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

Apr 22
Every now and then there's this prediction of when we will see the first one billion dollar company ran by one person...

... and I think back to how in 2016 there was this one product inside Uber that had crossed a $1B annual run rate that had a total of one dev allocated to it.
And half a data scientist (part-time).

It was cash.

Funny how headcount games can work inside fast-growing companies, especially when the product is a stated goal of what a founder does NOT want to support (but turns out to be essential!)
I only have second-hand details here but the story was along the lines of not being able to get official headcount (because when Uber was founded, no cash and no tipping were table stakes).

It only got funding after crossing the $1B landmark.

Was pretty incredible internally!
Read 4 tweets
Apr 11
From an eng manager at a full remote company:

"We just fired an engineer after ~15 days on the job who lacked basics skills on the job but aced the interview - clearly, using cheat tools.

He admitted to how he did it: he used iAsk, ChatGPT and Interview Coder throughout"
(I personally talked with this person and know them well)

This company hired full remote without issue for years: this is the first proper shocker they have.

They are changing their process, of course. In-person interviews, in-part likely to be unavoidable.
As a first change, they have started to be lot more vigilant during remote interviews, and laying some "traps" that those using AI assistants will fall into.

Just by doing that they think about 10% of candidates are very visibly using these (they just stop interview processes with them)
Read 4 tweets
Apr 5
I am coming around to why MCP is so impressive.

For one of my side projects, I used to have to log onto my database admin (PgAdmin) to query stuff.

I connected an MCP server to Postgres and can "talk" with my database (and data!)

An uplevel in my productivity + ease of work.
Let me give an example of how cool this is:

I have a service that sends our promo codes for Perplexity and Kagi that paid newsletter members can claim:

I can now "talk" with the data from my IDE to get all kinds of details!

Was impossible until now newsletter.pragmaticengineer.com/p/free-kagi-an…Image
Lots of questions on "which MCP did you use?"

I used Windsurf, but would work just as well with Cursor (and maybe VS Code as well now). Under the hood its all the same!

When setting up, took an hour to get it to work, thanks to my local npm + npx being out of date. Updated it and then worked fine.

The Windsurf MCP interface: just set up the Postgres one. But again behind the scenes its "just" an npm package that you can invoke from the command line as well! Which is the beauty of itImage
Read 6 tweets
Apr 4
I'm starting to understand why there are company eng blogs not worth reading.

When doing a deepdive on an interesting company in @Pragmatic_Eng, we do research, talk with engineers, then share the draft back for any minor corrections. Usually it's a "LGTM." But sometimes:
Sometimes the Comms or Brand team gets actively involved, and mistakenly assume they are the editors, and attempt to rewrite the whole thing on how they would usually publish it on eg their blog.

Every time, it's a disaster to see, but also amusing. Because a good article becomes SO bad. Interesting details removed, branding elements added etc.

(We never allow edits - and if they insist we simply publish nothing, throwing out our research. This has not yet happened, but it might be the first time it will)
Btw here are some of the deepdives we did. In most cases, it was a "LGTM"

In other cases, we rejected edit attempts... because its not their engineering blog!

(The bigger the company the more sterile those edits can become, in general, btw.)

newsletter.pragmaticengineer.com/t/engineering-…
Read 5 tweets
Apr 4
One thing that really bugs me about VCs and others projects claiming how AI will mean many devs redundant because smaller teams can do more with less: is ignoring the last.

Some of the most impactful / successful software was built by tiny teams in the 80s, 90s, 2000s. Like:
Microsoft’s first product in 1975 years ago: 2 devs

Quake in 1996: 9 devs

Google’s first search engine in 1998: 4 devs

We could go on.

Small teams with outstanding people doing great things happened before GenAI and will happen after as well (and without as well!)
What happened in all cases was the product got traction and there was more stuff to do that needed more outstanding people! So they hired more standout folks

The same will happen with GenAI: companies taking off thanks to using AI tools will hire more devs who can help them get more stuff done *using the right tools*. Some of those tools will be GenAI - but some of it not!
Read 7 tweets
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

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