Why ChatGPT will be the next big growth channel (and how to capitalize on it) | Brian Balfour

Key Concepts:

• New distribution platforms
• Chat GPT as a potential new distribution platform
• Four-step cycle of distribution platforms (Conditions met, Moat, Platform Opening, Platform Closing)
• Escape velocity
• Prisoner's dilemma in platform adoption
• Retention and engagement as key metrics
• Betting strategy for startups vs. late-stage companies
• AI adoption challenges and strategies
• Hard constraints for AI adoption
• Catalysts, Converts, and Anchors in AI transformation

1. The Changing Landscape of Growth and Distribution

• The traditional growth channels (SEO, paid growth, word-of-mouth) are becoming increasingly saturated and difficult to leverage.
• Incumbents can copy new ideas faster, shrinking the window for startups to achieve escape velocity.
• AI is accelerating competition by making software development easier.
• Brian Balffor argues that building a great product is necessary but not sufficient; great distribution is the key differentiator.
• Alex Rample's (Andreessen Horowitz) blog post from 2015 highlights that startups need to get distribution before incumbents copy.

2. The Emergence of New Distribution Platforms

• New distribution platforms offer startups an opportunity to gain an advantage because incumbents are slower to adapt.
• Casey Wyers noted that the AI technology shift hasn't yet been accompanied by a distribution shift.
• Balffor believes that all the conditions for a new distribution platform are now in place.

3. The Four-Step Cycle of Distribution Platforms

• Step 0: Conditions Met: Consensus around a new category (e.g., AI chat platforms), fierce competition among 5-7 major players, all seeking an edge.
• Step 1: Moat: A player identifies a defensible moat (e.g., network effects, data) and focuses on gathering it as quickly as possible.
• Step 2: Platform Opening: The player establishes a third-party platform with incentives for content creators, app developers, and other businesses. The value exchange is distribution in return for contributions to the platform.
• Step 3: Platform Closing: The platform owner locks down the platform for monetization and control. This can involve shutting down the platform, developing first-party applications to absorb use cases, or artificially depressing organic distribution to push users towards paid mechanisms.

4. Examples of the Four-Step Cycle

• Facebook:
  • Step 0: Competition with MySpace, Friendster, etc.
  • Step 1: Identified direct network effects as the moat.
  • Step 2: Opened up the third-party platform (the "canvas") with access to notification channels and feeds.
  • Step 3: Gradually peeled back the value exchange, taking a percentage of revenue, suppressing organic channels, and absorbing use cases into first-party applications.
• Google:
  • Step 0: Competition with Yahoo, Altavista, etc.
  • Step 1: Identified data modes and incentivized web developers to optimize for search algorithms.
  • Step 2: Created a great distribution mechanism for content.
  • Step 3: Increased ad real estate, suppressed organic distribution, and absorbed high-value use cases (e.g., travel, restaurant search).
• Mobile (iOS):
  • Step 0: Competition among different phone manufacturers.
  • Step 1: Defensibility based on apps.
  • Step 2: Created the App Store.
  • Step 3: Increased restrictions over time.
• LinkedIn:
  • Step 0: N/A
  • Step 1: N/A
  • Step 2: Boosted distribution for individuals to create content.
  • Step 3: Pulled back on organic distribution after introducing the thought leader ad format.
• Udemy:
  • Step 0: N/A
  • Step 1: N/A
  • Step 2: Started with 80% revenue share to creators.
  • Step 3: Pushed revenue share down to 15-20%.

5. The Prisoner's Dilemma and the Importance of Early Adoption

• Companies cannot opt out of the game. Competitors will adopt new platforms, and customer expectations will change.
• It's better to be early to a new platform and figure out an exit strategy later than to be late.
• Companies like Zynga grew massively on Facebook by taking advantage of the platform early.

6. Chat GPT as a Potential New Distribution Platform

• Balffor predicts that Chat GPT will be the new distribution platform.
• The moat is context and memory. The more context a model has, the better the output.
• Chat GPT has the best retention and engagement, as shown by data from DD doss (Menlo Ventures).
• Signals suggest that Chat GPT is about to launch a third-party platform (e.g., hiring for "agent platform" roles).
• The value exchange will likely involve access to context, memory, and distribution in return for integration.
• Chat GPT is forming preferred partnerships with larger players to lend credibility to the platform.

7. Alternative Platforms and the Role of Niches

• If not Chat GPT, Gemini (Google) or Apple could be contenders.
• Apple has the ultimate view into user context through its devices.
• Smaller platforms will also emerge, focusing on niches (e.g., Claude focusing on developer tools, Cursor creating an agent platform for developers).
• These smaller platforms will follow the same four-step cycle.

8. Timeline and Next Steps for Chat GPT

• The next major steps will likely play out over the next six months.
• Chat GPT recently launched agent mode.
• The next step could be announcing preferred partners or opening up the platform.
• Chat GPT will need to define the value exchange and incentivize developers to join the platform.
• Deeper attribution and new monetization mechanisms will be important for covering the cost of AI.

9. Betting Strategy for Companies

• Late-Stage Companies: Can afford to place multiple bets and wait to see who the winner is.
• Startups: Must choose one platform and go all in due to scarce resources.
• It's essential to integrate with new platforms (Chat GPT, Gemini, etc.) to avoid being overtaken by competitors.

10. Criteria for Choosing a Platform

• Retention and depth of engagement of users.
• User quality and ability to monetize.
• Value exchange offered by the platform.
• Scale and momentum.

11. The Importance of an Exit Strategy

• Companies need to think about how to exit the platform before the closing stage.
• This involves owning an important part of the user experience, accumulating specialized data, or creating micro-network effects.

12. AI Adoption Challenges and Strategies

• Form hard constraints (e.g., limiting headcount, requiring AI prototypes).
• Identify catalysts, converts, and anchors within the organization.
• Be prepared to exit anchors who are resistant to change.
• Executives are often disconnected from the actual AI adoption taking place within their companies.
• Measure actual adoption and usage.
• Address bottlenecks in the system (e.g., legal, procurement).

13. Key Quotes

• "Startups is a game of trying to get distribution before the incumbent can copy." - Alex Rample (Andreessen Horowitz)
• "The AI technology shift has been a technology shift that has not come with the distribution shift yet." - Casey Wyers
• "The slowest your output is constrained by the slowest part of your system." - Fared Masavat
• "Your job as a parent is to essentially make them more and more independent." - Brian Balffor

14. Conclusion

The emergence of new distribution platforms, particularly those powered by AI, presents a significant opportunity for startups to disrupt incumbents and achieve rapid growth. However, companies must understand the four-step cycle of these platforms, adopt a strategic betting approach, and be prepared to adapt quickly as the landscape evolves. Furthermore, successful AI adoption requires hard constraints, a focus on cultural change, and a willingness to address bottlenecks within the organization.