>Is it really that 10x performers exist, or that 0.4x performers are abundant so 2x performers look like 10x performers?

Performance is relative, so if the norm is 0.4x, that's the actual "1x" base to just 10x programmers by, even if it's below what a 0.4x programmer could potentially achieve if they really tried.

In other words, if most devs are underperforming due to complacency, lack of motivation, etc., that should also factor in in the 10x programmer calculation.

So, 10x doesn't have to be "10x as good when both are 100% motivated" just "10x as effective" is enough (even if it's because they are more motivated and not actually more intelligent, knowlegeable etc).

The norm can still be 1x and the number of 0.4x can apparently also be too abundant for comfort.

>There is also a significant variation in how the same person performs across multiple tasks.

Not only that, sometimes one individual can engineer things 10X better than at other times.

>Do these two engineers have the same experience with the technology at hand?

No, one has 10x the experience.

>How familiar are they with the system they're working on?

Very, one is just 10X more familiar.

>Do they have the same ability to make decisions on the go?

No, one is a 10X better decision maker.

>How easily can they get help?

Both easily, but one of the two only needs help 10X less often.

What I'm getting at is if our 1x is defined by average or median, essentially. Of course without actual data it is impossible to say.

Abstractly it's nice to know.

But practically does it really matter?

Even if we knew the case, one can't just e.g. whip 0.4x into 1x, so a 2x remains a very valuable 2/0.4 jump.

> Even if we knew the case, one can't just e.g. whip 0.4x into 1x, so a 2x remains a very valuable 2/0.4 jump.

This is pure speculation, which is why actual data would be useful. Is a measured 0.4x performer that way for innate reasons or is that something which some combination of training and mentoring, better tools, streamlined environments, etc. can help with? — or is the way that's measured even valid? I've seen a few cases where someone got flack for being slow until wider perspective showed that they were the only one solving the customer's real problem because it turned out that what they were doing was more complicated than it looked and/or the other guys were “solving” it in ways that required lots of ongoing maintenance.

>Is a measured 0.4x performer that way for innate reasons or is that something which some combination of training and mentoring, better tools, streamlined environments, etc. can help with?

For this or that individual (as per your example of "a few cases"), maybe.

For the majority do you think there will be something that hasn't been tried until now, what with all 2000 methodologies of management, team structure, company culture, development methodologies, tooling, agile, waterfall, and what have you, that will suddenly make a difference?

I think there are plenty of things which make a difference — for example the training and mentoring I mentioned — but the methodology point touches on the problem that they're neither cheap nor easy and most places are unwilling to invest in them. Very few companies which “adopt” something like Agile manage to substantially transform their culture because that's hard and it's a lot easier to make an announcement, do Agilefall, and avoid hard conversations.

Having worked at really high quality startups, and low-quality companies, this is a real thing.

0.1x developer might be a 10x developer that has given up because the build or management is fundamentally broken. Working more will just lead to burnout.

a 0.1x developer might be someone who at some point was very talented but now has no clue, but enough savvy to stay on as a lead/architect/senior

a 0.1x developer might not be qualified, but was hired because the company paid well below market rate.

Many reasons... A 10x is motivated, intelligent, and in the right place at the right time.

The Survey cited in Peopleware says that it is a 10x difference between the best and the worst performers. The best performers were something like 2.5x the average performer, as measured by time to complete a specific coding task in the 70s.

Office environment was a factor in performance.

Peopleware is 30 years old though. Back then very few decided to become programmers. Today when everyone flocks to the field chasing money and you have several orders of magnitude more programmers the ratio could be very different.

Don’t forget that we have -x performers.

There are some programmers who are worse than nothing happening. So a 10x looks better by working accords the averages of all the 1x, -1x, etc.

On the Net Negative Producing Programmer - https://wiki.c2.com/?NetNegativeProducingProgrammer and the referenced article from there http://pyxisinc.com/NNPP_Article.pdf

That article starts out with...

> We've known since the early sixties, but have never come to grips with the implications that there are net negative producing programmers (NNPPs) on almost all projects, who insert enough spoilage to exceed the value of their production. So, it is important to make the bold statement: Taking a poor performer off the team can often be more productive than adding a good one. [6, p. 208] Although important, it is difficult to deal with the NNPP. Most development managers do not handle negative aspects of their programming staff well. This paper discusses how to recognize NNPPs, and remedial actions necessary for project success.

> Researchers have found between a low of 5 to 1 to a high of 100 to 1 ratios in programmer performance. This means that programmers at the same level, with similar backgrounds and comparable salaries, might take 1 to 100 weeks to complete the same tasks. [21, p. 8]

Source 21 is: Shneiderman, Ben Software Psychology: Human Factors in Computer and Information Systems (Cambridge, MA: Winthrop, 1980)

https://www.amazon.com/Software-psychology-computer-informat...