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ChatGPT Central
Happy halloween đ! In todayâs edition, weâre giving you a swipe file of 9 proven prompt frameworks you can plug into ChatGPT right now. If youâve ever battled vague outputs or meandering answers, these give you role, objective, and structure in seconds.
We also added two timely insights: why shorter, clearer instructions often outperform bloated prompts, and how new memory features across AI tools change how much context you need to repeat. Skim it, steal it, and ship something youâre proud of in under 10 minutes. If this helps, forward it to one operator who needs a win this week.
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Prompt Frameworks that Just Work ⤾ď¸
The APE, ROSES, TAG, IDEA, PRO, CLEAR, STAGE, PEEL, and DRIP frameworks give you crisp scaffolds: define role and objective, set steps, include an example, and cap with style or parameters. Theyâre built for quick, repeatable results across content, planning, and optimization tasks.
Two fresh notes to upgrade your usage:
Keep it lean. Longer prompts are not automatically better. Irrelevant or poorly structured detail can hurt output quality, while focused structure improves results. Recent guidance echoes this: avoid prompt bloat and tailor length to task complexity.
Also, newer studies show performance can rise with length only when the added detail is relevant to the domain and phrasing is deliberate.
Memory matters. ChatGPT and Claude now offer enhanced memory options, reducing how much context you must restate. Use memory for stable preferences and recurring project facts, then keep prompts tightly scoped to the task at hand. You can review or disable stored memories anytime.
Action step: save the 9 frameworks as text snippets. For each recurring task, pin one template plus one example. When you need polish, add âRoleâ and âStyleâ lines from ROSES, then cap with DRIP-style parameters like word limit, audience, and tone. Youâll see faster, cleaner outputs and less back-and-forth.
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