We killed search operators right before AI agents needed them most.
Google was once a command line for the open web. With search operators, we could slice through the noise with precision. We could use filetype:pdf or site:forum to tell the system exactly what we wanted. We could tell the engine to ignore its own interpretation and just give us the raw match.
Over the last decade, we watched these tools disappear.
Google smoothed out the edges. They optimized for "natural language" and intent. They built a search engine for the casual human user. The official reason was simplicity. The cynical reason was that fuzzy results keep you on the platform longer than precise ones.
And they did this exactly at the moment a new user arrived. The AI Agent.
It turns out that AI agents are the ultimate power users. They aren't lazy. They don't get confused by syntax. They don't need "helpful" semantic fuzziness. They crave structure.
If I am building an agent to do deep research, I don't want it fighting with Google's interpretation of my query. I want it to act with surgical precision.
Think about an agent tasked with finding recent scientific papers. Without something like filetype:pdf site:arxiv.org after:2023, the agent wades through blog posts, LinkedIn summaries, and Wikipedia. It doesn't know what it's missing. It just returns what the algorithm decided was relevant and hallucination fills the rest of the gap.
We are facing an infrastructure problem. We dismantled the exact interface our AI future needs most.
An AI agent hallucinates less when you give it hard guardrails. Search operators were those guardrails. They allowed us to logically constrain the search space. Without them, the agent has to wade through the sludge of semantic results and guess what is relevant.
We pushed for a conversational web right when we needed a structured one.
We don't need a smarter Google for humans anymore. We need the old, raw Google back, a command line, not a conversation. But this time, built for our machines.