I was super-excited about vector search and embeddings in 2024 but my enthusiasm has faded somewhat in 2025 for a few reasons:
- LLMs with a grep or full-text search tool turn out to be great at fuzzy search already - they throw a bunch of OR conditions together and run further searches if they don't find what they want
- ChatGPT web search and Claude Code code search are my favorite AI-assisted search tools and neither bother with vectors
- Building and maintaining a large vector speech index is a pain. The vector are usually pretty big and you need to keep them in memory to get truly great performance. FTS and grep are way less hassle.
- Vector matches are weird. So you get back the top twenty results... those might be super relevant or they might be total garbage, it's on you to do a second pass to figure out if they're actually useful results or not.
I expected to spend much of 2025 building vector search engines, but ended up not finding them as valuable as I had thought.
- LLMs with a grep or full-text search tool turn out to be great at fuzzy search already - they throw a bunch of OR conditions together and run further searches if they don't find what they want
- ChatGPT web search and Claude Code code search are my favorite AI-assisted search tools and neither bother with vectors
- Building and maintaining a large vector speech index is a pain. The vector are usually pretty big and you need to keep them in memory to get truly great performance. FTS and grep are way less hassle.
- Vector matches are weird. So you get back the top twenty results... those might be super relevant or they might be total garbage, it's on you to do a second pass to figure out if they're actually useful results or not.
I expected to spend much of 2025 building vector search engines, but ended up not finding them as valuable as I had thought.