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Status: Archived concept — not current product or implementation guidance Phase: Phase 5 (AI Media) | Tier: Pro / Studio
This page preserves early product exploration only. It does not authorize automatic generation, unlimited usage, a provider, a model, public storage, or customer-data processing. Current notebook companion execution is off; see Notebook Media Governance.

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Overview

The hardest part of sharing is not wanting to share — it is figuring out what to say. A user finishes a research report, sees something interesting about their Blue Dream purchase, and thinks “I should post about this.” Then they open Instagram, stare at the caption field, type something, delete it, type something else, decide it sounds dumb, and close the app. The intent to share dies in the gap between wanting to share and knowing what to write. Social Posts eliminates that gap entirely. Every time High IQ generates intelligence — a research report, a monthly stats summary, a strain comparison, a collection milestone — it also generates 3-5 ready-to-share captions tailored to different platforms and tones. The user taps the one they like, hits share, and it goes. No writing. No editing. No friction. The caption sounds like something they would say because it is generated from their data and calibrated to their usage patterns. This is the cheapest AI media format to implement (pure LLM text generation, no audio/video/image pipeline), the fastest to generate (2-5 seconds), and the highest volume in terms of daily share opportunities. Every report, every milestone, every stat update can produce shareable text. While other AI media formats produce one or two outputs per order, Social Posts can produce dozens per month. The subtle power is in distribution. Every shared post includes a natural mention of High IQ — not as a forced “Download High IQ!” CTA, but as organic context: “According to my High IQ report…” or “50 strains tracked in High IQ.” The app becomes part of the vocabulary. When people see these posts repeatedly from different users, High IQ becomes synonymous with cannabis tracking the way Strava is synonymous with running.

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What It Does

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Post Formats

A short, personality-driven review of a strain the user just tried. Generated from the strain’s terpene data, the user’s notes (if any), and the report findings. Multiple tone options: casual (“Blue Dream hits different in January”), analytical (“The Myrcene-to-Limonene ratio on this batch is textbook for afternoon creativity”), or enthusiastic (“3rd time buying this and it never misses”).
A data-driven summary of the user’s month: “My January in cannabis: 4 new strains discovered, 60% sativa-dominant, Limonene was my top terpene, and my stash is worth more than my grocery bill.” These work well on Twitter/X where data-driven posts perform.
An “if you like X, you’ll love Y” format that ties cannabis preferences to pop culture, food, music, or vibes. Examples: “If your morning coffee is a cortado, your strain is Durban Poison. If it’s a mocha, you want Wedding Cake.” These are designed for virality — the format is inherently engaging and invites responses.
Milestone posts celebrating collection growth: “50 strains and counting. Here’s my top 5 this year.” “Just hit 100 strains tracked. Ask me anything.” “My indica-to-sativa ratio is 70/30 and I’m not apologizing.” These work across all platforms and tap into the collector/completionist psychology.
A hot-take comparison between two strains: “Unpopular opinion: Gelato is overrated if you’ve tried Ice Cream Cake. Same family, but ICC’s Caryophyllene hits harder.” These are designed for engagement — people love agreeing or disagreeing with takes.
“Just found a strain I’d never heard of and it’s incredible” posts generated when the user tries a strain outside their usual patterns. These highlight the app’s discovery features while creating genuine-sounding enthusiasm.

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Platform Optimization

Each post is generated in multiple versions optimized for different platforms:

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User Value

The insight is that people want to share but the friction of composing kills most share intent. By reducing sharing to a single tap — choose a pre-written post that sounds like you, hit share — the conversion rate from “intent to share” to “actually shared” increases dramatically. Volume of shares matters more than polish of any individual share.

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How It Works

1

Intelligence Event

Any intelligence generation event triggers Social Post generation: research report completed, monthly stats rolled up, new strain added to collection, milestone reached (10th strain, 50th order, etc.), or strain comparison viewed.
2

Context Assembly

The system gathers all relevant data for the event: strain names, terpene highlights, High Family, user stats, comparison data, collection metrics, and any user notes. For monthly stats, this includes aggregated consumption data.
3

Multi-Post Generation

An LLM (Claude) generates 3-5 post variants from the data, each in a different tone and for a different platform. The prompt specifies: sound like a real person sharing with friends, not a brand account. Reference specific data naturally. Include a subtle High IQ mention that feels organic, not promotional. Never use cringe marketing language.
4

Preview and Selection

The posts appear in a “Share” drawer on the report or stats screen. Each post shows a preview of how it will look on the target platform. The user swipes through options, taps the one they like, optionally edits it, and shares via the iOS share sheet.
5

Copy or Share

Two actions: “Copy to Clipboard” (paste anywhere) and “Share” (opens iOS share sheet pre-populated with the text). If a Strain Art image or Share Card exists, it is automatically attached to the share as a media preview.

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Technical Approach

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Architecture

This is the simplest AI media pipeline — no audio, no video, no image generation. Pure text.

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Cost Per Generation

This cost is so low that Social Posts could realistically be offered to free-tier users as an upgrade teaser — “here are 5 posts about your first report; Pro users get these for every report.”

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Prompt Quality Is Everything

The entire value of Social Posts lives in the prompt engineering. Bad prompts produce posts that sound like a marketing intern wrote them: Bad: “Just used High IQ to analyze my Blue Dream purchase! The terpene profile shows high Myrcene content. Download High IQ to learn more about your strains! #cannabis #weed #strainreview” Good: “Third time buying Blue Dream this year. The Myrcene is absurd on this batch — explains why it’s been my go-to after long days. Starting to think my High IQ report knows me better than my budtender does.” The difference is voice, specificity, and self-awareness. The good post references specific data (Myrcene, “third time”), sounds personal (“my go-to after long days”), and mentions the app naturally (“my High IQ report”) without being promotional. Key prompt strategies:
  • Never use exclamation marks in generated posts (instant marketing tell)
  • Reference specific terpene names and data points (shows intelligence)
  • Use first person and specific personal context (sounds real)
  • Include mild self-deprecation or humor when appropriate
  • Keep the app mention as context, not a call-to-action

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Tier Impact

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Dependencies

  • Research report data — built and live
  • User stats and analytics — built and live
  • Strain collection data — built and live
  • iOS Share Sheet integration — built and live
  • Post generation prompt engineering (per format, per platform)
  • Share drawer UI component
  • Clipboard copy functionality
  • Automatic Strain Art / Share Card attachment
  • Post preview rendering per platform

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Open Questions

  1. Edit capability — Should users be able to edit generated posts before sharing? Editing adds friction but increases comfort. Recommendation: yes, with a text field pre-populated with the generated post.
  2. Post performance tracking — Should we track which posts get the most engagement (if the user opts in to sharing analytics)? This data could improve prompt quality over time. Privacy implications need consideration.
  3. Scheduling — Should we offer post scheduling (“share this on 4/20 at 4:20pm”)? Adds complexity but could be a high-value Studio feature for users who take their cannabis social media seriously.
  4. User voice training — Could we analyze a user’s existing social media posts (with permission) to calibrate the generated voice? This would make posts sound even more authentic but has significant privacy and complexity implications. Long-term consideration.
  5. Hashtag strategy — Cannabis hashtags are frequently shadowbanned on Instagram. Should we avoid hashtags entirely, use euphemistic hashtags, or let users decide? The platform landscape changes frequently — this needs ongoing monitoring.
  • Share Cards — Visual format that pairs with Social Posts text
  • Report Sharing — Deep link sharing infrastructure
  • Strain Art — Art images attached to social posts for visual impact
  • Video Reports — Share Clips paired with captions for video-native platforms
  • Cannabis Personality — Personality-based posts (“I’m a Creative Explorer — what’s your cannabis personality?”)