Blog
Long-form analysis on what it means to build AI products grounded in domain mastery — and why it matters for professional practice.
Methodology
Domain expert AI products are purpose-built AI systems grounded in the tacit knowledge of real practitioners. This guide explains what they are, how they differ from generic AI, and why specificity changes outcomes.
Methodology
The most powerful AI products are built through structured collaboration between AI developers and recognised domain practitioners. Here is how that process works — and why it produces different results.
Analysis
Generic AI is trained on everything and masters nothing. Expert-built AI is trained on the knowledge of one domain's best practitioners. Here is why specificity beats scale for professional applications.
Methodology
Domain-specific AI development builds intelligence within a single field, shaped by its practitioners. This is why narrow AI outperforms general AI in professional domains — and how it is built.
Analysis
Most AI implementations fail not because the technology is wrong, but because the knowledge encoded in them is wrong. Here is what real-world AI implementation requires that most vendors miss.
Positioning
A new standard for AI products: built by recognised domain practitioners, for the professionals who work in that domain. This is what "built by experts to serve experts" means — and why it changes outcomes.