  This empirical study serves as a primer for interested service providers to
determine if and how Large Language Models (LLMs) technology will be integrated
for their practitioners and the broader community. We investigate the mutual
learning journey of non-AI experts and AI through CoAGent, a service
co-creation tool with LLM-based agents. Engaging in a three-stage participatory
design processes, we work with with 23 domain experts from public libraries
across the U.S., uncovering their fundamental challenges of integrating AI into
human workflows. Our findings provide 23 actionable "heuristics for service
co-creation with AI", highlighting the nuanced shared responsibilities between
humans and AI. We further exemplar 9 foundational agency aspects for AI,
emphasizing essentials like ownership, fair treatment, and freedom of
expression. Our innovative approach enriches the participatory design model by
incorporating AI as crucial stakeholders and utilizing AI-AI interaction to
identify blind spots. Collectively, these insights pave the way for synergistic
and ethical human-AI co-creation in service contexts, preparing for workforce
ecosystems where AI coexists.
