> ## Documentation Index
> Fetch the complete documentation index at: https://docs.highailabs.com/llms.txt
> Use this file to discover all available pages before exploring further.
# AI Podcasts
> Source-grounded conversational AI podcasts where two AI hosts discuss your strains, your orders, and your cannabis data.
**Status:** Archived concept — not current product or implementation guidance
**Phase:** Phase 5 (AI Media) | **Tier:** Pro / Studio
This page preserves early product exploration only. Its automatic generation,
unlimited usage, named-person personalization, ElevenLabs, CDN, and pricing
statements are superseded. Current notebook companion execution is off; see
[Notebook Media Governance](/guides/platform/notebook-media-governance).
## Overview
Two-host AI audio has demonstrated that people will listen to synthetic voices discuss their own source material. The format works because conversation is a natural way to absorb information. A dialogue between two hosts who disagree, riff on each other, and get excited about findings is inherently more engaging than a monologue — even when both hosts are AI.
AI Podcasts bring this format to cannabis intelligence. Two AI hosts — one analytical, one experiential — discuss your latest order, your terpene trends, your monthly consumption patterns, or a head-to-head comparison of two strains. They reference your data naturally: "So John just picked up Blue Dream for the third time. That is a pattern." "Yeah, and look at the Myrcene content — this batch is way higher than the last one. He might notice a different body feel." The conversation flows like two knowledgeable friends reviewing your purchase, not two robots reading a report.
This is the AI media format with the strongest potential unit economics and surprise-and-delight factor. The first-party pipeline will generate from structured cannabis intelligence data, with owned dialogue, evidence, voice, assembly, storage, and evaluation stages.
The ritual potential is enormous. "My monthly High IQ podcast dropped" becomes a sentence that subscribers actually say. Monthly recap episodes create recurring engagement touchpoints that feel earned (you generated this content through your purchases) rather than manufactured (here is a push notification because we need your DAU).
## What It Does
### Episode Formats
Two hosts discuss a specific strain from the user's latest order. They cover the terpene profile, effects forecast, High Family classification, how it compares to similar strains, and any notable medical research. If the user has tried this strain before, the hosts reference their history: "This is your third time buying this. Your notes from last time said it was 'perfect for Sunday mornings.'"
"Your Month in Cannabis" review episode. The hosts walk through all orders from the past month — what was purchased, how the terpene profile shifted compared to previous months, which High Families dominated, spending patterns, and standout strains. This is the flagship format because it creates a monthly ritual.
The hosts look at the user's current active stash and discuss the composition: "You've got six strains right now, and four of them are Myrcene-dominant. That is a LOT of body sedation in one stash." They suggest what is missing, what pairs well together, and what to try next.
A head-to-head comparison episode. The hosts debate two strains the user owns or is considering: effects, terpenes, use cases, High Family, potency. One host argues for each strain. Entertaining, informative, and useful for purchase decisions.
Any article from the TIWIH blog can become a podcast episode. The hosts discuss the article's key points, add color commentary, and relate the topic back to cannabis science. This extends the content marketing reach of every blog post.
### Host Personalities
The two hosts have distinct roles that create natural conversational dynamics:
| Host | Role | Voice | Style |
| ----------------------------- | ------------------------------------- | ----------------- | ----------------------------------------------------------------------------------------- |
| **Host A — "The Analyst"** | Data-driven, precise, slightly nerdy | Warm but measured | Leads with terpene data, research citations, classification details |
| **Host B — "The Enthusiast"** | Experience-driven, curious, relatable | Energetic, casual | Asks "but what does that actually feel like?", relates to personal anecdotes, makes jokes |
The contrast between them is what makes the conversation listenable. Host A says "the Caryophyllene content at 1.2% suggests anti-inflammatory properties." Host B says "okay but real talk — is this the strain you reach for after leg day or what?" Neither is wrong. Together they cover both the science and the experience.
## User Value
The "aha moment" is hearing two AI voices discuss YOUR specific strains by name, reference YOUR purchase history, and have a genuine-sounding conversation about YOUR cannabis data. The personalization transforms a novelty ("AI can make podcasts") into a utility ("this is the most convenient way to understand my order").
## How It Works
A podcast is triggered by one of: new research report generated (auto-generates Strain Deep Dive), month rollover (auto-generates Monthly Recap), user taps "Generate Podcast" on their stash or a strain comparison, or a new blog article is published.
The system assembles all relevant structured data for the episode context: strain profiles, terpene arrays, High Family classifications, user history, order details, notes, and comparison metrics. This is NOT the prose report text — it is the raw structured data that enables natural conversation.
An LLM (Claude) receives the structured data and a detailed prompt specifying the episode format, host personalities, conversation arc, and user context. The output is a dialogue script with speaker labels, timing cues, emphasis markers, and natural conversational elements (interruptions, laughter markers, "hmm" moments). The script is 800-2,000 words depending on episode length.
Each host's lines are sent to a TTS API (ElevenLabs) with distinct voice profiles. The voices are configured for conversational pacing — not audiobook narration. Emphasis markers from the script adjust pitch, speed, and volume. Word-level timestamps are returned for potential visual synchronization.
Individual audio clips are assembled into a continuous conversation with natural overlap timings, brief pauses between speakers, and ambient room tone to prevent clinical silence. A subtle intro jingle (2-3 seconds) and branded outro are prepended and appended. The final audio is exported as MP3 (128kbps, stereo).
The episode is uploaded to CDN storage. A push notification announces it: "Your new podcast is ready." The episode appears in the podcast section of the app with a play button, episode title, duration, and scrubbing progress bar. A 15-second preview is auto-extracted for the free tier upgrade hook.
## Technical Approach
### Pipeline Architecture
```
Report Data (JSON)
│
▼
┌──────────────────┐
│ Dialogue Script │ LLM generates two-speaker dialogue
│ Generation │ from structured strain/order data
└──────────────────┘
│
▼
┌──────────────────┐
│ Voice Rendering │ TTS API renders each speaker
│ (Host A + B) │ with distinct voice profiles
└──────────────────┘
│
▼
┌──────────────────┐
│ Audio Assembly │ Merge voices, add timing,
│ & Post-process │ intro/outro, normalize levels
└──────────────────┘
│
▼
┌──────────────────┐
│ CDN Upload + │ Store MP3, send push notification,
│ Notification │ extract 15-sec preview clip
└──────────────────┘
```
### Dialogue Script Quality
The script generation prompt is the most critical piece. A bad prompt produces stilted dialogue that sounds like two people reading alternating paragraphs of a report. A good prompt produces conversation that sounds like two friends at a dispensary counter.
Key prompt techniques:
* **Give hosts distinct knowledge gaps** — Host B should not know everything, so Host A has things to explain
* **Include disagreement moments** — "I actually think the Limonene is doing more work here than you're giving it credit for"
* **Reference specific data points naturally** — "1.2% Caryophyllene" not "the Caryophyllene percentage"
* **Include reaction beats** — "Wait, really?" "Okay that's actually interesting" "I didn't expect that"
* **End with a takeaway** — "So bottom line: if you're reaching for something after work, the GDP is your move"
### Cost Estimates
| Component | Cost Per Episode | Notes |
| ----------------------- | ----------------- | -------------------------------------- |
| Script generation (LLM) | $0.02 - $0.08 | \~2,000 tokens in, \~1,500 tokens out |
| TTS Host A (2.5 min) | $0.04 - $0.15 | ElevenLabs pricing varies by plan |
| TTS Host B (2.5 min) | $0.04 - $0.15 | Same voice API, different voice |
| Audio processing | $0.01 - $0.02 | FFmpeg, minimal compute |
| CDN storage (5MB MP3) | \$0.001 | Negligible per file |
| **Total per episode** | **$0.10 - $0.40** | **Lowest cost of any AI media format** |
## Tier Impact
| Tier | Access |
| ------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Free | 15-second faded preview of each episode. Audio plays for 15 seconds with the hosts mentioning the user's name and strains, then fades to silence with an upgrade prompt. Enough to hear the personalization, not enough to get the value. |
| Pro | Unlimited episode generation for all formats. Full playback, download as MP3, share clips. Auto-generation for every report and monthly recap. |
| Studio | Custom host voice selection (choose from 6+ voice pairs), extended Monthly Recap episodes (15-20 min), "Season" compilation of all monthly recaps, priority generation queue. |
## Future Possibilities
* **Choose host personalities** — Casual, scientific, funny, concise. Let users pick the vibe.
* **Friend collaboration episodes** — Two users opt in to a combined episode comparing their cannabis preferences: "John prefers indicas, but Sarah is all about the sativa hybrids..."
* **Seasonal specials** — A "420 Special" recap episode, "Year in Review" annual episode, "New Year's Strain Predictions" episode.
* **Guest experts** — A third AI voice representing a "cannabis scientist" or "budtender" for specific topics.
* **Podcast feed** — Generate a private RSS feed so users can listen in their podcast app (Apple Podcasts, Spotify) alongside their regular shows.
## Dependencies
* [x] Research report generation pipeline — **built and live**
* [x] User order history and stash data — **built and live**
* [x] Trigger.dev task infrastructure — **built and live**
* [x] Blog article content — **built and live**
* [ ] Dialogue script generation prompt (LLM)
* [ ] TTS integration with dual-voice support (ElevenLabs)
* [ ] Audio assembly pipeline (FFmpeg or similar)
* [ ] In-app audio player component with scrubbing
* [ ] Push notification for "episode ready" event
* [ ] CDN storage for audio files
* [ ] 15-second preview extraction for upgrade hook
## Open Questions
1. **First-party pipeline design** — Build dialogue planning, evidence checks, voice orchestration, assembly, storage, and evaluation as TIWIH-owned stages. Speech/model vendors remain replaceable bounded executors and cannot own the notebook contract.
2. **Episode length sweet spot** — Our data is focused (one order, one strain). Is 3-5 minutes the right length, or do users want longer episodes? Need user testing.
3. **Background generation timing** — Should podcast generation start immediately when a report is generated (user might not care about podcasts) or wait until the user visits the report page (saves cost but adds latency)? Recommendation: auto-generate for the first 3 reports to demonstrate value, then switch to on-demand if the user has not listened.
4. **Sharing format** — Share the full episode MP3, a 30-second clip, or a visual audiogram (waveform animation with subtitles over a branded background)? Audiograms perform best on social media but add rendering complexity.
5. **Voice consistency** — Should the hosts always sound the same (familiar, ritual-building) or should the voice profiles vary slightly to prevent listener fatigue?
## Related Features
* [Video Reports](/planning/ai-media/video-reports) — Visual alternative; video adds more but costs more
* [AI Music Videos](/planning/ai-media/ai-music-videos) — Premium format combining audio and video
* [Session Music](/planning/ai-media/session-music) — Music complements podcasts; different listening context
* [Blog AI Content](/planning/ai-media/blog-ai-content) — Blog articles as podcast episodes
* [Report Sharing](/planning/growth/report-sharing) — Sharing infrastructure for podcast clips