Mobile Dev Memo Podcast

Season 7, Episode 5: Ads in ChatGPT (with Rishabh Jain)
Date: February 3, 2026
Host: Eric Sufer (B)
Guest: Rishabh Jain (C)

Episode Overview

This episode dives deeply into the newly announced launch of ads in ChatGPT, an event that marks a major strategic shift for OpenAI and could reshape digital advertising. Host Eric Sufer is joined by industry expert Rishabh Jain to discuss the implications, philosophy, consumer and advertiser benefits, launch strategy, comparisons to other monetization models, technical and economic challenges, and potential long-term impact of introducing ads to generative AI agents.

Key Discussion Points & Insights

1. Predicting Ads in ChatGPT – The Rationale

Timestamp: [00:58]–[04:18]

• Eric (B) congratulates Rishabh (C) for accurately predicting the timing of ads in ChatGPT, connecting it to the hiring of Fiji Simo and OpenAI’s strategic needs.
• Rishabh (C) explains the logic: “It became very apparent…they understood the economics of the business they were building and the types of capabilities that they would need to develop underneath that.” ([02:32])
• Core point: Ads are the most economically rational and consumer-aligned way to scale large platforms, compared to alternatives like subscriptions or affiliate only.

2. Benefits of Ads for Consumers and the Market

Timestamp: [04:18]–[09:30]

• Eric addresses “insidification” fears (platforms degrade the experience once users are hooked), calling such reactions “predictable hostile” and “philosophically” wrong:
  • “In offering ads, they're giving more capacity to the accounts…ad-supported users will experience…access to better models, a better experience in exchange for these ads…If you get to the power of the Instagram ads engine, it's all upside.” ([04:18])
• Rishabh argues ads expand consumer surplus and economic opportunity:
  • “If you did not have ads…there is a 0% chance that a new company…will ever find that customer because there is no trusted data about that company because it's new by definition. And what we are then saying is we prefer an Internet where a new company will never have a chance to actually show up to a customer who could want their product. And that to me is a squarely worse internet.” ([06:41])
• Key Insight: Ads democratize discovery, breaking organic search bias toward incumbents and aggregators.

3. Comparing Monetization Models: Affiliate, Ads, and Economics

Timestamp: [09:30]–[15:32]

• Eric critiques the affiliate/instant checkout model:
  • “The affiliate model…was just suboptimal relative to ads…you're not going to have an ability to explore, exploit…without the bid to mediate that, you won’t have any ability to…penetrate that dynamic with something that's new.” ([09:30])
  • Cites research showing “growth in Internet and advertising spend coincides with an expansion of the availability of products.” ([10:18])
• Rishabh expands:
  • Editorial/affiliate links “bias toward Amazon…all you’re doing is feeding basically one of the biggest companies on the planet…do you guys want everything to go to Amazon?” ([11:18])
• Both agree the 4% affiliate fee is a bootstrapping step for data collection and will “go to zero,” giving way to full-fledged ad systems.
  • “4% is not a strategy…that 4% is not for CAC, it’s for a one-off transaction…If I pay for an ad…I get their email address. That is a relationship…I can remarket…” (Eric, [12:41])

4. Complexity of In-Platform Checkout & Marketplace Dynamics

Timestamp: [15:32]–[20:01]

• Rishabh highlights pain points of in-platform commerce, using TikTok Shop and Meta as examples:
  • Platforms take on “an incredible amount of pain…responsible for that consumer’s experience…They will take that pain…to actually understand the consumer behavioral data…but they won’t want to deal with it [long-term].” ([15:32])
  • Predicts OpenAI will revert to facilitating, not fulfilling, commerce as its main model.

5. Social Commerce & Competitive Dynamics (TikTok, Amazon)

Timestamp: [20:01]–[23:04]

• Eric questions why TikTok leans back into social commerce.
• Rishabh: “They want to compete on product search…if they believe they are going to capture enough audience where search intent…is high enough…they can own the product search interface…even Amazon is scared.” ([20:24])
• Discussion of Amazon’s “Shop brand sites directly” and competitive responses.

6. ChatGPT Ads Launch: Initial Product Strategy

Timestamp: [23:04]–[28:38]

• Eric: $60 CPM, limited targeting, no measurement—launch borrows from Netflix’s playbook.
• Rishabh: “I always give the benefit of the doubt…assume they are maximally intelligent…all of their actions are signal maximizing actions and promise mitigating actions.” ([23:04])
  • Charging CPM at launch “gets the direct data…without making any promises…to advertisers.”
  • Initial buyers are large Meta/TikTok advertisers maximizing experimental signal.
• Eric: “The real question is the rate of change. How quickly does this evolve?…They needed to start somewhere…Facebook started the same way.” ([26:06])

7. Targeting & Privacy Considerations

Timestamp: [28:38]–[35:38]

• Eric: Targeting could emulate Facebook (pixel/cappy), but using chat content for targeting risks conflicts.
• Rishabh: “They’re going to build an interest graph…The amount of things ChatGPT knows about me is astonishing…it doesn’t need the context of that chat to serve me relevant [ads]…the upside is de minimis if it exists at all. And the downside is massive.” ([32:47])
  • Predicts initial period of maximizing learning w/CPM, before shifting to models tuned for conversion.
• Eric: Avoiding niche/sensitive ad placements is smart risk mitigation.

8. Future Impact, Growth Potential & Economic Consequences

Timestamp: [36:33]–[43:07]

• Eric: “Let’s say…it’s January 30th, 2027…ChatGPT did $10 billion in revenue…what did they get right?”
• Rishabh: Execution and onboarding: “They have made it easy to onboard people and to enable them to put a budget in…to understand some amount of effectiveness of that spend…budgets of every…brand…are going to be extremely large because they can’t afford to not understand.” ([37:03])
  • Predicts up to $20 billion run rate by end of 2026 if execution is flawless.
• Eric: Biggest risk is lack of focus. Success depends on discipline and execution, not a “million other things.”
• Eric: “If you get this right…this is a massively accretive and an accelerant for economic growth…a trajectory change for the impact of digital advertising on GDP growth.” ([41:46])
• Rishabh: “OpenAI ads outcomes will deliver that level of growth…that is the right way to think about the impact, not the amount that was spent on ads, but…look at the amount of stuff that got bought…” ([43:07])
• Eric: Highlights the “money multiplier effect” of performance ads: spend leads to compounding returns for merchants and advertisers, powering new business creation.

Notable Quotes & Memorable Moments

“If you did not have ads…there is a 0% chance that a new company…will ever find that customer because there is no trusted data about that company because it's new by definition…that to me is a squarely worse internet.”
— Rishabh Jain [06:41]

“…if you get to the power of the Instagram ads engine, it’s all upside… people just ignore that. And I think it’s disingenuous to do that.”
— Eric Sufer [05:10]

“All you’re doing is feeding basically one of the biggest companies on the planet…do you guys want everything to go to Amazon?”
— Rishabh Jain [11:18]

“…all of their actions are signal maximizing actions and promise mitigating actions…keeping maximum leverage for themselves and maximizing the signal…”
— Rishabh Jain [27:05]

“They’re going to build an interest graph…It doesn’t need the context of that chat to serve me relevant [ads]…the upside is de minimis if it exists at all. And the downside is massive.”
— Rishabh Jain [32:47]

“Let’s say…January 30th 2027…ChatGPT did $10 billion in revenue last year…what did they get right?”
— Eric Sufer [36:33]

“The only constraint is ChatGPT’s ability to absorb that [spend]…the only problem will be ability to onboard, ability to supply…and those things are way harder than they sound.”
— Rishabh Jain [37:03]

“If you get this right…this use case…this could be another one of those inflection points…a trajectory change for the impact of digital advertising on GDP growth.”
— Eric Sufer [41:46]

Timestamps for Important Segments

• [00:58] — Introduction to the episode’s purpose: Ads in ChatGPT
• [02:03] — Rishabh on visualizing the logic behind ads in ChatGPT
• [06:41] — Why ads increase consumer surplus and economic opportunity
• [11:18] — The affiliate model and the Amazon bias in discovery
• [15:32] — The challenges of in-platform commerce for platforms
• [20:24] — TikTok, product search, and competitive response from Amazon
• [23:04] — Launch strategy: why $60 CPM and limited features make sense
• [32:47] — Targeting, privacy, and the role of AI/ML in ad placements
• [36:33] — Predicting the blowout: $10B+ ad revenue scenario for ChatGPT
• [41:46] — Digital ads as an economic inflection point, and OpenAI’s potential

Tone and Language

• Direct, analytical, and deeply technical, with friendly banter and candid honesty.
• The speakers are optimistic about the economics and positive impact of ads, but frank about operational and ethical pitfalls.
• Dismissal of "conspiratorial" or "hostile" anti-ad rhetoric, focusing on practical and empirical arguments.

Summary

Eric Sufer and Rishabh Jain deliver a masterclass in ad economics as they do a deep dive into why OpenAI’s move to introduce ads in ChatGPT is not only logical, but potentially transformative. They analyze the benefits to consumers, merchants, and the internet ecosystem; assess the strengths and flaws of affiliate, subscription, and advertising models; deconstruct the launch strategy and tactical choices; and debate the likely timelines and impact for OpenAI and the economy. Their conversation, filled with clear examples, bold predictions, and sharp industry insight, is essential listening (or reading) for anyone interested in the future of AI, advertising, and digital commerce.