Happy December! You might notice the newsletter looks a little different this month. From now on, we’ll be focusing on the commercial side of the tech business. Why? Because we believe that mastering commercial skills is essential for product managers. Our mission is to help you grow into an exceptional product professional with standout business acumen. Your feedback means the world to us—let us know what you think!
Introduction
Welcome to the December edition of The Business of Product, where we explore the intersection of technology, product development, and business. This month, we’re diving into the latest news impacting product managers and tech leaders, breaking down key stories shaping the industry, and unpacking business concepts that sharpen your decision-making skills. Whether you're deep in a launch or navigating a strategy shift, this newsletter is here to keep you ahead of the curve.
In the News
Tidal & Applovin Lay Off All Product Managers
Both Tidal (Jack Dorsey, CEO) and AppLovin (which has been one of the hottest tech stocks this year) announced that they are laying off their entire product management staff in an effort to become leaner and more agile. Fortune CNBC
Advancements in AI Agents
Agentic AI is revolutionizing both customer and employee experiences by enabling AI systems to autonomously plan, adapt, and execute tasks without explicit human directives. This advancement is reshaping creative industries, automating roles in content generation and design, and marking a significant step toward artificial general intelligence. cmswire
Software Stocks Surge Post-Election
Following the recent presidential election, software stocks have surged, with analysts expecting the rally to continue. Investors are optimistic about software companies' growth potential in a favorable economic climate. MarketWatch
Microsoft and Anthropic Deepen Ties
After investing $4 billion in Anthropic in September, these trainlblazers are deepening their strategic collaboration, with Anthropic naming Amazon Web Services (AWS) its primary training partner, in addition to being its primary cloud provider. This builds on their $4 billion partnership announced last September and the rapid adoption of Anthropic's Claude models on AWS. Anthropic will now use AWS Trainium and Inferentia chips for training and deploying future foundation models, while both companies work together to enhance Trainium's hardware and software capabilities. aboutamazon
See further analysis on this relationship in the Inside the News section.
Inside the News
Inside the News takes an in-depth look at today's important news. This week? Amazon’s Anthropic Investment: Strategic AI Move or Late-to-Market Gamble?
Amazon’s renewed discussions about investing billions more in AI startup Anthropic have raised eyebrows across the tech and business worlds. Having already committed $4 billion to the OpenAI competitor last year, Amazon is reportedly seeking to deepen its relationship with the company. But is this a strategic leap into the AI frontier or a reactive play to keep up with rivals like Microsoft and Google? With Anthropic leveraging Amazon’s cloud infrastructure and chips to power its AI models, the implications of this partnership could significantly shape Amazon’s future in artificial intelligence.
The State of Amazon in AI
Amazon’s position in AI is markedly different from its competitors. While companies like Google and OpenAI have made headlines with cutting-edge research and consumer-facing tools, Amazon has focused largely on applied AI, integrating it into its AWS ecosystem and consumer products like Alexa. However, these efforts have met mixed success. Alexa, once a trailblazer, now faces declining growth, while AWS competes in an increasingly crowded cloud market where AI capabilities are a key differentiator.
Unlike Google’s diverse portfolio of AI applications and OpenAI’s first-mover advantage in generative AI, Amazon lacks a flagship product showcasing leadership in foundational AI. This has led to a perception that Amazon is lagging in innovation—a narrative the company likely hopes to counter with deeper ties to Anthropic.
Strategic Implications of the Anthropic Partnership
For Amazon, the partnership with Anthropic serves several strategic purposes. First, it reinforces AWS’s value proposition. By offering customers early access to Anthropic’s advanced AI models, Amazon can position AWS as a must-have platform for companies integrating generative AI into their workflows. This is particularly critical as Microsoft Azure and Google Cloud both capitalize on partnerships with leading AI players.
Second, Anthropic’s computational demands play directly into Amazon’s hardware strategy. By training its models on Amazon’s proprietary chips, such as Inferentia and Trainium, Anthropic not only showcases Amazon’s hardware capabilities but also drives sales of these specialized processors. This could help Amazon close the gap with NVIDIA, the current market leader in AI-focused hardware.
Third, this move aligns with a broader trend among tech giants to integrate external AI expertise into their ecosystems. While Google’s DeepMind and Microsoft’s OpenAI partnership highlight in-house and collaborative models, Amazon’s investment signals a different approach: acquiring influence in promising startups to leapfrog its competitors.
The Risks and Challenges
Despite its massive potential, like all investments, it comes with significant risks. Amazon’s decision to rely on an external partner like Anthropic underscores its current inability to develop competitive foundational models in-house. This contrasts with Google’s self-reliant AI strategy and OpenAI’s sole focus on AI innovation. If Anthropic cannot maintain its technological edge or align with Amazon’s business priorities, the partnership could falter.
Moreover, the market may question whether AWS clients will find exclusive access to Anthropic’s tools compelling enough to switch providers. Anthropic’s reputation for safe and ethical AI, while admirable, has yet to translate into a dominant market position. Amazon must ensure its investment yields tangible value—not just for Anthropic but for AWS customers seeking cutting-edge solutions.
Big Opportunities Ahead
Still, there’s no denying that this partnership opens doors to significant opportunities. Anthropic’s AI models could bolster Alexa, revitalizing Amazon’s struggling smart home ecosystem. More sophisticated generative AI capabilities could make Alexa a true differentiator in an industry crowded with voice assistants.
On the enterprise side, this collaboration enhances AWS’s position as a leader in generative AI services. Anthropic’s models could attract startups and enterprises eager to integrate AI into their products, further entrenching AWS as a vital partner in AI-driven innovation.
Amazon’s chips also stand to benefit. As Anthropic scales its AI operations, demand for Amazon’s custom hardware could grow, potentially elevating Amazon as a key player in AI-focused chip manufacturing. This synergy could reshape the competitive dynamics between Amazon, NVIDIA, and other hardware giants.
Final Thoughts
Amazon’s growing investment in Anthropic is both a bold opportunity and a tacit acknowledgment of its challenges in AI innovation. By partnering with an emerging leader like Anthropic, Amazon can quickly scale its AI capabilities, leveraging the startup’s technology to enhance AWS and other services. However, success hinges on how well Amazon integrates this partnership into its broader strategy.
As the AI race intensifies, Amazon’s moves underscore the importance of agility, collaboration, and long-term vision in navigating the rapidly evolving landscape. Whether this partnership cements Amazon’s leadership or highlights its vulnerabilities will depend on its ability to capitalize on Anthropic’s strengths and address its own gaps in AI.Add your text here. Edit to add dynamic values like name, email and more.
Techonomics
Techonomics breaks down essential business concepts to help you sharpen your strategic thinking and product management skills. This month we’re diving into network effects—a powerful concept that drives the growth of many of today’s most successful tech platforms.
What Are Network Effects?
Network effects occur when the value of a product or service increases as more people use it. It’s a self-reinforcing dynamic that leads to exponential growth. The classic example is social media—each additional user adds to the value of the platform by creating more connections and content, making it more valuable to existing users. This is why Facebook, Instagram, and LinkedIn have grown into dominant forces in their respective spaces.
But network effects aren’t just limited to social media. They’re the engine behind many other digital platforms. Uber becomes more valuable as more drivers join the network because this reduces wait times for passengers. Similarly, Amazon’s marketplace becomes more attractive as more sellers and products are added, providing consumers with more choices and competitive prices.
Types of Network Effects
Understanding the different types of network effects is key for product managers and business leaders. Here are two of the most common:
Direct Network Effects: The value of a product increases directly as the number of users grows. Social media platforms are a textbook example: as more users join, existing users gain more potential connections and content, making the platform more engaging. This positive feedback loop is critical to scaling such platforms.
Indirect Network Effects: In some cases, a product's value increases due to the growth of complementary products or services. Two-sided marketplaces like Uber and Airbnb illustrate this. As more drivers sign up for Uber, it becomes easier and faster for riders to find transportation. Similarly, as more passengers use Uber, it becomes more lucrative for drivers to participate, fueling growth on both sides of the market.
Network Effects as a Competitive Moat
Network effects can also serve as a powerful competitive moat, helping companies defend their market position and build long-term value. In business terms, a "moat" refers to a sustainable competitive advantage that protects a company from competitors. Network effects are one of the most durable types of moats, particularly in digital markets.
Platforms like Amazon, Google, and Facebook are notoriously difficult to disrupt because their massive user bases provide immense value to both existing and potential users. For instance, a new social media platform would face an uphill battle competing with Facebook, where users already have well-established connections and interactions. The larger the network, the more entrenched the company becomes, creating a significant barrier to entry for new competitors.
However, network effects also require careful management. Companies must continue to deliver value to users as the network grows, or risk losing the engagement that makes the platform valuable in the first place. Balancing growth with user experience is key.
Why Network Effects Matter for Product Managers
For product managers (PMs), understanding network effects is essential, especially if your product benefits from a large user base or operates in a marketplace model. Products that harness network effects can grow exponentially if managed well, but failing to create or maintain these effects can lead to stagnation or even decline.
PMs should consider how their product scales with user growth. When planning new features, it’s crucial to think about how they will interact with the existing user base and whether they will strengthen the network effects that drive value. For two-sided platforms, focusing on balancing both sides (e.g., drivers and passengers, buyers and sellers) is often the key to unlocking growth.
The Strategic Takeaway
Network effects are a powerful driver of growth and a formidable moat in the digital economy. For product managers, leveraging network effects can be the key to transforming a product from a niche offering to a market leader. But achieving and maintaining these effects requires deliberate planning and careful attention to how user growth impacts the broader platform. When done right, network effects can provide an engine for exponential growth and a lasting competitive advantage in the marketplace.
5 Questions
"5 Questions" is an interview with a product business leader exploring their challenges, opportunities and perspectives.
The Chief Product and Technology Officer (CPTO) is a hybrid role that combines responsibility for both product management and technology strategy. Overseeing the entire product lifecycle—from design to technical execution—the CPTO ensures that product innovation aligns with scalable technology. This role has grown as companies seek tighter integration between product and engineering, especially in tech-driven industries.
This month, we’re excited to feature Wolfgang Hilpert, Chief Product & Technology Officer at JTL Software. With over two decades of leadership experience at companies like IBM, Microsoft, SAP, and MarketLogic, Wolfgang is known for driving transformational change in product and engineering teams. His expertise spans agile transformation, SaaS delivery, and leading complex global organizations through growth and innovation. A passionate advocate for customer value and business outcomes, Wolfgang's approach to balancing product-led growth with scalable technology has made him a highly sought-after leader in the industry.
Q1: What was the transition like from leading dedicated product or engineering teams to managing both as a combined CPTO role?
Wolfgang: The transition to a combined CPTO role was both challenging and rewarding. Leading either product or engineering teams requires a deep focus, but overseeing both forces you to think holistically about how technology underpins product strategy and vice versa. The key shift is balancing the two perspectives—ensuring engineering builds scalable, reliable platforms while also keeping the product vision aligned with customer needs. This role requires constant communication between teams to bridge gaps and break silos, which is something I enjoy because it fosters faster innovation and better outcomes for the customer. Having led both types of teams before, I could draw on my experience to integrate the two seamlessly.
Q2: As CPTO, how do you prioritize long-term technology investments against the short-term demands of hitting product milestones?
Wolfgang: Prioritizing long-term technology investments while meeting short-term product goals is one of the biggest challenges in this role. I approach this by clearly defining the roadmap and aligning both technology and product teams around shared goals. For example, in my time at JTL Software and Market Logic, I ensured that strategic tech investments, like improving test automation or reducing cloud costs, were integrated into our sprint cycles. This way, we're gradually strengthening our infrastructure without compromising on short-term product releases. A key element is transparency—communicating the value of long-term investments to all stakeholders helps balance immediate product demands with future-proofing our technology stack.
Q3: Are there specific areas where you consciously draw a line between technical decisions and functional/business considerations, and how do you manage the overlap between the two?
Wolfgang: Absolutely. The line between technical and business decisions can blur, but I try to keep it clear by always asking, "How does this serve the customer or the business?" For example, when we're considering a technology upgrade or a platform change, I ensure that the technical decision doesn't just make sense from an engineering perspective but also aligns with business goals like cost savings or improved time-to-market. Managing the overlap often involves trade-offs; sometimes we choose a solution that's technically elegant but may require more time to implement, and other times we prioritize speed to market, especially if the business impact is significant. The key is constant communication between the engineering and product teams.
Q4: Are there particular types of companies or product portfolios where a combined CPTO role is more effective than having separate product and technology leadership, and why?
Wolfgang: A combined CPTO role works best in companies with a strong focus on product-led growth and fast-paced innovation cycles, like JTL Software. When product and technology are closely intertwined, such as in AI-based platforms or complex marketplaces, having one leader for both areas helps maintain alignment and ensures that the technical execution matches the product vision. For instance, in organizations that require rapid iteration and deployment, separate leadership can create bottlenecks due to differing priorities. A CPTO role can break those silos and foster faster decision-making while keeping both product strategy and technical execution tightly coordinated.
Q5: What advice would you offer organizations that are struggling to define or effectively combine the product and technology leadership roles?
Wolfgang: My advice would be to first establish a clear shared vision and ensure both product and technology teams are aligned around the same goals—delivering customer value. Start by identifying the pain points between your current product and engineering collaboration. If you notice constant friction or misalignment, that’s a sign that a unified CPTO role could help streamline decision-making. When combining these roles, focus on appointing someone who has a deep understanding of both areas but also values cross-functional collaboration. You also need to ensure there’s a framework in place for balancing short-term product needs with long-term technical investments, as that’s where most conflicts arise. Finally, keep communication open and transparent, so both teams feel their priorities are heard and aligned.
We hope you enjoyed our new focus on building great product businesses. See you again next month!
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