What’s your tip for delivering “Context” better to AI models?
Prompt engineering has changed a lot recently. I remember around this time last year, strict prompt engineering rules were a must. From “You are a professional …” persona setting, to zero-shot, few-shot CoT techniques, these were necessary for quality outputs
Nowadays, it feels as if AI models do the engineering all by themselves without user input. They understand us well even if we’re just casually typing (some call it “lazy prompting”, and I even saw a product related to this on PH)
Since Dr. Andrew Ng says “lazy prompting” is a high level skill, I believe prompt engineering still matters.
Clearly conveying context remains crucial. How do you ensure your prompts include clear context?
Personally, I usually separate my [query], [context], and [references] clearly, and I’m meticulous with numbering.
I’d love to hear your solutions!
Replies
I agree—prompt engineering has evolved quickly. The shift from rigid, template-driven prompts to more fluid “lazy prompting” is fascinating, especially as models get better at filling in gaps.
That said, clarity still wins. A few things that help me ensure strong context:
Structure like a Story: Even with casual prompts, I frame my input with a beginning (goal), middle (relevant details), and end (specific ask). It’s like prompt storytelling, and models latch onto that flow.
Use Labels Liberally – explicitly labeling parts of the input—like Goal: Background: or Desired Output—gives the model instant anchors, especially in longer prompts.
Create a Reusable Prompt Framework—For projects like Vibe Village, our AI-generated music battles rely on dynamic, context-rich instructions. A flexible prompt scaffold lets us scale features like personalized trivia or AI song analysis efficiently without starting from scratch each time.
I loved your format with [query], [context], [references] too! Stealing that. 😄
@ed_clark Thanks for sharing your tips and about the project! Well structured prompt scaffold would be the core of such service.
I didn't know AIs like structured storytelling. I'm stealing that too :) Maybe integrating yours and mine, separating sections like [Goal] -[Details] - [Query], and filling them with rich storytelling might ace!
@hyuntak_lee Haha, yes! That [Goal] - [Details] - [Query] flow with storytelling baked in hits the sweet spot. It gives the model just enough direction and room to be creative.
I’ve found that even subtle narrative cues can shift the tone and depth of the output. Prompt structure really is an underrated superpower.
@hyuntak_lee
Totally feel you! Prompting has evolved fast—from super-specific, engineered inputs to models now understanding even casual language. I do think “lazy prompting” works surprisingly well these days, but I still prefer a more intentional approach.
Personally, I’ve developed a structure I stick to—clear roles, defined tasks, and a strong sense of context. I break things down before I even start prompting. It helps me get sharper, more aligned outputs, especially for content-heavy or strategic tasks.
So while models have become smarter, I’ve found that good prompting is still about clarity, not complexity. And honestly, when done right, it saves a ton of time in edits later too.
Would love to hear how others keep their prompts sharp!
@ambika_vaish Thanks for sharing your tips! I agree with your point that well-done prompt saves the edits and jobs later.
One question here, how to you structure the context part when it gets heavy? Do you number them like me or try storytelling like another? I'd love to know how you break things down even after breaking big things down :)
@hyuntak_lee ah I love this question.
depends on the task honestly—if it’s layered, I do number stuff out just to keep clarity. but if it’s brand/creative, I go more narrative, almost like I’m writing to a teammate or briefing someone.
I’ve also noticed that staying close to the “why” keeps everything anchored. otherwise it spirals real fast and the model just… drifts.
@ambika_vaish Oh making "why" clear was the point I was missing! I'm adding [purpose] section in my prompt from now on :)
Many people here say narrative prompting works. I'm gonna set the flow of the the story as if explaining it to a teammate like you said.
I've learned a lot from your comments. Thanks for sharing your insights!
@hyuntak_lee glad it was helpful in some way.
Yeah, the [purpose] bit really keeps things from drifting, especially when the prompt starts getting long or layered.
I’ve been mixing structure and narrative too, depending on what I’m trying to get out of the model. No fixed rules, but having a clear intent upfront usually saves me from backtracking later.
It's fascinating how models now grasp even casual language effortlessly. While "lazy prompting" seems effective, I agree that a deliberate approach is still valuable.
Here are some strategies I use to maintain context in prompts:
Narrative Anchoring: I structure prompts like a story with a clear setup, challenge, and resolution ask to guide the model effectively.
Modular Label System: I mix casual language with strategic labels to provide instant anchors for the model.
Context Compression: I leverage AI's improved inference by implying structure, which helps in maintaining clarity without overloading the prompt.
Dynamic Frameworks: I create reusable templates with variables to streamline the process and ensure consistency.
Progressive Disclosure: I layer context through follow-up prompts, allowing the model to build on previous information.
@anip_satsangi_ I learned a lot from your comment! Thanks for sharing your recipe :) Overloading context might confuse the model, so compressing with some level of technique or progressively revealing the next step seems like good approaches.
Supposing that the model has large context window and can fully handle it, would you still prefer progressively layering the context with follow up prompts rather than dumping all of them (well structured) in the first shot? Because sometimes I sometimes ask the model to ask me back info that's missing, and I think it would have been better if I provided those additional info at the first place.