My First Week with GPT-6 Astra (www.vincentschmalbach.com)

A firsthand account from a user testing GPT-6 Astra reveals both its advancements and limitations compared to its predecessor, GPT-5.5 and GPT-5.6 Sol. Astra proves to be a robust model, particularly excelling in front-end work and matching Fable's capabilities while maintaining a higher level of general coding proficiency. However, the user notes a significant downside: Astra tends to take on tasks as long-running projects, consuming excessive time and resources, which undermines its utility for daily workflows. During a week of use, the model quickly depleted two $200 Codex subscriptions, indicating a pattern that mirrors the inefficiency observed with previous versions. This experience highlights a crucial challenge within the AI/ML community—balancing model capability with practical usability. While Astra's enhanced abilities are noteworthy, the issue of task duration and resource consumption may hinder its application in regular coding tasks. OpenAI's usage recommendations underscore the need for users to adjust their strategies, suggesting lower effort settings to mitigate high token usage. Ultimately, while Astra remains a valuable tool for complex tasks, the user has reverted to GPT-5.5 for everyday operations, underscoring the ongoing need for AI models to align better with user productivity and cost expectations in professional environments.