GPT-6 Astra 分阶段工作流提升效果
This works really well with GPT-6 Astra: Give it a tweet of an impressive Astra demo. Ask Astra (m...
GPT-6 Astra用户分享分阶段工作流，先用medium版本复制，再用max版本优化，效果更好。
用户发现GPT-6 Astra可通过分阶段工作流提升输出质量。先使用Astra(medium)复制演示并设置目标，再切换至Astra(max)进行优化。这种方法将问题分解，让模型专注特定任务，避免同时处理多任务导致质量下降。通过迭代持续改进结果，比使用大量一次性处理多任务效果更好。
This works really well with GPT-6 Astra: Give it a tweet of an impressive Astra demo. Ask Astra (m...
This works really well with GPT-6 Astra: Give it a tweet of an impressive Astra demo. Ask Astra (medium) to replicate it to the best of its ability and giving it whatever extra instructions and adaptations you want. Set a /goal like provide proof of the results so it has something to compare to. After the first run, switch to Astra (max) and give it instructions to polish. And you can keep doing this iteratively to keep improving results. So there is one component to build and one to optimize/tune. I think it works well because it breaks the problem down and allows the models to focus efforts as opposed to trying to use lots of tokens for many things at once (usually lower quality results). This can essentially be done in one go using subagents and /goal. 💬 8 🔄 2 ❤️ 21 👀 2338 📊 10 ⚡
