Turn user interview recordings into an Airtable insight repository

Build me a weekly agent workflow that turns raw user research interview recordings into a structured, searchable insight repository in Airtable. The end product should be a thematic, quote-level database that product managers can query, not a flat dump of transcripts.

Trigger: cron, every Friday at 4pm in my local timezone.

Step 1. Use Google Drive's List Files operation to find audio files added in the last 7 days to a designated 'User Interviews' folder. Filter by parent folder ID, by audio mime types (mp3, wav, m4a, flac, webm), and by createdTime within the past week. If no new files are found, end the run quietly.

Step 2. For each new recording, use Google Drive's Download File Content operation to pull the raw bytes.

Step 3. Pass the bytes to Deepgram's Transcribe Pre-recorded Audio operation. Enable diarization and smart formatting so interviewer turns and participant turns are clearly separated, and so numbers, dates, and punctuation render cleanly. Use a high-accuracy model suitable for English interview audio.

Step 4. For each transcript, extract the most quotable participant statements. Skip interviewer prompts, small talk, and filler. Aim for verbatim quotes that capture a clear thought, opinion, or behavior. Trim to roughly one or two sentences each, but do not paraphrase.

Step 5. Classify each quote by one primary theme from this list: pain point, goal, feature request, workaround, positive sentiment. Also tag a coarse sentiment of positive, neutral, or negative.

Step 6. Write the quotes to Airtable using the Create Records operation against a 'Research Insights' table. One row per quote, batching up to 10 records per request. Fields to populate: Quote (long text), Theme (single select from the list above), Sentiment (single select), Participant (text, inferred from the file name or speaker label), Source File (the Drive file name plus a link to the file), Interview Date (date, from the file's createdTime).

Step 7. Also write a short top-level summary per interview to a separate 'Interview Summaries' table using Create Records. Fields: Participant, Interview Date, Source File, Summary (3 to 5 sentences covering who they are, what they care about, and the top takeaways), Top Themes (multi-select of the themes that came up most). One row per interview.

Before creating Airtable rows, ask me for the base ID, the Research Insights table name or ID, and the Interview Summaries table name or ID. Also ask me for the Google Drive folder ID for the User Interviews folder. Validate that the Airtable tables have the expected fields and warn me if any are missing instead of silently failing.

Keep the workflow resilient: if a single file fails to transcribe or classify, log the error and continue with the rest. At the end of the run, log a one-line summary of how many interviews were processed, how many quotes were filed, and any files that were skipped.