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):
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
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
Here’s one reason Apple fought tooth and nail to disallow web payments for apps:
Because Apple’s IAP is bad in many ways, and *so many* apps will move to web-based payments now not mainly because of the 30% Apple fee, but because of how bad IAP is.
Let me give you examples:
1. Refunds
With Apple IAP it’s just not possible to do!! No, it really is not for the merchant. They cannot do a full or partial refund. Talk about poor customer support!
2. Group subscriptions. Nonexistent with IAP.
3. Paying using a non-credit card option. IAP does not allow
4. CUSTOMER SUPPORT
In general, with Apple’s IAP this is nightmare. (After you pay 30% more, mind you!)
You cannot do stuff like “we’re sorry for your trouble, would you like 3 months free or a full refund?”
5. Asking ppl why they cancel. NOPE! Not even after they cancel
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.
"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)