Implications of AI on Software Engineering and Go to Market

The emergence of AI introduces a paradigm shift in software engineering and market strategies. Rather than replacing software engineers, AI creates entirely new roles, enabling a broader audience to develop software without the traditional challenges. This evolution suggests the potential for two distinct products: one tailored for senior engineers who orchestrate AI-driven task execution and another for non-technical users who can now create software independently. In terms of go-to-market strategies, organizations face a dilemma between pursuing traditional Total Addressable Market (TAM) analyses, which can lead to saturated 'red ocean' markets, and exploring the uncharted territories of 'blue ocean' markets where competition is minimal. By focusing on new customer behaviors and workflows enabled by AI, startups can uncover and grow in underserved markets, offering insights into customer needs that incumbents may overlook. This approach aligns more with long-term growth, as it allows companies to innovate while gathering valuable knowledge about new users, potentially leading to distinct market advantages as they encounter competition. Historical parallels can be drawn to the shifts seen in the tech landscape during the 1990s, where innovators forged new opportunities rather than competing in established market spaces.