Why Most Startups Build the Wrong Product and How to Get It Right | Ep 274 | DevReady Podcast скачать в хорошем качестве

Why Most Startups Build the Wrong Product and How to Get It Right | Ep 274 | DevReady Podcast

In this episode of the DevReady Podcast (   / aerionautech  ) , Anthony Sapountzis (  / anthony-sapountzis  ) , CTO and Co-Founder of Aerion Technologies and DevReady.ai | AI-Powered App Planning for Non-Tech Founders (http://devready.ai/) , is joined by Karina Carter (  / karina-carter  ) , Fractional Chief Product Officer and Leadership Coach. With over 12 years of experience spanning the United Nations, government research, startups and global tech companies, Karina brings a deeply practical perspective on modern product leadership. She shares insights from her journey into product management, her work building technology across complex markets like China, and her current role helping underperforming companies realign strategy, teams and execution. This conversation is essential listening for founders, product leaders and teams looking to build better software through strong product strategy, customer insight and disciplined decision making. Karina explains how transitioning from academic research at the UN into product allowed her to move faster, work directly with customers and turn data into action. Her experience running a venture studio in China required building bespoke technology to operate across the Great Firewall, giving her a unique perspective on solving complex problems in constrained environments. Today, as a fractional CPO, she is often brought into organisations that are struggling to perform, where she audits product strategy, uncovers misalignment and identifies untapped opportunities hidden in existing data. These discoveries frequently lead to new use cases and significant revenue growth without increasing team size. The discussion highlights how cultural context, data literacy and customer understanding are foundational to sustainable product growth. A core theme of the episode is Karina’s belief that better products do not come from bigger teams, but from people with a growth mindset and a sense of radical responsibility. She explains how she uses data to understand what is happening inside a product, then pairs that insight with deep customer conversations to uncover why it is happening. Customer interviews, she argues, are not about asking users what to build, but about understanding their real problems, fears and motivations. This approach allows product, design and engineering teams to focus on value rather than features. Anthony reinforces that most customers buy based on perceived value, not technical specifications. The conversation also explores why so much user research fails to deliver meaningful insight. Karina highlights how confirmation bias, inconsistent interview questions and poor research design often lead teams to hear only what they want to hear. She stresses the importance of structured interview frameworks, representative sampling and an understanding of cognitive bias when interpreting feedback. Together, Anthony and Karina explain why product teams should not overreact to the loudest customers, who are often a small and unrepresentative minority. Instead, feedback should be evaluated holistically, guided by a clear product vision, strategy and well defined OKRs, with every product decision treated as a hypothesis to be tested after launch. Finally, Anthony and Karina discuss the impact of AI tools like ChatGPT and vibe coding platforms on modern software development. While Karina supports experimentation and creative exploration using AI, she warns that these tools can accelerate poor decisions if foundational product thinking is skipped. They explore the risks of AI hallucinations, overreliance on automated analysis and the erosion of critical thinking in product teams. Both agree that AI is most powerful when used to support synthesis, competitor analysis and ideation, not as a replacement for human judgement. The episode concludes with a clear message that great products are built through disciplined discovery, thoughtful design and human insight, with AI used as an assistant rather than the decision maker.