Marketing

Summarizing Interviews with AI Without Losing Evidence

• A Third Model as Tiebreaker: Cost and Latency
• From Inter-Rater Agreement to a Human Label Budget
• Keeping a Tagging Prompt in Sync Across Two Models
• Reviewer Screen Versus Model Context: Two Views of One Packet
• Structuring Interview Notes So a Model Can Query Them Later
• Turning Refusals into a Labeled Set for Tuning
• Using an AI Agent to Tag and Cluster Customer Interview Notes
• What Interviews into Case Studies Cost in Model Tokens
• When to Trust a Customer's Stated Alternative
• When Two Models Disagree on the Same Input: A Tie-Breaking Rule
• A Fallback Ladder for Refusals: Clarify, Retry, Escalate
• A Human Coding Protocol for Model-Tagged Interviews
• A Query Pattern That Returns the Exact Sentence Behind a Tag
• A Reliability Table for Each Segment
• Calibrating an Agent's Plan Confidence, Not Just Its Answer
• Designing a Grounded Answer Schema for Interview Research
• Human Raters or a Model: A Cost and Agreement Ledger
• Keeping a Quote Index Fresh When Interview Notes Are Edited
• Logging Rater Disagreements and Revising the Rule
• Routing Interview Queries: Search Notes or Ask a Person
• Sampling Accepted Agent Decisions: How Many to Recheck
• Sampling Tagged Passages So a Person Can Check the Labels
• Scoring Interview Transcripts with a Rubric and a Model
• Splitting a Long Transcript So It Fits the Context Window
• Splitting a Packet So the Model Sees Only Its Task
• Splitting Extraction Prompts So Long Interviews Fit Context
• Storing Refusal Labels and Thresholds in Postgres
• Testing a Packet Template Against Two Models
• Using a Model to Tag Interviews Without Losing the Quote
• Using an AI Agent to Summarize Interviews Without Losing Evidence
• Weighing Stated Demand Against Revealed Demand: A Decision Rule
• What Tagging and Clustering Interviews Costs in Model Tokens
• When a Model Should Refuse to Tag a Transcript Passage
• When the Human Label Is Wrong: Auditing the Tiebreaker
• When the Similarity Score Is Not Enough to Show a Reviewer
• Writing a Labeling Guide for a Multi-Label Taxonomy
• Writing a Labeling Guide Two Reviewers Can Apply the Same Way