Chesterton's Fence, Second-Order Thinking, and AI: A New Paradigm for Product Managers
In the rapidly evolving world of product management, the advent of artificial intelligence (AI) and tools like ChatGPT have revolutionized the way we approach decision-making and problem-solving. However, as we embrace these new technologies, it's crucial to remember the wisdom of Chesterton's Fence, a principle that encourages second-order thinking before making changes to a system. This principle becomes even more critical when considering the first two weeks of a customer's journey with a product, a period that can make or break their relationship with it.
Chesterton's Fence: A Primer
Chesterton's Fence is a concept derived from a quote by writer G. K. Chesterton. It suggests that before removing a fence (or making a change), one should first understand why it was put up in the first place. This principle encourages us to consider the potential second and third-order effects of our actions, thereby avoiding unintended consequences that could cause more harm than good.
The Intersection of Chesterton's Fence and AI in Product Management
In the context of product management, AI tools like ChatGPT have become increasingly prevalent. Lenny Rachitsky's article, "How to use ChatGPT in your PM work," provides real-life examples of how PMs are using ChatGPT for tasks such as collecting and summarizing user feedback, coming up with product name suggestions, strengthening arguments, and inspiring roadmap ideas.
However, as we integrate these AI tools into our workflows, it's essential to apply the principle of Chesterton's Fence. Before replacing traditional methods with AI-driven ones, we should understand why the existing systems were put in place and consider the potential consequences of changing them.
For instance, consider a PM deciding to replace manual user feedback analysis with an AI tool. Before making this change, they should understand why manual analysis was initially chosen, what benefits it offers, and what potential issues could arise from switching to an AI-driven method.
Second-Order Thinking and the First Two Weeks of the Customer Journey
The first two weeks of a customer's journey with a product are critical. It's during this period that customers form their initial impressions of the product, and these impressions can significantly influence their long-term relationship with it. A great onboarding experience is essential, but it's not enough. PMs need to understand what users are doing once they've signed up and actively use the product.
This is where second-order thinking comes into play. It's not enough to simply observe user behaviour; PMs need to understand why users are behaving the way they are and what underlying needs or desires are driving their actions. They need to consider not just the immediate effects of their decisions, but also the potential second and third-order effects.
For example, if data shows that users are frequently visiting a particular feature but not engaging with it, a first-order thinker might conclude that the feature is not valuable and consider removing it. However, a second-order thinker would ask why users are visiting the feature in the first place and what need it might be fulfilling, even if it's not being used. Perhaps the feature is not intuitive enough, or maybe it's not meeting the users' needs in the way they expected. By understanding the why behind the what, PMs can make more informed decisions that better serve their users.
The Power of Second-Order Thinking in AI-Driven Product Management
The power of second-order thinking becomes even more critical when AI is involved. AI tools, while powerful, are not infallible. They can generate unexpected results, and their decision-making processes are often opaque. Therefore, understanding the rationale behind their recommendations and considering the potential consequences of following them is crucial.
For example, if ChatGPT suggests a new feature based on user feedback, a PM should not blindly implement it. They should consider why the current features exist, how the new feature would fit into the existing system, and what potential second and third-order effects it could have.
## The Future of Product Management: Second-Order Thinking and Rapid Response
Looking ahead, the ability to apply second-order thinking and respond quickly to insights gained during the critical two-week initial user journey will become increasingly important in product management. As AI tools become more sophisticated and integral to our workflows, the need for human insight and critical thinking does not diminish; instead, it becomes even more vital.
AI can provide us with data, but it's up to us to interpret that data, understand the why behind the what, and make informed decisions that serve our users best. This requires not just understanding the immediate effects of our actions, but also considering the potential second and third-order effects.
Moreover, the ability to respond quickly to these insights is crucial. The first two weeks of a user's journey with a product are a critical period, and the ability to make rapid changes in response to user behavior during this time can significantly impact the product's success.
Next…
As we continue to integrate AI tools like ChatGPT into product management, the principle of Chesterton's Fence remains as relevant as ever. It reminds us to apply second-order thinking, understand the rationale behind existing systems, and consider the potential consequences of our actions. By doing so, we can harness the power of AI while mitigating potential risks, leading to more effective and responsible product management.
In the end, the goal is to create products that users not only use but love. And to achieve this, we need to understand our users deeply, consider the broader implications of our decisions, and be ready to adapt quickly based on our insights. This is the future of product management, and it's a future that, with the right approach, promises to be incredibly exciting.
