  Architecting software-intensive systems can be a complex process. It deals
with the daunting tasks of unifying stakeholders' perspectives, designers'
intellect, tool-based automation, pattern-driven reuse, and so on, to sketch a
blueprint that guides software implementation and evaluation. Despite its
benefits, architecture-centric software engineering (ACSE) inherits a multitude
of challenges. ACSE challenges could stem from a lack of standardized
processes, 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 with
artificially intelligent decision support to enable rapid architecting in a
human-bot collaborative ACSE. An emerging solution to enable this collaboration
is ChatGPT, a disruptive technology not primarily introduced for software
engineering, but is capable of articulating and refining architectural
artifacts based on natural language processing. We detail a case study that
involves collaboration between a novice software architect and ChatGPT for
architectural analysis, synthesis, and evaluation of a services-driven software
application. Preliminary results indicate that ChatGPT can mimic an architect's
role to support and often lead ACSE, however; it requires human oversight and
decision support for collaborative architecting. Future research focuses on
harnessing empirical evidence about architects' productivity and exploring
socio-technical aspects of architecting with ChatGPT to tackle emerging and
futuristic challenges of ACSE.
