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The arrival of generative AI represents a "meteor" moment for the technology industry—an event so significant that it fundamentally alters the landscape for every company in its path. For product leaders, the challenge isn't just adopting new tools; it is about completely reimagining product strategy from first principles. Paul Adams, Chief Product Officer at Intercom, has navigated this shift firsthand, pivoting an established company to an AI-first approach while managing the complexities of organizational change.
Adams, whose background spans leadership roles at Facebook, Google, and Dyson, argues that the current technological wave is comparable to, if not larger than, the mobile revolution or the internet itself. Survival and success depend on a leader’s ability to map their core value proposition against AI capabilities and to execute with conviction. Beyond AI, effective leadership requires mastering the psychology of failure, understanding market differentiation, and refining the stories we tell about our products.
Key Takeaways
- The "Meteor" Mindset: AI is not a trend to be bolted onto existing products; it is a fundamental shift that requires re-evaluating your product’s core premise to determine if AI can replace or augment your workflow.
- Ship to Learn: Embracing a culture of "ship fast, ship early" is essential for innovation, even if it requires managing the tension between speed and perfection.
- Differentiation vs. Table Stakes: Startups must over-index on differentiation to gain traction, while mature companies must balance innovation with the "boring" table stakes required to retain customers.
- Product Market Story Fit: A great product in a great market can still fail if the narrative doesn't resonate; the story is as critical as the code.
- Avoid Overcorrection: When fixing organizational issues, leaders often "swing the pendulum" too far—such as hiring only specialists after relying on generalists—creating new problems in the process.
The AI Meteor: Redefining Product Strategy
The launch of ChatGPT marked a "before and after" moment for the software industry. For Adams and Intercom, it signaled an immediate need to rip up the existing roadmap and start over. The strategy wasn't to ask how AI could be added to Intercom, but to ask: If we were building this solution today, would it be human-first or AI-first?
Mapping Product Utility to AI Capabilities
To navigate this shift, product leaders must strip their product down to its basic premise. Why do people use it? What specific problem does it solve? Once that foundation is clear, you must rigorously ask: Can AI do this?
The answer generally falls into three categories:
- Total Replacement: The AI can simply do the work. In customer support, this looks like a bot resolving a query instantly without human intervention.
- Augmentation: The AI cannot do the job alone but can significantly enhance human performance (e.g., a "copilot" for support agents).
- Not Yet Possible: Areas where human empathy or complex reasoning still outperform current models.
This is a meteor coming towards you... I think if people don't explore AI properly it will leave them behind.
Organizational Adaptation
Integrating AI isn't just a technical challenge; it is an organizational one. Adams advises against creating a siloed "AI team" that bolts features onto the product. Instead, the goal should be to upskill the entire engineering and product organization. While you need specialized machine learning engineers to build the foundation, product teams must learn to design for probabilistic outcomes rather than deterministic flows.
Leadership Lessons: Failure, Fear, and Resilience
Long before his tenure at Intercom, Adams worked on some of Google’s most notable social experiments, including Google Buzz and Google+. He notes that these projects failed not for a lack of talent, but because they were motivated by fear rather than user needs. The drive to compete with Facebook created a defensive strategy, leading to products that technically functioned but lacked a genuine reason to exist for the user.
The Reality of Public Failure
Resilience is a learned skill, often forged in embarrassing moments. Adams recounts freezing on stage during a major keynote at Cannes, walking off mid-speech, and having to return to finish. The lesson was stark but liberating: the worst-case scenario happened, and he survived. This experience informed his leadership style, which emphasizes psychological safety.
At Intercom, this translates to a "ship to learn" philosophy. Big bets require risk, and risk guarantees occasional failure. If a team is terrified of embarrassment, they will retreat to incrementalism. A healthy product culture accepts that shipping fast means occasionally getting it wrong, provided the team learns and iterates quickly.
Essential Frameworks for Product Decision-Making
Frameworks should be simple tools to aid thinking, not rigid academic exercises. Adams utilizes several mental models to navigate complex product landscapes.
Differentiation vs. Table Stakes
Customers adopt products based on differentiation (the attraction of the new), but they churn or refuse to buy based on a lack of table stakes (the entry requirements). This dynamic shifts as a company matures:
- Startups: Must invest heavily in differentiation. You cannot beat an incumbent by building a better version of their table stakes.
- Scale-ups: Must eventually pivot to build the boring, essential features (reporting, permissions, integrations) to allow larger customers to switch.
Adams notes that Intercom has oscillated between these two, sometimes swinging too far toward differentiation and neglecting basics, or vice versa. The goal is to maintain a conscious balance based on the current strategic phase.
Swinging the Pendulum
When an organization identifies a problem, the natural human reaction is to overcorrect. Adams calls this "swinging the pendulum."
For example, a startup realizing they lack experience might pivot to hiring only seasoned veterans from large corporations. These experts often bring rigid processes that stifle the startup's agility. The result is a swing from "chaos" to "bureaucracy," missing the healthy middle ground. Awareness of this tendency allows leaders to arrest the swing before it reaches the opposite extreme.
Product Market Story Fit
Product Market Fit is a well-known concept, but Adams argues that Product Market Story Fit is equally vital. A great product in a viable market can still fail if the story is convoluted or unappealing.
The "story" is not just marketing fluff; it is the explanation of value. If you cannot explain why your product is better in a way that resonates with the customer's energy and anxiety, the product will not gain traction. This was a critical failure point for early challengers to Spotify—products that were technically superior but failed to capture the narrative.
The Future of Work and Efficiency
The integration of AI into workflows—such as Intercom’s "Finn" chatbot—raises valid questions about the future of jobs. Adams is an optimist, viewing AI as an efficiency multiplier rather than a simple replacement mechanism. In industries like customer support, which suffer from high attrition and burnout, AI can handle the repetitive volume, allowing humans to focus on complex, high-empathy interactions.
For product teams, this efficiency extends to the build process itself. With AI capable of writing code and designing interfaces, the ratios of engineers to product managers may shift. The role of the engineer moves from writing boilerplate code to reviewing and orchestrating AI-generated solutions. This requires a workforce that is adaptable, curious, and willing to continuously update their skills.
Only work on what matters most. Stop worrying about things you can't control.
Conclusion
Whether it is navigating the "meteor" of AI or recovering from a public failure, the common thread in Adams’s strategy is pragmatism combined with high conviction. Leaders must be willing to make big bets, even when the data is ambiguous. By keeping frameworks simple, focusing relentlessly on the customer problem, and maintaining the agility to pivot when the market shifts, product teams can turn existential threats into their next great growth curve.
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