Descriptions:
Dylan Davis, founder of an AI consultancy, walks through a practical four-part framework for automating client document data entry using Claude, ChatGPT, and Google Gemini. The core concept — which he calls the “AI funnel” — addresses a near-universal business pain point: clients send the same information in different formats (PDFs, image scans, spreadsheets, emails), and staff spend hours manually copying it into templates field by field. The system uses AI to handle the chaotic input side and normalize it into a consistent output.
The tutorial covers four concrete steps: defining the output schema by listing field names, data types, and required versus optional status; writing a rules-based system prompt that prevents the AI from hallucinating or over-inferring; building an audit table with four status flags — extracted, inferred, missing, and ambiguous — plus source quotes for human review; and testing across five to eight diverse real-world input examples before any further automation. Davis also provides a reusable prompt for situations where no clean template exists, showing how to have AI extract field definitions from three to five historical completed examples.
The methodology is explicitly tool-agnostic and works inside Claude Projects, ChatGPT Projects, or Gemini Gems. Davis recommends using the highest-reasoning model available for field definition tasks and emphasizes a manual-first approach before introducing any downstream automation — making this accessible to operations teams and consultants without a development background.
📺 Source: Dylan Davis · Published April 11, 2026
🏷️ Format: Tutorial Demo
