Context compression is probably more important than prompt engineering
Hot take: For long AI workflows, context management matters more than prompt engineering. A perfect prompt can't save a conversation that's 80% irrelevant context. I've started treating long AI sessions like this: Persistent project brief Decision logs Context checkpoints Compression summaries Reusable templates The quality difference after 50+ messages is huge. Does anyone els
PROMPT
Hot take: For long AI workflows, context management matters more than prompt engineering. A perfect prompt can't save a conversation that's 80% irrelevant context. I've started treating long AI sessions like this: Persistent project brief Decision logs Context checkpoints Compression summaries Reusable templates The quality difference after 50+ messages is huge. Does anyone else actively compress conversations instead of continuously extending them? I documented the workflow and examples here: https://medium.com/@nagatomopedro05/why-every-long-ai-session-eventually-falls-apart-697fc4b140f9 submitted by /u/ClickOk5811 [link] [comments]
Replace the bracketed fields with your own goal, audience and context.
Paste the prompt into the recommended tool; treat the first output as a draft.
Point out gaps, add examples, and define the output format you want more precisely.
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