While scholars have long studied knowledge search from a problem-solving perspective, research examining how technological changes shape the specific components of knowledge search, namely problem formulation and solution finding, remains scant. This study bridges this gap by teasing apart these components and examining how Artificial Intelligence-Generated Content (AIGC) technologies affect the solution finding process. Leveraging a quasi-experimental design, our analysis of data from StackOverflow, a popular platform for crowdsourcing coding knowledge, shows that the likelihood of individuals obtaining potential solutions increases with the introduction of ChatGPT, after we control for changes in problem formulation. However, this increase does not lead to an increasing likelihood of obtaining an accepted solution and instead results in a prolonged duration for locating an accepted solution. Additionally, we also explore how the direction of individuals’ knowledge search (search depth and search domain) moderates these effects, and we attribute such heterogeneity to varying capabilities of solution evaluation.