Building slides in one shot feels faster. It isn’t. You paste a wall of text, the model guesses what you want, and half the time it guesses wrong. Wrong audience, wrong tone, wrong points bolded. Now you’re rewriting twelve slides instead of fixing three lines.
Here’s the idea a Redditor posted in r/PromptEngineering: split the job into two prompts instead of one. First prompt, the model isn’t allowed to build anything. It has to tell you the goal of the deck, who’s reading it, and the 5 to 7 points worth their own slide, then wait for you to correct it. Second prompt, only after you’ve fixed its assumptions, it builds the actual outline: one point per slide, headline plus 3 bullets, plain language, and it flags any point too thin to carry a slide on its own.
Old way vs new way:
- 🔹 One-shot: paste text, get slides, discover the model assumed the wrong audience, rebuild the whole deck
- 🔹 Two-step: paste text, model states its plan, you correct 3 lines, THEN it builds slides that actually land
The contrast is basically “catch the mistake when it’s a sentence” vs “catch it when it’s a slide deck.” A 3-line plan is cheap to fix. A finished set of slides is not. And the “too thin to fill a slide” flag does something extra: it stops the model from padding a weak point with fluff just to hit slide count.
How to run it:
- Paste your source text and explicitly tell the model: do NOT make slides yet.
- Ask it three questions first: what’s the single goal (inform, persuade, teach, update), who’s the audience and what do they already know, and what are the 5-7 points that deserve their own slide.
- Read its answers. If it assumed the wrong audience (a status update read as a sales pitch, which is exactly what happened to one commenter three decks in), correct it right there.
- Only then send the build prompt: one point per slide, headline plus 3 bullets max, flag thin points.
- Fix only what got flagged. Ship.
Next deck you build, try the two-step before you build anything. Cheap correction beats expensive rework, every time.
Frequently Asked Questions
Q: Why does the model guess the wrong deck type (like building a sales pitch when I just need a status update)?
Without context, the model defaults to persuasive, polished decks because that’s the most common use case in its training data. Once you specify the actual goal (inform vs. persuade vs. teach), it resets its assumptions and structures content to match. The comment about getting a sales pitch for an internal status update is exactly why this two-step catches that before you waste time rewriting.
Q: Doesn’t adding a planning step make this slower?
Initially it feels like it, you’re asking questions before building. But the author found it’s actually faster overall because you avoid rewriting entire 12-slide decks. A 3-line plan is cheap to correct; a deck is not. Plus, you catch thin content upfront instead of discovering it mid-presentation.
Q: How do I know if a point is “too thin to fill a slide”?
If the source text barely mentions a topic and you’d have to invent details to fill 3 bullets, that’s too thin. The model should flag these during step two, it’s your signal to either combine that point with another, pull in more source material, or cut it entirely. This prevents padding slides with obvious fluff.
Q: What if the model still gets the audience wrong after step one?
It happens, sometimes your description doesn’t match what the model thinks that audience needs. If the outline still feels off, give concrete feedback: “This audience already knows X, so skip that” or “They need more detail on Y because they’re new to this domain.” Then regenerate the outline. The goal/audience pins are usually the sticking point, so extra precision there saves the most rework.
Stop pasting text and asking for slides cold, do this two-step instead
by u/netra_2428 in PromptEngineering