In the rapidly advancing field of artificial intelligence, software development has emerged as a key area of innovation. Despite the plethora of \emph{general-purpose} AI assistants available, their effectiveness diminishes in complex, domain-specific scenarios. Noting this limitation, both the academic community and industry players are relying on \emph{contextualized} coding AI assistants. These assistants surpass general AI tools by integrating proprietary, domain-specific knowledge, offering precise and relevant solutions. Our study focuses on the initial experiences of 62 participants that used a contextualized coding AI assistant — named StackSpot AI— in a controlled setting. According to the participants, the assistants’ use resulted in significant time savings, easier access to documentation, and the generation of accurate codes for internal APIs. However, challenges like variable responses and limitations in handling complex codes were observed. The study’s findings, detailing both the benefits and challenges of contextualized AI assistants, underscore their potential in revolutionizing software development practices, while also highlighting areas for further refinement.