From Hype to Reality: Building AI Products That Solve Real Problems

The Pitfalls of Building AI Products: Solving Real Problems vs. Utilizing Emerging Technology

In the fast-paced world of technology startups, the allure of building AI products is strong. The promise of cutting-edge technology and the potential for exponential growth can be enticing. However, a recent post has highlighted the pitfalls of this approach and the importance of starting with a real user need rather than simply wanting to use an emerging technology.

The author of the post argues that building an AI product should not be the primary focus for new startups. Instead, they should prioritize solving real problems that customers are facing. Starting with a genuine user need ensures that the product will add value and meet the expectations of customers.

The author cites the example of chatbots, a technology that has resurfaced in recent years. Despite the advancements in language processing with models like OpenAI’s GPT, the author argues that most people dislike interacting with chatbots. They feel that chatbots cannot match the experience of speaking with a real human being, and often fail to provide effective solutions to problems. Therefore, building a customized chatbot purely because “GPT is cool” is unlikely to lead to a sustainable business or solve a genuine user need.

The author highlights the challenge that technologists face when it comes to understanding user needs. They tend to take comfort in building technology rather than investing time in problem discovery. However, the best approach is to prioritize understanding the problem and then iterate and build accordingly. This requires a shift in mindset from focusing on technology to focusing on solving real problems and meeting user needs.

The post also addresses the issue of chatbots acting as a filter to divert customers from reaching human support. While some chatbots may be genuinely helpful, many are seen as obstacles to reaching a human who can actually solve the problem. Users often prefer a human connection and being listened to, rather than receiving mindless automated responses. The author argues that chatbots should not be seen as a solution to all customer service issues, and that empowering chatbots to actually solve problems is a complex challenge.

At the heart of the discussion is the importance of acknowledging the limitations of technology and the need to focus on real user needs. Building an AI product for the sake of using emerging technology is not a guarantee of success. Instead, startups should prioritize problem discovery, create a feedback loop to iterate and improve, and ensure that the product adds real value for users.

While there may be instances where chatbots or AI-powered solutions can be effective, the key is to approach them with a clear understanding of the problem they are solving and with the goal of enhancing the overall user experience.

In conclusion, the post serves as a reminder for new AI startups to prioritize user needs over the allure of emerging technology. Building AI products should not be the primary focus, but rather a means to solve real problems and create value for customers. By starting with a genuine user need, startups can ensure that their products meet expectations and have the potential for long-term success.

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