The discussion highlights the limitations of large language model (LLM) function calls and emphasizes that code orchestration can provide a more effective solution. The comments suggest that while frameworks like Hugging Face's Smolagent can be effective, they pose challenges, particularly concerning rollback actions after failures. The need for a stateless but persistent execution environment is stressed, enabling management of long-running AI tasks without high costs or complexity. Additionally, it is noted that architectural patterns from large tech companies related to event sourcing can significantly enhance the durability and manageability of execution environments for AI tasks. Many AI startups are learning these lessons too late, attributed to a slow adoption of these necessary architectural best practices in their frameworks.