Google Search for a long time was surprisingly simple internally.
Google Search for a long time was surprisingly simple internally. 90's era tech that stayed powerful for multiple decades. That's because if you have an emergent, ...
Topic: google search
18 chunks · 16 episodes
Topic summary
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A short read on the topic's time range, peak episode, and strongest associations. Use it as the quick orientation before drilling into examples.
- google search appears in 18 chunks across 16 episodes, from 2023-11-13 to 2026-02-16.
- Its densest episode is Bits and Bobs 4/29/24 (2024-04-29), with 2 observations on this topic.
- Semantically it travels with Google, search result, and ChatGPT, while by chunk count it sits between emergent process and higher quality; its yearly rank moved from #46 in 2023 to #77 in 2026.
Over time
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Raw mentions over time. Use this to see absolute attention, not relative rank among all topics.
Observations
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The primary evidence view for this topic. Sort it chronologically when you want concrete examples behind the larger pattern.
Some systems encourage experimentation.
... what you do, you're unlikely to get hurt, and you'll likely get a good result. Google Search had this characteristic, and chatbots do too. The expectation for how likely a given input is to give good enough results is a prior that configures ...
Web 2.0's insight was: because all of these users use the same domain, you can aggregate signals to benefit all users.
...at via anonymous aggregation to produce crowdsourced intelligence. For example, Google Search's ranking is largely powered by the clickstream and the querystream. As Tim O'Reilly has said, data is like sand. Not useful in small quantities, but...
Google Search as a centralized service felt somewhat less scary to me than ChatGPT.
Google Search as a centralized service felt somewhat less scary to me than ChatGPT. But why? Both could have outsize impact from just a bit of bias given their sca...
Google Search started off as being most useful in the long tail of use cases.
Google Search started off as being most useful in the long tail of use cases. For all the things where the head of portals and manually-curated directories didn't ...
Chat is a forgiving interface for quality.
...nd tries are very hard to get to the bar of viability and then improve. Compare Google Search and (spoken) Google Assistant interactions. With Google Search, as long as the answer is in the top 10, it's fine. Formulating a query is fast, and t...
Consumer businesses tend to be pulled inexorably towards engagement and ads.
...gravity well of incentives into competing for users' attention. Many years ago, Google Search and Ads had a wall between them. Not any more. The wall was not bulldozed by any instantaneous force. It slowly eroded in the sandstorm of A/B experi...
You have to work to get disconfirming evidence from LLMs.
...orrected its error and said that it's brown M&Ms, which I then confirmed with a Google search. A great example of the gullibility problem!
The Aggregator playbook requires two things to work:
...ywheel. The more any user uses it, the more the quality for all users improves. Google Search has this property. Notably, neither of these is true anymore for OpenAI. OpenAI is no longer the best model. OpenAI also doesn't seem to have much of...
An assistant that gives you a handful of options to choose from is useful.
... judgment is in the loop, always. But the boring / hard part is automated away. Google Search is fundamentally framed as "here are 10 options, you pick the one you want" Very forgiving UX modality, with a clean hill to climb of quality. 4-up U...
Asking an assistant to do an action is like hitting that "I'm feeling lucky" button.
...uite large; you're out $100 and only realize it was wrong days later. If it's a Google Search, the downside is tiny; just immediately do the query again manually. Amazon's search results have famously become quite scammy and crappy, which mean...
Google Search was selecting over a sea of static content.
Google Search was selecting over a sea of static content. But in AI, content can be hallucinated on demand, so maybe the Google-like position is the generator of t...
Open-ended tools can have the zombo.com problem.
...e a clear starter use case for users so they can get a sense of what it can do. Google Search and ChatGPT are two open-ended tools. But they are both good enough at so many things, that no matter what you do as a first use case, you're likely ...
A design pattern with humans in the loop: 4-up evolution.
...ost every MidJourney user session presumably has many iteration cycles, whereas Google Search sessions presumably have 1.1 (or less) iteration cycles. It allows the user to be in the driver's seat, but without having to be proactive. It gives ...
Google Search is a meta-product.
Google Search is a meta-product. Its quality and usefulness isn't just a reflection of the effort invested by its builders. The quality and usefulness is also in t...
Google Search is a hyper bespoke yet mass market product.
Google Search is a hyper bespoke yet mass market product. It was one-size-fits-all, but also perfectly bespoke to each user's needs. The user interacts with it, in...
LLMs are vulnerable to the "screenshot attack".
...t in the system. But it is not a given that it has to work this way! Consider a Google Search result where one of the ten blue links is clearly not a good result. It's not nearly as viral, Google isn't vouching for it as strongly. Going even f...
Coevolution drives massive increases in capability.
...aces you see this self-hoisting quality: Generative Adversarial Networks (GANs) Google Search's quality coevolving with user's expectations. Dunbar's Social Brain hypothesis, where massive increases in intelligence were driven by each person t...