•The coordination challenges in multi-agent LLM systems are fundamental distributed systems problems, not merely a lack of intelligence in current AI models.
•Expecting future 'smarter' AGI models to spontaneously solve coordination is a fallacy, as impossibility results in distributed computing apply regardless of agent capabilities.
•Building robust multi-agent software requires dedicated formalisms, languages (like choreographic languages), and tooling to manage interactions and achieve consensus, similar to traditional distribut...
•A developer realized an eight-year-long dream of building high-quality SQLite devtools in just three months.
•The primary accelerator for this rapid development was the systematic use of AI coding agents.
•The resulting tool, Syntaqlite, fills a crucial gap for SQLite and custom SQL dialects like PerfettoSQL, demonstrating AI's potential to tackle complex, previously daunting projects.
•Imbue's `mngr` tool enables launching and orchestrating hundreds of parallel AI agents (specifically Claude) for complex tasks.
•A case study demonstrates `mngr` using these agents to *test and improve* its own documentation and test suite.
•The process involves converting tutorial scripts into pytest functions, with agents executing, debugging, and refining them.
•This AI-driven testing approach highlights unclear interfaces and points to a future of more composable, scalable, and self-improving software development.
•The coordination challenges in multi-agent LLM systems are fundamental distributed systems problems, not merely a lack of intelligence in current AI models.
•Expecting future 'smarter' AGI models to spontaneously solve coordination is a fallacy, as impossibility results in distributed computing apply regardless of agent capabilities.
•Building robust multi-agent software requires dedicated formalisms, languages (like choreographic languages), and tooling to manage interactions and achieve consensus, similar to traditional distribut...
•A developer realized an eight-year-long dream of building high-quality SQLite devtools in just three months.
•The primary accelerator for this rapid development was the systematic use of AI coding agents.
•The resulting tool, Syntaqlite, fills a crucial gap for SQLite and custom SQL dialects like PerfettoSQL, demonstrating AI's potential to tackle complex, previously daunting projects.
•Imbue's `mngr` tool enables launching and orchestrating hundreds of parallel AI agents (specifically Claude) for complex tasks.
•A case study demonstrates `mngr` using these agents to *test and improve* its own documentation and test suite.
•The process involves converting tutorial scripts into pytest functions, with agents executing, debugging, and refining them.
•This AI-driven testing approach highlights unclear interfaces and points to a future of more composable, scalable, and self-improving software development.
