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I find that a better signal is simply the quality of the tool or technology. It's like surfing. Some people want to see hundreds of surfers on the wave before

I find that a better signal is simply the quality of the tool or technology. It's like surfing. Some people want to see hundreds of surfers on the wave before they start paddling out. That's fine. There's nothing wrong with that. But I personally believe that a better way to surf, especially when it comes to technology which tends to have short cycles, is to learn how to spot the wave as it builds, while it's still a swell, before it breaks. I've seen time and again that there's incredible value to be had if you can learn how to do that. One of the best examples of this value being that you're able to hire really talented people, because they form the critical mass at the beginning of a successful wave. Once the larger corporates come in, this advantage disappears.

Cyph0n 5y ago
I think the challenge would be in defining "quality" in a way that allows you to compare between multiple different technologies. If the definition ends up aligning with what large companies look for when adopting a new technology, then the signal ends up being the same. I definitely agree with the notion that the early adopter group is more often than not more talented than average. But, I'm sure companies also take this into account when deciding whether or not to pick a new technology.
- jorangreef 5y ago
  Is it really a challenge if "quality" is a measure of being fit for purpose? You don't necessarily have to compare across every technology if you are able to recognize a great tool that does what you need. "If the definition ends up aligning with what large companies look for when adopting a new technology, then the signal ends up being the same." And even then, the signal is only the same, but it's not worse. Whereas if large companies don't always optimize for quality, but have other incentives at play, or if they are less nimble, or less efficient, then looking for what large companies look for might actually end up setting you back with worse signal. So there's no upside I think.
ncmncm 5y ago
The value of the tool or technology is what is in question. A notable project choosing it and succeeding is signal. But there is a lot of noise. An individual judgment about the value is noise unless that individual has demonstrated a pattern of picking winners early and correctly. Early adopters are often smarter than the average bear, but are also much more likely to jump ship the moment the next fad breaches. That might be OK if you only need them for a short time.

Cyph0n 5y ago

I think the challenge would be in defining "quality" in a way that allows you to compare between multiple different technologies. If the definition ends up aligning with what large companies look for when adopting a new technology, then the signal ends up being the same. I definitely agree with the notion that the early adopter group is more often than not more talented than average. But, I'm sure companies also take this into account when deciding whether or not to pick a new technology.

jorangreef 5y ago
Is it really a challenge if "quality" is a measure of being fit for purpose? You don't necessarily have to compare across every technology if you are able to recognize a great tool that does what you need. "If the definition ends up aligning with what large companies look for when adopting a new technology, then the signal ends up being the same." And even then, the signal is only the same, but it's not worse. Whereas if large companies don't always optimize for quality, but have other incentives at play, or if they are less nimble, or less efficient, then looking for what large companies look for might actually end up setting you back with worse signal. So there's no upside I think.

ncmncm 5y ago

The value of the tool or technology is what is in question. A notable project choosing it and succeeding is signal. But there is a lot of noise. An individual judgment about the value is noise unless that individual has demonstrated a pattern of picking winners early and correctly. Early adopters are often smarter than the average bear, but are also much more likely to jump ship the moment the next fad breaches. That might be OK if you only need them for a short time.