Gergely Orosz Profile picture
Oct 9, 2021 12 tweets 3 min read Read on X
There’s a debate on whether 10x software engineers exist.

They do: I’ve seen several of them.

And their existence freaks the hell out of me. 5 examples of 10x engineers and why you should be afraid when you see one:
1. The Move-Fast-And-Leave-Behind. A dev with a hacks mindset at a scaleup. They get shit done 10x faster than the engineers who that take this (literally) shit over when it needs to scale, try to reverse engineer it, but ultimately have to toss and rewrite the whole thing.
2. The That’s Trivial To Finish. Someone w many product-minded traits blog.pragmaticengineer.com/the-product-mi… amazing at prototyping and telling the non-technical manager they’ve done 90% of the work, and the other devs should have no problem finishing the last 10%. Which then takes 10x as long.
3. The Only Non Quitter. A company a terrible eng culture and just as bad codebase which oversells itself. Devs quit all the time and the new joiners struggle with everything. Save for TONQ who gets stuff done. Obviously the most tenured dev, and the only one lasting >2 years.
4. The Debugging Machine. A place with a codebase w no tests or documentation. New joiners tend to break everything and TDM needs to be called in to save the day. An engineer who has been around for years, though refuses to ever document/share any of their well-earned knowledge.
5. The Story Point Hoarder. A company where productivity == story points shipped. A tenured engineer who figured out how to make sure every second sprint they claim 5-10x as many story points as most other team members through cherry-picking work, optimising for these points.
So yes, 10x engineers do exist. They live in a mostly unhealthy engineering environments allowing for 10x behaviours.

If the above examples proved anything it’s how we should not ask: “how can we have more 10x devs?”, but answer “why are most our devs at 0.1x productivity?”
10x devs share the trait of being tenured at a company, and being perceived 10x as efficient as most new joiners.

Which begs the questions:
1. Why does an engineer need years of work at the company to get productive?
2. Is perception == reality?

Those are the 10x questions.
2 more archetypes:
6. The Reinvent The Wheel Dev. One of the first engineers at a startup who decides to reinvent the wheel. Writes a custom SPA framework, with layer, MVC abstraction. Then gets everything done 10x faster than new hires (who they label as “not smart enough”)
7. The Stupidly Hard Worker. Typically someone who is also #1 or #6 at some level. They work 12+ hour days, also through most weekends. Management loves them as they’re clearly devoted to the company, and ignores any complaints because this hard work & perceived 10x output.
Finally, my observation on what a highly productive engineer can look like (who I would not call 10x):

blog.pragmaticengineer.com/the-cheetah-so…
The subtle hints of what “scares” me is a bit too subtle so let me put it clearly:

It’s not the stereotyped people. They’re all hard workers and get positive feedback.

The scary thing is the environment they operate in, where leadership doesn’t even know/realize the problems.

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More from @GergelyOrosz

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
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
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
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
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
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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