In biology there’s a term called Carrying Capacity that refers to the maximum population of animals an ecosystem can contain. a16z’s Andrew Chen, in his book The Cold Start Problem (where he wrote about network effects) borrowed that term from biology to say every modern network has a minimum and maximum network size problem to solve.
Here’s how I interpret that for the current state of search engines:
In the same way that it takes a critical mass of searchers and information to kickstart the network effects of a search engine (aka the minimum network), there’s a maximum capacity that once exceeded, it can reduce the value of the network over time as more people and information are added to it.
In the case of Google, we’re past that point. 3–5bil results for any queries. Tik Tok shows you <10 when you’re searching for experience and places.
Searching in interest based or profession based Slack or FB groups gives you <5 extremely high quality results (e.g. searching “go to market strategy” in a slack community of 100+ senior PMs in SF).
the pro and the con of these new emerging search behaviours is that there’s no universal discovery for them. you have to be in the right underworld to experience the best search.
i say it’s both pro and a con. Con because the world is missing out on its best search engines (they exist! but they’re siloed).
Pro because it’s the next big thing for search and it’s where I have no doubt we’ll see a few new unicorns in the next 5 years. (my startup works exactly in this problem space).
Somewhat related side note: i believe this paper will heavily influence future of search
Google organised the world’s information, a bunch of new startups are gonna organise the world’s knowledge.
Let’s end and recap this with a question:
Can a product keep the volume of knowledge [that each user is exposed to] a constant and reasonably low, but design network effects that increase knowledge quality per user over time. Extremely difficult but solvable technical and growth problem.
What do you think? Ping me on Twitter or email me at sina@learningloop.org