London used to be the tech hub of Europe before Brexit (VC investment, # of tech positions, big tech presence etc). I lived/worked there for 5 years and it was great.
Still a good place... but Brexit is making EU engineers explore options outside the UK like this, one at a time:
As someone who has seen London tech at its prime, I think one of the biggest misses of the current UK government is not doing more to "retain" the London tech hub.
Dublin, Amsterdam, Barcelona, Berlin and other EU "hubs" are slowly, but surely pulling London EU folks away.
My response to "what is your take on choosing the next city?" was this:
"What will the next EU* tech hub be?"
*taking the UK out of EU.
My take: it should have been Paris... if they capitalized on it, and changed a bunch of policies (which they don't and won't).
Amsterdam & Dublin are the biggest winners, and plenty other gainers).
And here's an inbound DM on why Paris (sadly) is a place that will struggle to attract tech talent. Even though it has all many characteristics in location, size, population, transport to be a tech hub.
The language for tech is English, and in Paris you *need* to learn French.
A person weighing in (over a DM that I edited to remove personal details) on Barcelona.
And on how you should expect to (eventually) learn the local language either way. Which I agree with - I'm slowly improving my Dutch as well in Amsterdam.
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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.
"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)
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.
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!)