Vibes-based Search

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The problem with the internet is that we have too much and can find too damn little. In our palms, we hold the total sum of human knowledge, but most of the time, that isn’t enough to be genuinely useful. Due to a combination of SEO-optimized garbage and the technical challenge of organizing the world’s information, surfacing the answers we’re looking for on Google obliges us to navigate by knowledge star charts, triangulating our position in the digital universe with funky search terms like “best hiking trails AND iceland AND reddit.”

But “best hiking trails AND iceland AND reddit” is simply not how humans think. As I’ve discussed previously, much of our intellectual labor happens in the subconscious, in the elements of taste that make up how we process thought. We think in vague terms, like, “Flights to Iceland are cheap, I’ve heard the hiking there is pretty good.” Put simply: There is a vibe to how we think that is lost when we transform our questions into something Google search can understand.

The good news is that LLMs are the first technology that is explicitly trained on those subconscious elements of thought. Rather than rely on boolean searching—the borderline hieroglyphic set of logic rules you can use to make Google search more precise—you can fine-tune an LLM to think the way you do. That way, instead of mustering up the perfect search terms, you only have to wave in the direction of what you are looking for. You can type, “I’ve heard Iceland hiking is good, anything under five miles that's kinda epic?” and get a list of solid options instead of getting stuck in SEO hell.

I call it “vibes-based search.” And it represents a profound evolution in the way we find and interact with information online.

By making a large language model the principal technology in a search engine, vibes-based search evolves the process beyond carefully chosen keywords and star maps to something more direct and actionable. But because it understands how we think, it can also help us find what we want without knowing exactly what it is that we are looking for. Put another way, it represents an evolution beyond information and answers, to understanding.

I recognize that this description is a little dense and art-schooly. In plain English, LLMs have three new capabilities that change the nature of search:

Intuitive leaps: LLMs can answer poorly written questions with spooky-accurate answers. Even when users only vaguely gesture towards what they are trying to say, LLMs can intuit what they actually mean.
Ingest and understand new materials: Because it’s easy to integrate an LLM into an existing product, you can incorporate search into essentially any dataset. Even better, the LLM can “understand” the material, allowing you to surface answers, not just key phrases.
Co-create new answers: Generative AI allows you to generate new insights from existing data or remix multiple datasets together easily. It means search becomes a creative piece of software, as flexible as a programming environment.

Vibes-based search is an amalgam of these three capabilities. It means that you can write, code, and create in a way that traditional search can’t match. Let me show you what I mean.

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