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Gergely Orosz Profile picture
@GergelyOrosz
Nov 7, 2021 • 8 tweets • 4 min read • Read on X
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The 2021 Talent .io salary report is out. These reports work with the data they have, and it's clear that high-paying tech companies don't use "Europe's largest tech recruitment platform" at all, resulting in data that is off from reality.

A thread on why these reports are off:
1. Access to data. Looking at the Amsterdam data distribution, Adyen, Booking, Uber etc all don't have their data here. They all pay €90K+ for seniors in *base salary* - we'll talk about the rest. Uber and Booking €110K & above:
2. Total compensation vs salary. These reports focus on salary, but the highest paying companies often pay a lot more than just salary. E.g. at Uber I had years when my stock vesting that year was above my €100K+ salary. My bonus target was €22K as a senior engineer.
3. This report confirms what I have been saying: there are ranges invisible to most recruitment companies and employees on Tier 2, and especially Tier 3 ranges:

Read the full article on the trimodal nature of tech compensation:
blog.pragmaticengineer.com/software-engin…
4. So where do you get better data? You ask around people you know. Go on Blind (the app). Check out levels.fyi. And I'm building techpays.eu that already has over 500 Netherlands/Amsterdam data points.
5. My next newsletter issue will be about how to find your next opportunity as a software engineer/engineering manager, including a list of (within inner circles) known companies that pay towards the top of the market.

Subscribe here: newsletter.pragmaticengineer.com
6. To recap:

These reports are good at showcasing #1 (Tier 1) compensation. They don't tell you *anything* about Tier 2 and Tier 3. Those companies use in-house recruiters and don't recruit through these platforms (or don't share their data at least).

blog.pragmaticengineer.com/software-engin…
And the full survey: …g-pictures.s3-eu-west-1.amazonaws.com/Salary+Report+…

Clearly they put a lot of effort writing the survey: but be very, very, very wary on basing compensation on this. You won’t be competitive even in Tier 1 if you do. Even the Tier 1 market has moved up the past months.

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More from @GergelyOrosz

Gergely Orosz Profile picture
Mar 14
A good reminder why you can pick up GenAI - and you probably should. Real story:

Small company, 5 devs. Last time they hired was 12 years ago. AI comes out: company wants to add AI feature. But they don't have the expertise. So hire an AI agency.

Agency spend 3 months planning:
After 3 months, the present a very complex architecture to build: several services multiple databases, SageMaker models etc, using a language a company is not using (Python - this is a Java shop)

It will take 6-9 months to build

Operational costs will be higher fort this one feature than all of the SaaS operational costs for the company!
Lead dev who is close to retiring (and has been at the company for 25 years) thinks "this cannot be right, surely."

So he says "screw it." Reads up on GenAI, builds a few prototypes and tells company to drop the agency: they will build it in ~3-4 months, much faster and cheaper.
Read 9 tweets
Gergely Orosz Profile picture
Feb 19
Klarna was the company that went all-on replacing customer support with an AI bot and went on to brag about the cost savings.

Now they are reversing course.

Easy to see more companies blindly replacing quality customer support with a worse AI implementation will follow... Image
Back when Twitter was full of influencers declaring the end of customer support thanks to Klarna I did something few people did:

Signed up for Klarna, bought an item, and used the bot.

I was NOT impressed. At all.

Called that this was... very basic. blog.pragmaticengineer.com/klarnas-ai-cha…Image
A year ago I wrote this, and I still stand by it.

You probably don't need an AI bot when you think you actually need an AI bot...

blog.pragmaticengineer.com/klarnas-ai-cha…Image
Read 6 tweets
Gergely Orosz Profile picture
Feb 16
"Leetcode-style / DSA / algorithmical interviews are useless and don't measure what's really expected on the job. They are also inefficient, and companies using these are hiring for the wrong people."

Heard this SO many times.

The responses almost always miss the point.

I'll do a longer post one day, but a few thoughts:

1. YOU are not Big Tech. You probably don't have 1,000+ qualified applicants show up for an entry-level job posting and 100+ for a senior posting - in just a day or two, without advertising it

2. When a company gets large enough combined with #1, the game becomes not reducing false negatives but reducing false positives to zero

3. "LeetCode-style interviews are BS and don't measure what you do on the job." Yes. This is part of the reason. Guess what else is BS at Big Tech? A lot of stuff? Do you think people who are unwilling to put up with BS (that has historic context and can be internalized) would last at these companies? No: they would quit shortly or be pushed out as they refuse to do what everyone else does. These interviews conveniently self-select for people who can and do put up with BS

4. Career ladders. There is a notion that a Principal engineer should be as good or better than a new grad in every area - including algo coding. Like it or not, it's how it is

5. Technical managers. Many of these companies expect managers to pass the same bar. Like it or not, again: the reality is at these places many (probably all) line managers can code, and can do it very well.

6. Scalability of process. Have you ever had the challenge of onboarding 120 new interviewers in a month? Every quarter? These companies have this problem.

7. If it ain't broken: don't fix it.

Look at the business results of Big Tech. If the interview process would be broken, it would show up in eg shipping slower and being outcompeted by competition etc. In reality: Big Tech is more nimble than ever. E.g. Threads, Copilot, Gemini etc. Their interview process works *for them*

8. You are probably not Big Tech and don't have to solve for this very distinct set of problems.
Remind me how Big Tech hiring is broken when they built a new social media network in 6 months from idea to launch. This was 2x faster than e.g. Bluesky (a nimble and amazing startup btw)

Threads story: newsletter.pragmaticengineer.com/p/building-the…

Bluesky story: newsletter.pragmaticengineer.com/p/bluesky

Via @Pragmatic_Eng
The problem is not how these very large companies interview: they've done this for a long time, and will keep doing it for a long time.

The problem is mindlessly copying this approach for companies that would want to optimize for other stuff and don't have the same situation. Like they don't have a massive number of qualified candidates streaming in the door. Or they might want to reduce false negatives as well. Or they are willing to invest more thoughtfulness into a different interview process as they don't need to worry about scaling it like a large company does etc.

Plenty of smaller companies don't follow the algo interviews, btw. Of course it all comes with tradeoffs: e.g. those companies will often have to invest a lot more effort per candidate / update interviews more frequently when questions leak etc.

Don't forget the goal of any interview process is to balance between getting enough signal to confirm this person will be a stellar new hire - while minimizing the process needed for this (and the time investment + annoyance for the candidate).

The most candidate-friendly interview process is this:

"Oh, Jenny here says you were superb to work with. Here's an offer, want to join us?"

No effort for the candidate, but the company might be taking a risk (depending on the quality of recommendation) plus this process excludes anyone who has not worked with someone at the company.
Read 6 tweets
Gergely Orosz Profile picture
Feb 16
I rarely do predictions but this is an easy enough one to make:

Big Tech will bring back onsite interviews for the final round of interviews, flying in candidates.

When you pay top of market, AND do hybrid work, in the age of invisible AI helpers, remote interviews are a risk
A company expecting staff to work in-office 2-3 days per week will increasingly prefer in-person (final round) interviews.

If they pay top of market: this itself will be enough for most candidates to do it. The payoff is high enough, after all.

In-person interviews also negate all "cheating" that can be done with AI. It also means existing interview formats (eg algo interview, sytems design etc) don't need to be changed to remain as effective as before!
Previous research via @Pragmatic_Eng on GenAI changing tech interviews (given most engineers use these for work already, of course they are changing interviews as well!)

newsletter.pragmaticengineer.com/p/how-genai-ch…
Read 4 tweets
Gergely Orosz Profile picture
Feb 13
Don’t fall for speculation like this.

Software developer job postings are back to where they were in ~2019, following the COVID boom (and zero interest rates!).

You know what else has the same pattern? Banking jobs. Marketing jobs. Heck, HR jobs: Image
Banking and finance jobs:

The story is not how software developer jobs are disappearing because of eg AI.

The story is how there was an economic boom 2021-2022, massive hiring, and now a correction.

A lot to do with zero interest rates! More: newsletter.pragmaticengineer.com/p/zirpImage
Retail jobs.

Using this one graph you could tell the same story of how “retail jobs are dying” (looking at the clear trend of downwards job postings)

Except there’s noting about AI tools be told there…

If all graphs look the same: consider it’s maybe the economy? Image
Read 4 tweets
Gergely Orosz Profile picture
Feb 7
Building a profitable company as a commercial open source one with a permissive license feels more challenging these days.

The company needs to make money: which it usually does by selling a managed version of the software.

But here’s the catch: (cont’d)
1. If the open source version of the software is standout and easy to operate: users have little to no incentive to choose the managed version

2. If the license is restrictive, competitors can simply undercut pricing. They don’t need to invest in development of the software much
Open source is a wonderful distribution method. Devs jump on permissive open source projects because… well, permissive license!

It also means that in case of a restrictive relicensing: a permissive fork can be born (see eg Elastisearch vs OpenSearch; Redis vs ValKey)
Read 7 tweets

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