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Architecting software-intensive systems can be a complex process. It dealswith the daunting tasks of unifying stakeholders' perspectives, designers'intellect, tool-based automation, pattern-driven reuse, and so on, to sketch ablueprint that guides software implementation and evaluation. Despite itsbenefits, architecture-centric software engineering (ACSE) inherits a multitudeof challenges. ACSE challenges could stem from a lack of standardizedprocesses, socio-technical limitations, and scarcity of human expertise etc.that can impede the development of existing and emergent classes of software(e.g., IoTs, blockchain, quantum systems). Software Development Bots (DevBots)trained on large language models can help synergise architects' knowledge withartificially intelligent decision support to enable rapid architecting in ahuman-bot collaborative ACSE. An emerging solution to enable this collaborationis ChatGPT, a disruptive technology not primarily introduced for softwareengineering, but is capable of articulating and refining architecturalartifacts based on natural language processing. We detail a case study thatinvolves collaboration between a novice software architect and ChatGPT forarchitectural analysis, synthesis, and evaluation of a services-driven softwareapplication. Preliminary results indicate that ChatGPT can mimic an architect'srole to support and often lead ACSE, however; it requires human oversight anddecision support for collaborative architecting. Future research focuses onharnessing empirical evidence about architects' productivity and exploringsocio-technical aspects of architecting with ChatGPT to tackle emerging andfuturistic challenges of ACSE.

Towards Human-Bot Collaborative Software Architecting with ChatGPT