Why ChatGPT will be the next big growth channel (and how to capitalize on it) | Brian Balfour
Brian Balfour, founder of Reforge, explains the predictable four-step cycle of technology platforms, from open to closed, and argues that ChatGPT is about to enter the "open" phase, creating a massive, time-sensitive distribution opportunity that startups and incumbents alike cannot afford to ignore.
Building a great product is necessary but not sufficient for success. The real differentiator is distribution. In today’s landscape, incumbents copy startups faster, organic channels are shrinking, and AI has increased competition, making it harder for new companies to achieve “escape velocity.” Historically, the most significant opportunities for startups to gain this velocity emerge when new distribution platforms are created.
While the AI technology shift has been happening for a couple of years, it has not yet been accompanied by a major distribution shift. All the ingredients are now in place for this to happen, and it will follow a predictable, four-step cycle that has repeated with every major platform from Facebook to Google to the iOS App Store.
The Four-Step Cycle of Distribution Platforms
New distribution platforms follow a predictable pattern, and understanding this game is crucial for survival and success. The cycles are also getting progressively shorter, meaning the window of opportunity is smaller than ever.
-
Step 0: Competitive Market Conditions. A new, massive category emerges (like AI chat platforms), but there is no clear winner. A handful of major players (OpenAI, Google, Anthropic, etc.) are in a fierce battle for dominance, looking for any edge to win a market that will likely end in a monopoly or duopoly.
-
Step 1: Identifying the Moat. One player identifies the key to building long-term defensibility. For early social networks, it was the friend graph. For AI platforms, the emerging moat is context and memory. The model with the most context about you, which feeds a “memory” loop, will produce the best, most personalized outputs and create lock-in.
-
Step 2: The Platform Opens. To build this moat as quickly as possible, the leading player opens a third-party platform. They create a value exchange: developers and companies add use cases, content, and users to the platform, and in return, the platform provides a powerful new form of distribution. This is the “gold rush” phase where early adopters can experience explosive growth.
-
Step 3: The Platform Closes. Once the platform has achieved market dominance and its moat is secure, the incentives change. The platform begins to lock down for control and monetization. This happens in a few ways:
- They suppress organic distribution to push developers towards paid channels.
- They build their own first-party applications to absorb the highest-value use cases.
- They take a larger percentage of revenue (e.g., Apple’s 30% tax).
- In some cases, they shut down access entirely to prevent a competitor from emerging on their own platform.
This cycle isn’t necessarily “evil”; it’s a natural outcome of competitive and capitalistic pressures to maintain growth and prevent disruption.
The Prediction: ChatGPT as the Next Great Distribution Channel
All signals point to ChatGPT being the platform that will initiate this new cycle, likely within the next six months.
- The Moat: ChatGPT is furthest along in building the moat of context and memory. They were first to launch memory features and are investing heavily in data connectors.
- Retention and Engagement: Data shows ChatGPT has significantly higher and improving user retention curves—including the elusive “smile curve”—compared to competitors. Historically, the platform with the best retention, not necessarily the largest initial distribution, wins (e.g., Facebook vs. MySpace).
- Signals of a Platform Launch: OpenAI is actively hiring for an “agent platform” and has already begun forming preferred partnerships with major companies like HubSpot, which lends credibility and paves the way for a broader third-party ecosystem.
How to Play the Game: A Prisoner’s Dilemma
The natural reaction might be to avoid building on a platform that will eventually squeeze you. However, this is a prisoner’s dilemma you cannot opt out of. If you don’t integrate, your competitors will, and customer expectations will shift to demand your product’s presence on the new platform.
Your Betting Strategy:
- Late-Stage Companies: Can afford to spread their bets across multiple emerging platforms and wait to see a clear winner emerge before committing fully.
- Startups: Do not have this luxury. You must make a focused, all-in bet on a single platform. The risk is higher, but so is the potential reward. Think of Zynga’s massive success from betting on Facebook early.
Criteria for Placing Your Bet:
- Retention & Engagement: Prioritize the platform with the stickiest user base.
- User Quality & Monetization: Analyze the user base’s willingness to pay (e.g., iOS vs. Android revenue splits).
- The Value Exchange: Understand what the platform is offering you in terms of distribution and incentives.
- Scale: All else being equal, the platform with more scale and momentum is a better bet.
Once you’re in the game, you must immediately start planning your exit strategy. How will you use the platform’s distribution to build your own moat—such as by accumulating specialized data, owning a critical part of a workflow, or creating micro-network effects—so you can survive after the platform inevitably closes?
On Effective AI Adoption within Companies
Beyond platform strategy, there’s a stark difference in how companies are successfully becoming “AI-native.”
- Set Hard Constraints: The most effective leaders aren’t just writing memos; they are creating hard constraints that force change. Examples include: “We will not add new headcount until you prove AI cannot solve the problem,” or setting a goal to operate with 15% of the team size of a competitor at the same revenue scale.
- Address the Anchors: Every organization has catalysts (early adopters), converts (who will adapt with structure), and anchors (who resist change). The companies making the fastest progress are setting hard deadlines for anchors to either make the transformation or be exited from the business. This is viewed not as a tool change, but a fundamental culture change that requires density to succeed.
- Find the Bottleneck: If you only use AI to accelerate one part of a system (e.g., engineering), you simply move the bottleneck elsewhere (e.g., to product management). You must analyze and accelerate the entire system (e.g., code, design, and product) to see real gains in output.