🤖 AI Summary
A developer building an AI orchestration platform (Maitento/ScrumBuddy) created an AI-first programming language, compiler, assembler, virtual machine and stdlib in five days with Claude AI acting as co-architect. The project aimed to replace brittle C# glue (JSON, string substitutions, tangled control flow) with a first-class language for model calls, prompt flows, data munging and orchestration logic. By day one the author had designed a simple assembly, bytecode and VM supporting stacks, conditionals and syscalls; subsequent days produced a tokenizer, AST, a working expression parser (using a descendant/precedence approach) and final assembly output. Claude helped most effectively as a high-level sparring partner—guiding parsing strategies, helping design expression precedence and generating complex test scripts—rather than autonomously writing production code.
The significance for the AI/ML community is twofold: practically, it demonstrates how LLMs can dramatically accelerate complex systems engineering when paired with an experienced engineer (the author estimates roughly a 2x speedup), enabling faster iteration of enterprise AI flows; conceptually, it underscores that AI tooling is best used to augment architecting, debugging and test generation rather than replace domain expertise. Key technical takeaways include the importance of explicit control-flow primitives (stacks/syscalls), careful token-reader management during recursive parsing, and leveraging AI to craft tests and analyze verbose runtime logs to rapidly root-cause bugs.
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