Perplexity got ads

Original Article ↗ Hacker News Discussion ↗

Monetization Pressure & Business Models

  • Many see ads as inevitable: LLM companies burn huge amounts of cash; subscriptions alone may not cover costs, especially with “winner-take-all” and nation‑state–backed competition.
  • Others argue ads are a sign the product isn’t sustainably valuable without external subsidy.
  • Some point to usage-based/API pricing and efficiency (e.g., DeepSeek-style) as alternatives, but question how end-user products then make money.
  • There’s debate over whether AI firms should “just” stay small and sustainable vs pursuing hypergrowth.

Ads: Utility vs Harm

  • One camp calls ads a “necessary evil” that funds free services like search, video, sports, and social media; most consumers tolerate them.
  • The opposing camp sees the ad industry as exploitative “attention pollution,” with weak ROI and heavy psychological manipulation.

Impact on Trust and UX

  • Core concern: LLMs were attractive partly because they removed SEO spam and ads; re‑inserting ads undermines that benefit.
  • Worries that sponsored prompts (“Why is TurboTax the best…?”) will bias or override truthful answers.
  • Unclear what exactly advertisers can influence (only sponsored query, or also sources, wording, and ranking?).
  • Fear that future models might embed undisclosed paid bias in answers, making “truth” indistinguishable from marketing.

Paid Tiers, Pricing, and Viability

  • Questions whether Perplexity Pro is ad‑free; several comments state ads are present even for paying users, which is seen as “double dipping.”
  • Frustration that nearly all AI services land on a $0 / $20-per-month split; some want cheaper, lower‑cap tiers ($3–5), but others note payment processing and support costs make low prices hard.
  • Skepticism that enough people will ever pay for search/LLM access to displace ad‑funded models.

Alternatives and User Responses

  • Some users say they’ll cancel Perplexity if/when ads appear in results; others already prefer tools like Kagi, Claude, you.com, or local models.
  • Kagi is cited as an example of a paid, ad‑free search+LLM product with a small but enthusiastic base, though questions remain about scalability and dependence on other engines.
  • A subset argue people who truly care about ads/privacy are a minority; mass-market products will keep optimizing for ad revenue.