Show HN: SwarmWright, structured multi-agent AI defined in markdowns

This addresses a critical emerging challenge in AI development: managing the complexity and chaos of multi-agent systems. As AI applications evolve beyond single models, orchestrating interactions between autonomous agents becomes paramount. SwarmWright's approach of defining agents in markdown and topology in JSON offers a structured, human-readable method for managing these systems, directly tackling the "growing folder of markdown files and Python scripts" pain point. This formalization of agent communication and interaction patterns is essential for scalability, debugging, and maintainability in complex AI deployments. The emphasis on enforcing a "hard" topology while preserving agent autonomy balances control with flexibility. This product targets organizations building sophisticated AI workflows, providing a framework to transition from ad-hoc scripting to robust, governed multi-agent architectures, a necessary evolution for enterprise-grade AI solutions.