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

May 28
Something I hear very little talk about:

How AI coding tools are so much LESS useful when used on existing, large codebases at work (with custom frameworks, conventions, coding style etc)

... compared to doing greenfield work or side projects

So common for me to hear: "yeah I love it on my side projects, but at work it's 'meh'"
I'm getting details talking with devs at the likes of eg Google, Meta, Microsoft: the companies building some of the best AI coding tools out there!

And yet, for their existing codebases, the usefulness is marginal. Mostly for autocomplete (that has a higher miss rate than for greenfield)
And yes, surely there are workarounds. I just don't hear much of these used or successfully used!

Point is almost all success stories I hear are greenfield ones or small projects, or ones started with these tools

Using on larger one a bigger challenge

Read 5 tweets
May 25
This blog is SO good at pointing out what should have been obvious about AI for coding (Copilot and others)

These tools are good for re-creating whatever they’ve been trained on.

They are not what will create the next, better generation of frameworks, libraries, technologies. Image
Full blog - you should *absolutely* read it

I also find these AI tools helpful when it’s doing the routine task I’ve done many times and can do it with eyes closed

But… it’s not helpful when I want to build something GREAT that is elegant, and better than beforedeplet.ing/the-copilot-de…
Anyone who tells you otherwise hasn’t built software from scratch that is best-in-class

And likely things software is all solved by now

But it’s NOT

Those who invent the next chapter I cannot see doing it relying mostly on AI. Quite the opposite
Read 9 tweets
May 16
I am hearing SO many stories about people realizing coding with AI tools (aka “vibe coding”) is a game changer after “reviving” an old side project or idea on the side and making so much progress

But… while I often hear the excitement on starting: not hearing “finished” often!
Almost like these tools were amazing at making rapid progress at first… but it still takes a ton of effort to finish things and feels like most people go back to leaving side projects unfinished (even if in a more advanced state?)
FWIW guilty as charged

I got a bunch of side projects “revived” and was amazed at how fast it was

Then I just… kind of let them on the side? Turns out the reason I don’t touch them is because… they are just not a focus. Even tho it’s less effort now: still effort!!
Read 4 tweets
May 13
Question from an ex-Uber engineer:

"I got this reachout from recruiting Uber. I responded that I'm happy to discuss why I left (so Uber can learn from it) but not planning to return.

I got ghosted. Why? They asked, after all!"

Here is exactly why (continued): Image
It's b/c you mis-read the email (which is so easy to do!)

It sounds like a "we'd love feedback and improve", right?

WRONG

This is a recruitment email, using Uber alumni as a high conversion channel.

It's from a sourcer: who only has one goal: get ppl in the hiring pipeline! Image
(Btw I got the same email - likely sent out to ex-Uber folks who have left for more than eg a year, in certain regions)

The "Sourcer" role if laser-focused on bringing in candidates to roles currently hiring.

If Uber wanted feedback, it would come from HR

A sourcer will not do a call with someone they know has a 0% chance of entering the hiring pipeline!

Check the signatures of the emails next time and you'll know what the goal of the person sending almost certainly is
Read 5 tweets
May 6
Can we just mention what practically everyone using Cursor and Windsurf uses/pays for as version control again

And who owns that service
In case you missed it: it was Microsoft who voluntarily cannibalized their very very profitable Visual Studio business and released VS Code for free. And made it trivial to fork. VS Code + forks probably account for 80%+ of the global dev market in usage

Why did they do it?
This was clearly on purpose from Microsoft - give up one revenue generating area to keep winning in a much bigger one

Not squeezing all lemons is an underrated and very smart strategy, as @jakozaur puts it

Also why NVIDIA is “losing” in AI models to eg OpenAI, Anthropic etc
Read 4 tweets
May 3
I’m tired of hearing the “AI is killing tech jobs” narrative. Here is data on “top” tech companies and startups hiring.

The last 2 years (since GenAI went mainstream and AI coding tools evolved greatly) we’re seeing more hiring from them. Below the pandemic peak ofc Image
Data source: @Pragmatic_Eng

newsletter.pragmaticengineer.com/p/the-reality-…

And before you show me the tech jobs going down graph that goes viral every week: know that most sectors see the “decline in jobs” from the pandemic peak: blog.pragmaticengineer.com/software-engin…
And this is not about denying the impact of GenAI for tech jobs. We will see smaller teams do more (already are). More demand for “top” software engineers, and most likely less for entry-level and “average” talent.

We don’t know (yet) if we will see an explosion of smaller teams/companies and if we’ll see a demand surge to take over/maintain “vibe coded” businesses as they start to scale
Read 4 tweets

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