale small changes can save or make a company more money than an engineers salary.
Simply making a process 2% more efficient can save hundreds of thousands of dollars a year. Or increasing advertising conversions by 1%. etc etc.
Simply making a process 2% more efficient can save hundreds of thousands of dollars a year. Or increasing advertising conversions by 1%. etc etc.
Right, but system creation+enhancements can be made by a single engineer in a large % of those cases. Overwhelmingly so if you already have a working live system to start with and you are seeking incremental improvements (vs a full rewrite).
There aren't many technical challenges I have encountered, when reduced to their smallest functional dimensions, that couldn't be fundamentally addressed by a single engineer. Obviously, efforts like writing an entire (practical) operating system are impossible for a single engineer to accomplish, but even then a single engineer could lead the entire effort or massive parts of the effort (e.g. the Linux kernel).
Conversely, I have seen far too many cases of "too many chefs in the kitchen" when it comes to a software project. This is the end of the spectrum where you end up stuck on Docker with a stochastic and otherwise insane architecture that isn't even consistent within each product, much less across the entire organization.
There aren't many technical challenges I have encountered, when reduced to their smallest functional dimensions, that couldn't be fundamentally addressed by a single engineer. Obviously, efforts like writing an entire (practical) operating system are impossible for a single engineer to accomplish, but even then a single engineer could lead the entire effort or massive parts of the effort (e.g. the Linux kernel).
Conversely, I have seen far too many cases of "too many chefs in the kitchen" when it comes to a software project. This is the end of the spectrum where you end up stuck on Docker with a stochastic and otherwise insane architecture that isn't even consistent within each product, much less across the entire organization.
The percentage of changes that actually improve things drops significantly as the company gets more optimized, so you need to try more things to have a good chance of actually getting one implemented.
Say that a tweak to the page improves ad revenue by $50M. 98% of tweaks have neutral or negative effects. The expected value of the tweak is thus $1M, well over one engineer's salary. You need to have 50 of them going on in parallel to have a good chance of actually finding a successful tweak, though. (Well, technically about 150 to have a 95% confidence that at least one will prove useful, but there's also a good chance that more than one will be useful then.) That's what all the engineers are doing - independently implementing different changes and discarding 98% of the results.
When I did this kind of work, the vast majority of engineering time was actually spent measuring the results. It was not unusual for the actual implementation work to be done in about 3 hours, but the experiment design, approval, configuration, logging, data-collection, and analysis to take 3 weeks. And that was with a fair amount of existing tooling for measurement & process.
Say that a tweak to the page improves ad revenue by $50M. 98% of tweaks have neutral or negative effects. The expected value of the tweak is thus $1M, well over one engineer's salary. You need to have 50 of them going on in parallel to have a good chance of actually finding a successful tweak, though. (Well, technically about 150 to have a 95% confidence that at least one will prove useful, but there's also a good chance that more than one will be useful then.) That's what all the engineers are doing - independently implementing different changes and discarding 98% of the results.
When I did this kind of work, the vast majority of engineering time was actually spent measuring the results. It was not unusual for the actual implementation work to be done in about 3 hours, but the experiment design, approval, configuration, logging, data-collection, and analysis to take 3 weeks. And that was with a fair amount of existing tooling for measurement & process.
Most of the time one competent 10x engineer could indeed build out all the special features that a company needs. The problem is that one person generally doesn't know all the best practices required of every problem domain, so they may implement things poorly. Furthermore, the one dev thing really doesn't scale up. As soon as your product gains any critical mass and you have an outage then the platform is hosed because no one knows how to fix anything except MAYBE that one engineer who implemented all the special features.
There are no systems running Windows 10X in production yet.
Can't tell if you're trolling, so in case you've confused others.
http://svdictionary.com/words/10x-engineer
http://svdictionary.com/words/10x-engineer
Its a shame this amazing reference is being downvoted.
Hopefully Windows 10X puts an end to the "10x developer" meme.
Hopefully Windows 10X puts an end to the "10x developer" meme.
But WeWork doesn't make any money. That is the problem. No matter how many smart engineers they hire, it is just adding additional cost, until they start to turn a profit.
Majority of its business value goes to real estate owners.
Majority of its business value goes to real estate owners.
Even though this article's title sounds like it, this isn't meant to be flippant: https://danluu.com/sounds-easy/
Also see the other child comment: Once you have a significant amount of revenue, investing the effort improve things by 0.1% (or even 0.01%) can have a not-insignificant impact on the bottom line.
Also see the other child comment: Once you have a significant amount of revenue, investing the effort improve things by 0.1% (or even 0.01%) can have a not-insignificant impact on the bottom line.
Twitter has 321 million monthly active users.
WeWork has 466 thousand members.
The scale is quite different.
WeWork has 466 thousand members.
The scale is quite different.
I have always wondered this too. On the surface, Twitter doesn't seem like a very elaborate service. I'm sure there's serious thorny scaling problems to deal with. But how many engineers does that really take?
Remember the fail whale? Scaling is hard.
It's hard when you build a global business on a scripting language.
One of Twitter's main challenges at this stage is content moderation and fraud detection, a technical challenge for which solutions are not straightforward or easily scalable.
Consumer VC companies are businesses that require growth at all costs. So they need to invest in man-hours to churn out features.
If they were a normal company, they’d focus on the top x projects that generate value and spend as little as possible on the rest.
If they were a normal company, they’d focus on the top x projects that generate value and spend as little as possible on the rest.
Twitter runs an entire advertising platform. If you've ever logged into Adwords or Adsense you'll know how complicated that is.
I wouldn't be surprised to learn that the basic twitter.com tweeting/commenting/retweeting system isn't remotely the most complex system that Twitter even has.
I wouldn't be surprised to learn that the basic twitter.com tweeting/commenting/retweeting system isn't remotely the most complex system that Twitter even has.
So you'd freeze the feature creep, but keep working on the set of features you listed? I think you answered your own question.
8 people work on the tweeting part, 4000 on ad sales.
According to [0], apparently at least some of them are involved with exploring fancy over-engineered tech-stacks
[0](https://vicki.substack.com/p/you-dont-need-kafka)
[0](https://vicki.substack.com/p/you-dont-need-kafka)
Help convince investors that it's an innovative tech company and thus worth 5x the valuation it'd otherwise get.
edit: This is based on some of the pointless pie in the orbit of pluto projects I've heard they were trying to work on.
edit: This is based on some of the pointless pie in the orbit of pluto projects I've heard they were trying to work on.
The first 100 engineers build stuff. The remaining 400 engineers fix the stuff the first 100 build.
You mean 1500 people.
1500 is the rough total number of employees, including non-tech ones, but the question is more along the lines is what the need is for 500 programmers/sysadmins/etc.
EDIT: Nevermind, I got confused with this part of the article:
> New York-based WeWork has roughly 15,000 employees
EDIT: Nevermind, I got confused with this part of the article:
> New York-based WeWork has roughly 15,000 employees
WeWork currently employs about 15,000 people.
Though pretty much everyone expects that number to drop a good bit with layoffs (including this one) in the coming months.
Though pretty much everyone expects that number to drop a good bit with layoffs (including this one) in the coming months.
No 1500 is number of tech employees.
See https://www.theinformation.com/articles/wework-plans-to-shed...
See https://www.theinformation.com/articles/wework-plans-to-shed...
[deleted]
- Kubernetes operation: 3 people
- API on top of Kubernetes: 2 people
- Tools around the API on top of Kubernetes: 1 person
- API and tools specific for continuous integration: 2 people
- Database operation: 2 people
- Event/Data pipeline: 5 people
- Authentication: 3 people
- Mobile API: 2 people
- Mobile App: 2 people
- Web API: 4 people
- Web App: 4 people
- ETL/Data science: 5 people
- Document writers, testers, new tech on-boarding evangelists: 5 people
That's 40 people for one feature. And you have 12 features, you need 500 people.
- API on top of Kubernetes: 2 people
- Tools around the API on top of Kubernetes: 1 person
- API and tools specific for continuous integration: 2 people
- Database operation: 2 people
- Event/Data pipeline: 5 people
- Authentication: 3 people
- Mobile API: 2 people
- Mobile App: 2 people
- Web API: 4 people
- Web App: 4 people
- ETL/Data science: 5 people
- Document writers, testers, new tech on-boarding evangelists: 5 people
That's 40 people for one feature. And you have 12 features, you need 500 people.
40 people with this kind of breakdown for a product, sure. This huge team for a feature? Lol, no
Every feature requires 2 people to build the endpoints, 3 people to wire up the auth and 2 people to add it to the web app? And that's all they do going forward?
Pair programming!
is this breakdown based on experience with the wework tech stack?
There IS a market for a WeWork like service.
A WeWork-like model has appeal to someone like me that would love good coffee and an office/hoteling space! Especially as I travel a lot and sometimes want a reliable private workspace in an arbitrary city. Coffee shops frankly don’t cut it for working/meeting with people all day.
Also there’s often a need for meeting spaces in arbitrary cities. my company would have used an airBNB style conference room scheduling solution half a dozen times last year.
All to say there’s at least a potential customer base here. Whether it’s a profitable business model, well, maybe :)
A WeWork-like model has appeal to someone like me that would love good coffee and an office/hoteling space! Especially as I travel a lot and sometimes want a reliable private workspace in an arbitrary city. Coffee shops frankly don’t cut it for working/meeting with people all day.
Also there’s often a need for meeting spaces in arbitrary cities. my company would have used an airBNB style conference room scheduling solution half a dozen times last year.
All to say there’s at least a potential customer base here. Whether it’s a profitable business model, well, maybe :)
There's definitely a profitable business there, even. WeWork is absolutely a very reasonable, solid business. It's probably just not worth $50 billion.
I feel like a missed opportunity for WeWork was a kitchen. AFAIK none of them sell food for purchase. Why not get all the workweek lunch revenue?
If my friend who owns real estate can be used as an anecdotal bulletpoint: At the pub last night he told me how he and numerous other property owners here in Chicago have people who are trying to start their own catering/dinner party businesses and will rent out airbnb's with especially nice/large kitchens to do all of their food prep over a couple of days, check out and leave. A couple of them graduated to being able to sign leases on their own commercial kitchens once their respective client bases grew large enough.
At first, he said he was confused why the kitchen of all places was constantly the most time-costly area of his properties to clean. Then one of the renters let him know what was going on.
Now there's an opportunity.
At first, he said he was confused why the kitchen of all places was constantly the most time-costly area of his properties to clean. Then one of the renters let him know what was going on.
Now there's an opportunity.
Wow, that is fascinating. There's clearly a larger market for commercial kitchen space than is being satisfied.
Yes, I mean that is what Travis Kalanick is doing with his new company Cloudkitchens
Oh you gotta be kidding, really?
Edit: Googled it, You are NOT kidding wow. On the one hand, it's a great idea. On the other hand CloudKitchens?
I grok that, but...is the target market here DevOps people who make a great alfredo on the side?
Edit: Googled it, You are NOT kidding wow. On the one hand, it's a great idea. On the other hand CloudKitchens?
I grok that, but...is the target market here DevOps people who make a great alfredo on the side?
Would WeWork operate the cafeteria themselves, or make kitchen space available for cuisine-inclined people to make and sell food to the people using the co-working space?
In either case, you can imagine opting in to a monthly spend for N employees of your company, at some kind of discount, to spend at the cafeteria. Wouldn't be much different from the private club model of running a restaurant, where you have a given monthly spend that you have to use no matter what. And everyone in the WeWork already has badges so it'd be simple tap-to-pay that would go directly onto/against your monthly coworking bill.
In either case, you can imagine opting in to a monthly spend for N employees of your company, at some kind of discount, to spend at the cafeteria. Wouldn't be much different from the private club model of running a restaurant, where you have a given monthly spend that you have to use no matter what. And everyone in the WeWork already has badges so it'd be simple tap-to-pay that would go directly onto/against your monthly coworking bill.
There's IWG. The unsexy competitor whose been doing it for longer and has more properties and isn't valued at 100x their worth.
>> my company would have used an airBNB style conference room scheduling solution half a dozen times last year.
These exist. They exist all over the world. Regus being one.
These exist. They exist all over the world. Regus being one.
There are companies that provide office space everywhere. Check out Regus for example -- http://regus.com.
Can't most hotels provide a conference room and other services?
It’s called a hotel or motel. They contain all those things you desire.
Not really. Having tried to use hotels for meetings, they are unreasonably expensive and do stupid stuff like “the whiteboard rental fee is $500/day”
Maybe that's just the cost of offering these things. How much money do you think they're making off of those fees? They're probably covering costs and are low margin.
I think they are making a killing. If you have a business meeting in progress with your client, you are not going to move to another hotel bc of $500 whiteboard fee. You cringe and put this expense on your corporate credit card. And hotel knows this.
As someone who's been around enough people who book conventions, they're making a KILLING off these fees. It's the business model of the industry; they get you on the extras. Every little coffee or snack break is outrageously expensive. God help you if you cater a lunch through them.
If you think the services for a wedding are expensive, try booking a convention. Companies have way more money to spend than random couples do, and the hotels/convention centers know it.
For example, here's a typical catering menu for a convention center. Note that most of these prices are per person, and also note all the extra fees that they'll ding you for on pages 2-4 on top of the already high food costs (e.g. $2 per meal and break per person for plates).
If you think the services for a wedding are expensive, try booking a convention. Companies have way more money to spend than random couples do, and the hotels/convention centers know it.
For example, here's a typical catering menu for a convention center. Note that most of these prices are per person, and also note all the extra fees that they'll ding you for on pages 2-4 on top of the already high food costs (e.g. $2 per meal and break per person for plates).
Literally last week I got an email from WeWork looking for a Senior Data Engineer with "High Comp". I never understand these companies, aggressively hiring before they lay everyone off
I think it will cause a lot of cognitive dissonance if you treat large companies like you'd treat a single person. Imagine there is one person in charge of everything; it would be super weird if they bring you in for an interview on the day they're firing everyone else. But that's not how these large companies work; one person made the hire someone and some other person that's never met the first person made the decision to lay everyone off. You have to look at it like a distributed eventually-consistent database. In that context, everything should make sense; there was a netsplit and the consensus algorithm produced a different state in each cluster.
(There's a reason why we try not to design database like that. Perhaps there is a management lesson in there somewhere.)
(There's a reason why we try not to design database like that. Perhaps there is a management lesson in there somewhere.)
This ... it is incredibly easy to trap yourself into thinking large companies are even aware of everything they're doing in every little niche and nuance pocket of their operations. In many cases, there can be a growth area that had job requisitions approved for a high-growth investment in a small part of the company while the entire rest of the company experiences a massive layoff. This can occur both with central knowledge of the hiring in that small pocket of the company or without. Either way, the effect is the same and so is the reaction ... it just looks weird.
But I was told WeWork is a tech company. Repeatedly.
I don't know who told you that, but Adam didn't: according to him WeWork is a community company, a new category.
Just imagine what would have happened if WeWork added “blockchain” to their mission statement in late 2018.
This article on Masa from January gives some insight on what engineers were doing: https://www.fastcompany.com/90285552/the-most-powerful-perso...
tl;dr They used sensors to determine that people drink coffee in the morning and the line was long. They also used sensors to determine that small groups of people were booking large conference rooms so they made more small conference rooms.
Relevant part:
WeWork’s potential lies in what might happen when you apply AI to the environment where most of us spend the majority of our waking hours. I head down one floor to meet Mark Tanner, a WeWork product manager, who shows me a proprietary software system that the company has built to manage the 335 locations it now operates around the world. He starts by pulling up an aerial view of the WeWork floor I had just visited. My movements, from the moment I stepped off the elevator, have been monitored and captured by a sophisticated system of sensors that live under tables, above couches, and so forth. It’s part of a pilot that WeWork is testing to explore how people move through their workday. The machines pick up all kinds of details, which WeWork then uses to adjust everything from design to hiring. For example, sensors installed near this office’s main-floor self-serve coffee station helped WeWork discern that the morning lines were too long, so they added a barista. The larger conference rooms rarely got filled to capacity–often just two or three people would use rooms designed for 20–so the company is refashioning some spaces for smaller groups. (WeWork executives assure me that “the sensors do not capture personal identifiable information.”)
tl;dr They used sensors to determine that people drink coffee in the morning and the line was long. They also used sensors to determine that small groups of people were booking large conference rooms so they made more small conference rooms.
Relevant part:
WeWork’s potential lies in what might happen when you apply AI to the environment where most of us spend the majority of our waking hours. I head down one floor to meet Mark Tanner, a WeWork product manager, who shows me a proprietary software system that the company has built to manage the 335 locations it now operates around the world. He starts by pulling up an aerial view of the WeWork floor I had just visited. My movements, from the moment I stepped off the elevator, have been monitored and captured by a sophisticated system of sensors that live under tables, above couches, and so forth. It’s part of a pilot that WeWork is testing to explore how people move through their workday. The machines pick up all kinds of details, which WeWork then uses to adjust everything from design to hiring. For example, sensors installed near this office’s main-floor self-serve coffee station helped WeWork discern that the morning lines were too long, so they added a barista. The larger conference rooms rarely got filled to capacity–often just two or three people would use rooms designed for 20–so the company is refashioning some spaces for smaller groups. (WeWork executives assure me that “the sensors do not capture personal identifiable information.”)
This is it. A friend who worked in the analytics team mentioned how everything is measured and taken into account when renovating and buying new buildings. Things like exposure to sunlight, time spent at a desk, etc. These analytics are offered to FB/Amazon/big-co along with office as a service.
As someone else mentioned, cool/potentially profitable company. Just not worth 40B.
As someone else mentioned, cool/potentially profitable company. Just not worth 40B.
Do you think so? I posted this mostly as a joke.
The idea that this was anything close to being "AI" is a bit silly. The insight that there were long lines for coffee in the morning and small groups were taking large conference rooms are simple observations that one person could've made and written a report about.
The idea that this was anything close to being "AI" is a bit silly. The insight that there were long lines for coffee in the morning and small groups were taking large conference rooms are simple observations that one person could've made and written a report about.
There should totally be a cottage industry of AI snakeoil salesmen that travel the valley in colorful wagons claiming to provide cure-all data insight tonic.
This is why they are a pretend tech company. Tech roles are the company otherwise. This is part of the likely 2,000/15,000.
A WeWork recruiter recently sent me a SRE job role and I just laughed.
Why does wework even have tech roles?
Meetup.com is owned by WeWork. There could be substantial development there, although meetup.com's interface is still a confusing mix of new features that never get finished and old features that never quite go away.
Infrastructure and software are hard.
What hard problems related to software and infrastructure WeWork was solving? I can not imagine a single one. Handling check-ins? Counting number of beers consumed?
"Counting number of beers consumed?"
This spring I talked to their software engineering manager/lead at a tech meetup in Shanghai (the guy was from SF) and he said that they plan to hire tens of engineers just to analyze their beer consumption data to optimize supply.
This spring I talked to their software engineering manager/lead at a tech meetup in Shanghai (the guy was from SF) and he said that they plan to hire tens of engineers just to analyze their beer consumption data to optimize supply.
This should be top level comment.
SF is the only place in the country where you could say that with a straight face.
In fact, that guy has probably long since left and is doing his own beer analytics startup.
In fact, that guy has probably long since left and is doing his own beer analytics startup.
Being a landlord doesn’t require much in the way of bespoke infrastructure and software.
They may as well just close down now.
The morale there must be terrible. Anyone good who survives the cuts will GTFO to greener pastures.
Anyone who stays or anyone desperate enough to join will be terrible.
Good bye We, consider this my eulogy, we hardly knew ye, and may you rest in peepee.
The morale there must be terrible. Anyone good who survives the cuts will GTFO to greener pastures.
Anyone who stays or anyone desperate enough to join will be terrible.
Good bye We, consider this my eulogy, we hardly knew ye, and may you rest in peepee.
- People book conference rooms.
- Let people check in and check out.
- Let people book hot desks.
- Manage access for members, hot desks, event participants etc.
- Lots of other stuff.
At some point, the off the shelf software is no good, especially if you're looking to... build a single experience around the world for lots and lots of office buildings under your management! The software will have a lot of other admin and reporting doodads. Especially if you're trying to turn your office company into an everything company. Then the scope goes way up.
You might even start thinking about managing everything because you're a control freak... stuff like central air con control and energy use analytics across all properties... I'm just throwing stuff out there, I've never worked for WeWork.
Does this justify hundreds of engineers? It is so easy to hire more people when you have a massive war chest. Projects begin to justify themselves because you'll need them "soon enough". And if the founder pulls it off, then they're a genius! Or not.