Honestly I was a little surprised at the cheating too. I think I was a little naive in the beginning that if you actually wanted a job you would understand that you would have to be able to write code. But some folks are in a school mentality that if you get a grade/diploma you're good, regardless of whether you understand the things required to go into that.
Having tried a number of different ways to do admissions, I can assure you doing interviews is possibly the worst.
As far as ISAs go, it all comes out in the wash. If you create a pool of ISAs and students don't get hired you may have more ISAs but the average ISA is worth less, so the only thing that matters is whether each individual student gets hired. There's no financial wizardry that can let you sell $1 for $2 in the long-run.
Yeah that's fair enough. I don't think the people cheating ever got far enough to actually effect job stats. It was pretty easy to sus out who actually knew enough to keep going. I don't fault Lambda for that, it's just the reality of any educational goal line.
For the interview thing, that's just what you were doing at the time. At the rate you were iterating, I'm sure that there's a better process now.
This is generally true but not always. As you can imagine we have loads of data on this.
If you only selected students who had been tinkering with writing code for 10 years certainly you'd be successful in doing so, but you'd also eliminate ~90% of those who we have seen become software engineers.
The only way we've found that does it well is to have people actually start writing code and see if they enjoy it. That's why we now have multiple free classes, have a free dropout period once you're in the school, and even have a three-week free trial of the school itself.
The notion that financing ISAs removed the incentives isn't really accurate.
First, most of the time ISAs are financed it's in the form of a loan you have to pay back with interest with an ISA and its repayments as collateral, or it's a sale to a neutral SPV with recourse in the case repayments don't hit a certain threshold.
In the rare instance (we've never done that) schools have been able to sell ISAs full stop, it's been at extreme discounts or based on discounted predicted likelihoods of future revenue, and if those ISAs don't repay the buyers bail and the school trying to sell them is out of business.
Edit: It's too late to edit my comment, but I noticed an error we have sold ISAs with minimal recourse not at enrollment, but at the point of _graduation_; we would sell half at an extreme discount at graduation (based on likelihood of being hired) and keep half on our books.
It's certainly true that BloomTech isn't for everyone, and that not everyone will want to become a software engineer. We try to filter for that, but it's tough.
A lot of people like the idea of making software engineering salaries, but don't particularly like building software. Then there are others that fall in love. We haven't found a great way to predict other than having people try it out.
If your point is one must understand 100% of computing before being hired as a software engineer none of us would ever be hired.
You can produce value long before you understand everything there is to know, of course, and a lot of being a software engineer is being able to problem solve on the job.
BloomTech exists to help people get to the point they can do that and create value. No school can pretend to teach everything there possibly could be to know about how software works.
I can't speak for other code bootcamps, but BloomTech is at 960+ hours for our shortest program, and considerably longer for our longer ones. And it's really hard, intentionally.
That's an absolute minimum six months full-time (and a lot of students spen dmore than 40 hours/week) with no breaks; longer hour for hour than the time in a CS degree spent on software-related topics (though those vary far more widely than most of us like to pretend).
If you eliminate context switching, have the right tooling and instruction, yeah you aren't coming out the other side a principal engineer, but you can certainly build stuff, contribute to code the right way on teams, understand data structures and algorithms enough to make stuff performant, problem solve and build a whole lot of stuff and a lot of value.
That's enough to start getting paid, and 30 years later you can continue to marvel at how you're still just scratching the surface.
> BloomTech is at 960+ hours for our shortest program
I helped run a large school for 6 years with 4,000 students/year who took an 850 hour program. Sad to say that amount of training isn't necessarily as much as it sounds.
No, that is not true. We never claimed to have an audited report until we actually had an audited report.
I asked if there was an auditor who would verify them after the fact to show that they were accurate, but we had had never claimed they were audited at that point.
Unfortunately auditors doing that is a months-long process, so we could only have them audit subsequent reports (which they have done).
I don't think the assertion that "lambda grads weren't able to get good jobs" is true.
Obviously not every single student has been hired, but our hiring rates have always been pretty good (they're better now than they were in the past), and thousands of BloomTech (we had to change our name because of a trademark lawsuit) grads have increased their lifetime earnings by billions of dollars, and work at nearly every major company you can think of.
You can see our 2021 audited outcomes report here with all of the data https://www.bloomtech.com/reports/outcomes-report. (Note: 2021 outcomes report is very recent as you have to get students graduated, give them time to get placed, etc.)
Some of it I'm thrilled about, some of it shows us where we have more work to do (or need to do better in admissions - candidly it's always a difficult balance between giving folks chance and certainty of those folks' outcomes.)
High level:
90% of those who are job seeking got hired.
Our median hired grad increased their income by $27,500 (and that's just their first job - obviously software/data science salaries shoot up quickly after a first job).
About half of our students have degrees, and half do not.
This comment got me interested, so I dived deeper into the report [0].
Learners are divided into three groups: graduated (59%), still enrolled (5%), and withdrawn (36%). Graduated learners are further divided into two groups: job seeking (63%: ~37% of all learners) and non-job seeking (37%: ~22% of all learners). Here's the definition of “non-job seeking”:
“A BloomTech graduate who has been unresponsive to outreach, has explicitly indicated they are not pursuing a technical role, or has explicitly indicated they have paused their job search.”
When we apply the base rate to the 90% rate, we conclude that 33% of those who attend the program (learners) got hired.
I see, that’s … extremely unimpressive especially if you take the median salary increase from above. And I think maybe we should take everything else this guy is saying as potentially dishonest. Not including people who stopped trying to get a job is just an absurd way to do this calculation. Imagine a clinical trial that just ignores everyone who disconues due to adverse events. These stats seem borderline predatory
We should do a better job of getting more granular on that piece, because it really does matter, but the above isn't the right way to do that math to answer the question prospective students have, and is misleading in the opposite direction. The outcomes report is directed at prospective students who want to understand what will happen to them if they attend the school and look for a job.
You have to remember that (for this outcomes report) nearly every student uses an ISA under which no one is required to pay us unless/until they get a job using the skills they learned. There are a number of people who attend never intending to switch careers, a (large) number who ghost us the day after graduation, and a (large) number who get a job but don't tell us until we get tax returns (so we learn they were hired only after this outcomes report).
Our team works their asses off to work with these students, and is doing everything they possibly can. Slacks, calls, texts, emails, some of which are auto-generated from me personally, and in some cases even physical mail, to try to get them to work with us. If they respond _in any way at all_ with anything other than something that equates to, "I don't want a tech job" they are job-seeking in the outcomes report. We have built tooling to make applying to jobs easier, we find jobs that you should apply to for you, have an outreach generator where our team will write emails to hiring managers for you, and more recently even what we call "job search takeover" where we work with students on resume/portfolio/job criteria in advance, and we will actually do all of the work to fill up your calendar with interviews.
Students who look for a job in any way whatsoever get hired at a very high rate. In my view, if you're a prospective student, that's the information you actually want to understand. The fact that there are a number of students students (most of whom are using ISAs) who never intend to look for a job or don't look for a job is a fair indictment of our business model, but not a fair indictment of the quality of the school or the likelihood of getting hired.
So how should we treat that in an outcomes report? If you're a prospective learner do you want to know about the hiring rate of the people who ghost us or don't intend to look for a job, or do you want to know the hiring rate of people who map to the profile of what you expect to do?
If anyone has ideas of a better way to slice that data to convey the best information to a prospective learner, I would love to hear it.
Hmm, perhaps. I actually don't spend as much time on social as it would seem. It takes very little time to dash off a tweet. It's almost like a background process that runs in my mind, and it helps me think through things and shave the edges off of my thinking.
There's also probably a dopamine hit that I get from it that I'm not as aware of being a driving indicator, but I don't believe it negatively impacts my ability to run the company.
I wouldn't say I was cheering; I was simply acknowledging that, though difficult, Twitter certainly has too many employees for the amount of revenue they're bringing in, and I am skeptical of claims that Twitter will cease to function as they go from 8,000 employees to whatever the new number is (2,500 seems to be the latest)?
There's certainly internal knowledge that is lost in a transition of that kind, but the amount of money Twitter was burning makes no sense, and while reducing numbers of engineers is risky (and complex systems require more engineers than most people assume), I completely believe that Twitter will be able to sustain the technical operations and move quickly in shipping product with a mere 2,000 engineers.
> Twitter certainly has too many employees for the amount of revenue they're bringing in
Twitter was profitable (pre-Musk acquisition, and ignoring a one-time lawsuit settlement that wasn't an ongoing expense); it objectively did not have too much headcount (or other recurring expenses) for its revenue, prior to the added expense burden of debt service costs it was saddled with by Musk as part of the acquisition.
Their recent failure to properly execute payroll in some European jurisdictions, and the fact that they apparently no longer have sufficient account managers to even stay in contact with major advertisers at a time when they are trying desperately to actively manage those relationships and maintain them despite the distrust the takeover has engendered seem to be signs that the cuts were to deep on the non-technical side for the operation that Twitter is trying to run; I don’t see any real analytical reason to reject that the same is true on technical side.
(And that’s before considering that the reductions also seem likely to have broken both contract and, in many jurisdictions, labor laws, and legal costs associated with that are starting to mount, with at least one case already lost.)
You were cheering. You’re still cheering. And you’re doing it while you’ve had continuous layoffs of your own staff that have put everyone who works for you, or anyone unfortunate enough to be part of your predatory boot camps, in jeopardy.
I don’t take any joy or schadenfreude from your failures. Real people’s lives are involved and it genuinely makes me sad.
But glass houses dude. Glass houses. Maybe when you’re own company is falling apart, you should refrain from publicly commenting on someone else’s.
I was not cheering, and my opinion is consistent; as money becomes much tighter companies have to rightsize themselves to the amount of revenue coming in. This is true across Silicon Valley and it is true of us.
Why do you need to comment at all, I guess is my question. Why not spend the time trying to run your own business rather than callously argueing how over-staffed Twitter was. Why does that matter to you? You don’t work there. You aren’t one of Elon’s investors. Why not just keep your thoughts to yourself, the day 3700 people lost their jobs, instead of pontificating about how a company needs to rightsize itself? Especially when you had to know you were weeks away from laying off half your remaining staff.
Someone else mentioned you need to spend less time online and you argued that you’re not that online and that the dopamine rush is worth it for you. Fine. Deal with it in therapy. But know that it looks incredibly tone deaf that the day you lay off half your staff (and the day after), you’ve spent hours debating yourself and justifying your actions on HN and shitposting on Twitter.
[I am explicitly not weighing in on whether this gambit will work or not. Could go either way, there is a lot of luck involved in business.]
> Twitter certainly has too many employees for the amount of revenue they're bringing in
This doesn't make any sense given that Twitter's revenue per employee (RPE) was roughly double that of well-run companies like Oracle or SAP and in the ballpark of EA and Adobe. This metric is a red herring currently being used to trim workforces. Which, that's the game and this is where we are in the cycle. But the ratio of revenue:employee doesn't tell the story here.
Granted cost structures and business models are different across these firms, and Twitter likely could have cut some staff (they all likely will in coming months now that it is timely to do so). But that's exactly the point here: the Twitter ratio between employees and revenue works fine at other companies, and has done so for a long time. Expedia has built a sustainable business with a lower RPE than Twitter, and it is similarly a pure-play Internet company. From a strictly financial perspective, it's equally likely that there were other levers that could have equally been tuned to fix Twitter's persistent problems.
IMHO the bigger problem was they are tooled as a high-growth company, but they were not growing fast. Even a modest bit of consistent growth, say 15% y/o/y, sustained for years, would likely have ameliorated their problems. Perhaps they have a large fixed cost to running Twitter, and they simply have not scaled the business enough to make it worthwhile yet -- could they double their business from the pre-acquisition base while only increasing staff 25%? That would be a good business! But I would guess the fundamental issue was that they are tooled for hypergrowth that is likely not on the radar.
Big staff cuts, modest (but smaller) revenue drops, then aiming to grow at a slower, sustainable pace is pretty stock PE stuff (although they typically try to pay at or below market instead of much higher than market). Can only assume people who see this as genius have never observed PE work.
Twitter was continually on the cusp of breakeven and would have lost money the quarter ahead of Musk's takeover had they not sold MoPub. Even before Musk took over they had planned on a 25% headcount reduction.
Their revenue per employee pales in comparison to other companies of its ilk, and I think we would disagree whether SAP and Oracle are well-run companies :)
> Twitter was continually on the cusp of breakeven
This also fits the model where they have a large relatively fixed cost base to operate, but could reap profits if they reached a larger elusive size. Again -- my hypothesis is they are tooled for hyper growth and the business has not been able to deliver that. Giving up on high growth and cutting to profitability is part of the stock PE playbook and definitely makes sense in the absence of strategies for generating massive growth.
> we would disagree whether SAP and Oracle are well-run companies
Interesting perspective, I meant it in the sense that they have operated for decades in competitive industries while making oceans of real profit for shareholders over that period. Most of us would be fortunate to run companies as poorly. :-)
> Interesting perspective, I meant it in the sense that they have operated for decades in competitive industries while making oceans of real profit for shareholders over that period. Most of us would be fortunate to run companies as poorly. :-)
Very true, but Twitter has lightning in a bottle captured the way few other companies do.
Went "unempathetic" mode. He didn't have to do what he did and in the way he did. You were cheering for him instilling fear in the remaining employees.
There are a few edge cases where folks will be working through that period and contract with us afterwards in different/new roles, but impacted employees are not expected to work with us during that period.
If you were actually to commit fraud regulators can come for you whether you register or not. The act of registration is simply to make it easier to tell regulators what is happening.
Having tried a number of different ways to do admissions, I can assure you doing interviews is possibly the worst.
As far as ISAs go, it all comes out in the wash. If you create a pool of ISAs and students don't get hired you may have more ISAs but the average ISA is worth less, so the only thing that matters is whether each individual student gets hired. There's no financial wizardry that can let you sell $1 for $2 in the long-run.