I'm genuinely worried about all our short term investment in mitigating the failure modes of models that may only be SOTA for a few months.
It's very possible people being 'late' adopting AI may end up with a leg up, not only because they spent more time polishing personal skills during this time, but also because they don't bring all the baggage of 'AI competence' that is becoming irrelevant at breakneck speed.
This is “second mover advantage.” There are several dynamics that can make it better to wait and move later. Framed in terms of firms, moving late is advantaged when:
Let’s consider those criteria for an individual competing in the labor market with AI. The category should be long lived, AI is here to stay. Switching costs (here, hiring/firing by employers/clients) are low. Objective quality standards fails; technical labor is notoriously difficult to quantify. Imitation costs (can you copy someone else’s good ideas) are moderate but decreasing. That’s where model and tooling improvement shows up.
Based on this analysis, I agree that late movers are well positioned IF the market leaders continue to improve models and tooling to integrate best practices that were previously individual skills.
Early movers should exploit the lack of objective standards. Use your experience with the first generation of tools as marketing to win and retain clients. Continue to invest in soft skills like communication.
bluegatty · · focus · HN ↗
AI is rapidly saturating it's ability to be useful and these products need to start to mature.
It's not 'fun' to manage 50 different broken MCPs and their variety of ways in which they are broken.
It was 'fun' at the start, now it's just 'broken technology'.
Astra and Opus 5.5 are the 'starting point' for the next era of AI where we expect robust tooling.
TomGarden · · focus · HN ↗
I'm genuinely worried about all our short term investment in mitigating the failure modes of models that may only be SOTA for a few months.
It's very possible people being 'late' adopting AI may end up with a leg up, not only because they spent more time polishing personal skills during this time, but also because they don't bring all the baggage of 'AI competence' that is becoming irrelevant at breakneck speed.
pbronez · · focus · HN ↗
- the product category is long lived
- switching costs are low for buyers
- there are objective standards of quality
- product imitation costs are low
<a href="https://insight.kellogg.northwestern.edu/article/the_second_mover_advantage" rel="nofollow">https://insight.kellogg.northwestern.edu/article/the_second_...
Let’s consider those criteria for an individual competing in the labor market with AI. The category should be long lived, AI is here to stay. Switching costs (here, hiring/firing by employers/clients) are low. Objective quality standards fails; technical labor is notoriously difficult to quantify. Imitation costs (can you copy someone else’s good ideas) are moderate but decreasing. That’s where model and tooling improvement shows up.
Based on this analysis, I agree that late movers are well positioned IF the market leaders continue to improve models and tooling to integrate best practices that were previously individual skills.
Early movers should exploit the lack of objective standards. Use your experience with the first generation of tools as marketing to win and retain clients. Continue to invest in soft skills like communication.