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:
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.
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).
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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And yes, Sonos used to have a great software experience.
I got my first Sonos around 2019 or so I think - and the setup and tuning were very nice (positioning speakers in a room for best performance.) Worked well for me at least.
Major banks skipped due diligence on the deal when providing massive loans to the world's wealthiest person buying Twitter for $44B, assuming they would make a quick buck by selling on these loans.
But they cannot sell it on and make money on it?
The full story by WSJ:
It's hard to feel sorry for massive banks that don't make the quick buck they expected to do, because they loaned for an objectively terrible deal? (Twitter was sold for 2-3x the value of Snap, despite fewer users, similar rev)wsj.com/tech/elon-musk…
FWIW Snap today:
- Has ~2x as many users as we can assume X has (Snap: more than 800M MAU)
- Has ~2x as much annual revenue (about $5B)
- Is worth $15B
... meaning X would be valued no more than $15B today, most likely.
It's notable that coding assistants like Copilot, Tab9 and many others are available in most IDEs... save for XCode.
This means we have an unlikely "control group" to determine if these AI assistants make a major difference in coding: native iOS devs vs everyone else!
Assuming these coding assistants provide a meaningful and long-term productivity boosts: teams doing web and Android development using these tools (e.g. via Jetbtains or GH Copilot) *should* be meaningfully more productive vs iOS folks.
Interesting if we'll see major differences
The reason for this is how XCode seems to be deliberately hostile for extensions: and so the inline coding extensions that IDEs like Visual Studio and Jetbrains IDEs support (and that AI tools use) are not available for XCode.
Outside of coding and customer service, what are areas where GenAI / LLMs result in very clear productivity gains or business gains, without a deterioration in the experience for customers?
These are two areas I currently see as "yeah, GenAI actually works here, not just a fad"
Funnily enough, even when Sundar Pichai was asked about GenAI, he seemed to only list these two examples. Two weeks ago he said:
"There are pockets, be it coding, be it in customer service, et cetera, where we are seeing some of those [GenAI] use cases seeing traction"
The "et cetera" is what I'm interested in.
Coding is a fantastic fit for GenAI:
- Simple grammar (simpler than human language!)
- Huge amount of extremely high quality training data (code that compiles!)
- Hallucinations can be limited by compile/test
- Humans review output
Here is an EU regulation that surely massively accelerated online businesses:
The right to return any physical goods purchased online within 14 days.
Here’s why (my recent story with a faulty vacuum cleaner that will make me only buy stuff like this online, even from a shop:)
I needed a vaccuum cleaner while in Hungary. So I walked into a retailer shop and bought a cordless one.
The vacuum cleaner broke after 7 days (no charge.) Took it back to replace it… but was told that in-store purchases are not eligible for the 14-day return. Only online ones
So now the retailer is sending my brand new vacuum cleaner for repair. I have no appliance for 2-3 weeks while they attempt to repair what should have not been broken.
There is zero point as a consumer buying appliances in-person: thanks this 14-day policy not applying to them.
Delta (by regulation) needs to stand in for the losses and cover them for passengers.
The interesting parts of the lawsuit will be:
1. What contracts did Delta strike with CS/MS in case of them causing financial damage to their business, like now?
2. What does the judge say?
FWIW suing Microsoft seems to be pointless to me. Liability stands with CrowdStrike: they very clearly caused the damage. Just me, but I cannot see a judge come to any other conclusion.
Ship changes that run in the kernel at your own risk, as we will see.