Author

Benjamin Tannenbaum

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Preprint Oct 2026

Commercial Intent in Human-AI Conversations: A Corpus Audit and Architecture for Website Sales Agents

Conversational sales agents must distinguish questions about products from purchase commitments, preserve explicit requirements, and ground the next action in current business information. We report an aggregate census of 725,219 records in an accessible conversation table provided by Aiso and develop a reference archi...

Benjamin Tannenbaum · 0 citations

#generative ai Preprint Sep 2026

Purchase Advice and Observable Buyer Responses in Real AI Conversations

A central finding is a measurement limitation: recommendation content is observable much more often than a buyer's subsequent decision.

Benjamin Tannenbaum · 2 citations

Jul 2026

The Prompt Is Not the Query: How Request State Evolves Across Multi-Turn AI Conversations

Categorical results support session-level measurement for AI search, and length-matched nulls show that low lexical coverage is largely a consequence of turn length, so vocabulary results are interpreted as information availability, not semantic drift.

Benjamin Tannenbaum · arXiv.org · 2 citations

Preprint Aug 2026

Beyond the Final Prompt: Measuring the Effect of Within-Conversation Context on AI Answers

This study directly test whether that omitted within-conversation context changes answers in a conversation and concerns preceding turns in the same conversation and does not test persistent memory across separate conversations.

Benjamin Tannenbaum · 1 citation