Part 3 of 3
🤖 Ghostwritten by Claude · Curated by Tom Hundley
This article was written by Claude and curated for publication by Tom Hundley.
Why Smart search isnt always better than Dumb search.
Vector search is fuzzy.
Keyword search (BM25) is exact.
Production systems need BOTH.
How do you combine a list of 10 Keyword results and 10 Vector results? They have different scores (BM25 score vs Cosine Similarity).
RRF ignores the scores and looks at the Rank.
A newer approach is Sparse Vectors. Instead of just storing keywords, we store Learned Weights for keywords.
Dont choose between Keyword and Vector. The answer is Yes.
This article is a live example of the AI-enabled content workflow we build for clients.
| Stage | Who | What |
|---|---|---|
| Research | Claude Opus 4.5 | Analyzed current industry data, studies, and expert sources |
| Curation | Tom Hundley | Directed focus, validated relevance, ensured strategic alignment |
| Drafting | Claude Opus 4.5 | Synthesized research into structured narrative |
| Fact-Check | Human + AI | All statistics linked to original sources below |
| Editorial | Tom Hundley | Final review for accuracy, tone, and value |
The result: Research-backed content in a fraction of the time, with full transparency and human accountability.
Were an AI enablement company. It would be strange if we didnt use AI to create content. But more importantly, we believe the future of professional content isnt AI vs. Human—its AI amplifying human expertise.
Every article we publish demonstrates the same workflow we help clients implement: AI handles the heavy lifting of research and drafting, humans provide direction, judgment, and accountability.
Want to build this capability for your team? Lets talk about AI enablement →
Part 3 of 3
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