The Real Solution for Vertical AI
AI Engineer · youtube · 2026-07-12
This talk addresses a core issue with vertical AI products: improving accuracy doesn't equate to solving user pain points. When doing tax data entry, Filed achieved a model accuracy of over 80%, but users remained unsatisfied because they still had to perform massive amounts of validation. AI merely shifted the shape of the work without actually reducing the burden.
The presentation outlines three design principles:
- Embed AI into existing workflows instead of forcing users to adapt to a new platform.
- Provide a "1000-foot view" before drilling down, letting users quickly confirm the big picture before validating details layer by layer.
- Focus on skills, not just the model, encoding real-world edge cases into reusable knowledge so the system gets smarter over time.
He also drew a parallel to early AI coding tools: what truly worked wasn't tossing a block of code at the user for review, but integrating AI directly into the editor and workflow, using mechanisms like planners, memory, and skills to reduce the user's validation burden.
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