Analysis of Reddit Discussion on Proprietary Data for AI Defensibility and Mentioned Stocks (DUOL, FIG, ADBE)

This analysis is based on a Reddit discussion (event timestamp: 2025-11-28 UTC) focused on the role of proprietary data in AI defensibility. The OP argued that non-scrapable, causal, identity-consistent datasets (e.g., Duolingo’s learning interactions, Adobe/Figma’s creative process data, Mastercard’s transactions) are more critical for AI competitive moats than models alone.

1. Mentioned stocks as “worst at the moment”
   : Verified via internal market data showing significant November 2025 declines: Duolingo (DUOL) -31.35%, Figma (FIG) -27.99%, Adobe (ADBE) -5.93% [0].
2. Proprietary data assets
   :
   • Duolingo uses billions of proprietary learner interactions to power its adaptive AI engine, Birdbrain [1].
   • Adobe’s Firefly Foundry enables training custom AI models on proprietary creative data [2].
   • Figma (FIG, public since 2025 after the failed Adobe acquisition) leverages collaboration data from its design platform [3].
3. Reddit’s data quality
   : Raw Reddit data is noisy, but curated datasets like OpenWebText have been used for high-quality LLM training [4], making the “slop tier” claim context-dependent.
4. Synthetic data utility
   : Industry research indicates synthetic data offers privacy and scalability benefits, with projections to outweigh real data by 2030 [5]. However, real data remains critical for capturing nuanced complexity [6].
5. Reddit’s monetization
   : Advertising accounts for 94% of Reddit’s Q3 2025 revenue, but growing AI data licensing deals signal ongoing efforts to improve data monetization [7][8].

1. Short-term vs. long-term value disconnect
   : The mentioned stocks (DUOL, FIG, ADBE) showed significant short-term declines [0], but their proprietary data assets remain a long-term competitive advantage, as evidenced by corporate AI strategies [1][2][3].
2. Reddit’s data paradox
   : While raw Reddit data is noisy, curated versions have proven valuable for AI training [4], highlighting untapped monetization potential beyond advertising [7][8].
3. Synthetic data nuance
   : The claim that synthetic data is universally “more useful” is oversimplified; both real and synthetic data have complementary use cases (real for ground truth, synthetic for scalability/privacy) [5][6].

• Short-term volatility
  : DUOL, FIG, and ADBE face continued short-term market pressure following their November 2025 declines [0].
• Reddit’s revenue concentration
  : Over-reliance on advertising (94% of Q3 2025 revenue) exposes Reddit to ad market fluctuations [7].

• AI-driven growth
  : DUOL, ADBE, and FIG can leverage their proprietary data to develop advanced AI features, strengthening long-term competitiveness [1][2][3].
• Reddit’s data monetization
  : Expanding AI licensing deals present opportunities to diversify revenue streams beyond advertising [8].

• Verified facts
  : DUOL, FIG, and ADBE experienced significant price drops in November 2025 [0]; each holds proprietary data assets critical to their AI strategies [1][2][3].
• Nuanced perspectives
  : Reddit’s data quality varies by curation [4]; synthetic data’s utility is context-dependent [5][6]; Reddit has room to improve data monetization [7][8].
• Sentiment balance
  : Bullish on long-term AI value from proprietary data; bearish on short-term stock performance; neutral on synthetic vs. real data tradeoffs.