"Shipping something to someone always wins," declared Kenneth Auchenberg, partner at AlleyCorp and veteran of Stripe and VSCode, during his address at the AI Engineer World's Fair in San Francisco. His insights, drawn from years of building products for developers, emphasized that the fundamental principles of product development remain paramount, even as artificial intelligence reshapes the technological landscape. Auchenberg’s talk centered on applying a "product builder lens" to the burgeoning AI-native world, arguing that success hinges not on grand, infrequent releases, but on relentless iteration.
A core tenet of Auchenberg’s philosophy is that "it's not the number of big bangs you do... It's the number of iterations you crank at a problem," otherwise known as rapid iterative loops. This principle is more relevant than ever in the age of AI. He illustrated this with the compelling "skateboard to car" analogy: instead of building a car piece by piece—wheels, then chassis, then engine—where a functional product only emerges at the very end, one should build a skateboard, then a scooter, then a bicycle, then a motorcycle, and finally a car. Each stage is a continuously viable product, offering immediate utility and, crucially, immediate feedback.
This continuous feedback loop is essential. "If you can't run your loop in a day, your product development process is broken." Auchenberg stressed the necessity of users seeing something, providing feedback, and allowing for rapid iteration and improvement, ideally within a single day. This demands an intimate understanding of the customer.
He advocated for working with "actual people you know," not just personas, urging developers and product leaders to genuinely understand how users solve problems today. This deep customer knowledge, coupled with an unwavering commitment to rapid iteration, forms the bedrock of successful product development. Writing a press release or launch blog post *before* building, and showing it to prospective customers for feedback, serves as a vital sanity check. It forces specificity and ensures that the proposed solution addresses a real need, preventing the common pitfall of building in a vacuum.
Ultimately, Auchenberg asserted that "nothing is changing about the craft of building products." While AI tools like ChatGPT, Cursor, and Granola are accelerating every aspect of product building, significantly reducing the cost and time associated with development, the core challenge remains. The product work itself—understanding user needs, designing solutions, and iterating based on feedback—is now "more important than ever." The winners in this new era will be those founders and teams who can build tastefully, deeply understand their customers, and maintain an incredibly high iteration velocity. This relentless focus on shipping, iterating, and learning from real users is the enduring path to product success.
