AI Workflow Uses Past Transcripts to Help Podcasters Avoid Repetitive Guest Questions

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A new podcast research workflow, built with Audiogram and Anthropic's Claude via MCP, searches Apple Podcasts and retrieves episode transcripts to analyze a guest's previous interview answers. Unlike the common practice of generating questions from a guest's bio using ChatGPT, this approach identifies recurring themes, position changes, and already-answered questions. In a test using two published Sam Altman interviews, the tool surfaced gaps and produced targeted follow-up questions on topics like privacy limits and independent AI review. The workflow is driven by a structured prompt asking Claude to compare transcripts, separate evidence from inference, and cite specific episodes for every finding. The author disclosed involvement in Audiogram's early-user growth and noted current limitations around transcript availability and speaker label accuracy.

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CTF Challenge Shows How HTTP Request Smuggling Bypasses Path-Based Access Controls

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Google Identifies Three Russian Spy Groups Hijacking Auth Flows, Bypassing MFA

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