GenAI & Creative Practices: Stop Treating Prompts Like Spells

I keep seeing the same mistake in "GenAI for creatives" conversations: we talk about prompts like they're the creative practice.

They're not.

A prompt is a moment. A creative practice is a loop. It has memory, constraints, revisions, and-most importantly-taste.

The interesting shift in the last year isn't that models got "more creative." It's that the best creative outcomes are coming from people who stopped trying to say the perfect thing once and started building systems that let intent evolve without losing the plot. Research is starting to describe this gap explicitly: the mismatch between a creator's high-level intent and what a one-shot generator can reliably execute (the "Intent-Execution Gap") [2]. And HCI work like ToMigo shows why this hurts so much in design: at the start, your intent is under-specified on purpose, and you discover what you mean by iterating [1].

So let's talk about GenAI & creative practices like adults: as workflows, representations, and feedback loops-not incantations.

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Creative intent is not a string; it's a structure

If you've ever tried to generate a "calm, modern brand identity" and gotten something that looks like a startup pitch deck from 2017, you've already learned the core truth: "intent" is multi-dimensional. It's purpose, mood, style, content, and composition-and those pieces constrain each other.

ToMigo's big idea is to stop pretending a short prompt can carry all that. Instead, it represents intent as a design concept graph: nodes for things like purpose, mood, art style, motifs, typography; edges that explain how choices support each other ("bright saturated palette supports playful mood," etc.) [1]. The point isn't graphs for graphs' sake. The point is that this becomes a shared "boundary object" you can inspect and edit as the work evolves, instead of re-rolling images and hoping you converge [1].

Here's what I noticed when I started thinking this way: the hardest part of "prompting for creativity" is not describing what you want. It's catching what the model assumed you wanted.

A structured representation forces assumptions to surface. And surfaced assumptions can be negotiated.

That's the move from "prompting" to "art direction."

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Orchestration beats one-shot generation (and it's not just for code)

The Vibe AIGC paper is basically a manifesto for the same idea at a system level: one giant model doing one giant generation is hitting a usability ceiling for real creative work, because the work requires long-horizon consistency, verification, and iterative decomposition [2].

Their proposed shift is: the user becomes a "Commander" who provides a vibe (a high-level intent state), and a Meta-Planner breaks it into steps and tools-storyboarding, character consistency, editing passes, and so on-rather than gambling on a single pass [2].

You don't need to buy the whole "new paradigm" pitch to steal the practical lesson: creative practice is a pipeline, not a prompt. And pipelines need two things prompts don't provide by default: decomposition and checks.

This also connects to a more "engineering-ish" framework from Generative Ontology: using schemas, constraints, and validation to keep generated artifacts structurally coherent (in their case, game designs) [3]. Their argument is one I love because it's blunt: LLMs hallucinate structure, not just facts. You can get fluent output that collapses when you try to use it [3].

If your creative output needs to be usable-a design system, a narrative bible, a campaign with consistent voice-then you need something that plays the role of a compiler: constraints, validations, and explicit handoffs [3]. Otherwise you're shipping vibes with missing parts.

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Human direction is the secret ingredient (and research finally measured it)

There's a tendency in some circles to say, "Just let agents run." But an experimental study on collaborative "vibe coding" found something that maps cleanly onto creative work in general: when AI systems provide the high-level guidance across iterations, performance can collapse; humans are uniquely good at giving effective directional instructions over time [4]. The best hybrid setup in their experiments kept humans in charge of direction while delegating evaluation/selection to AI [4].

Translate that into creative practice: you can offload exploration, variations, even critique. But you shouldn't offload taste and direction. That's the job.

The catch is that direction has to be operationalized. "Make it better" is not direction. "Keep the layout, but shift mood from playful to ominous while preserving legibility and the primary motif" is direction.

Which brings us back to structure.

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What this means for prompting: build an intent loop, not a prompt

When you treat GenAI as part of a creative practice, you start writing prompts that behave like process. They produce artifacts you can carry forward: an intent spec, a style state, constraints, and evaluation criteria.

Below are three prompts I actually recommend using as a baseline in creative workflows. They're intentionally "boring." That's the point. They make the work legible.

You are my creative director and scribe.

We are designing: [artifact type]
Audience: [who it's for]
Context: [where it lives: app, poster, pitch deck, short film, etc.]

Step 1 - Ask clarifying questions:
Ask 6 questions that surface hidden assumptions about purpose, mood, style, and constraints.
Do not ask about tools.

Step 2 - Produce an Intent Spec:
Return a structured spec with these sections:
- Purpose (1-2 sentences)
- Mood / emotional target (3-5 adjectives + 2 anti-goals)
- Style references (describe, don't name brands)
- Must-include elements
- Must-avoid elements
- Constraints (format, accessibility, legal/ethics, time)

Step 3 - Produce 3 concept directions:
Each direction should differ along at least two axes (mood + style, or style + composition).

That's the "ToMigo-ish" move without actually building a graph UI: you're forcing intent into explicit pieces the model can't quietly swap [1].

Next, an orchestration prompt-your cheap version of a Meta-Planner.

Act as a planner for a creative workflow.

Given this Intent Spec:
[paste spec]

Design a 5-iteration workflow. For each iteration provide:
- Goal of iteration (what changes / what stays fixed)
- Input artifacts needed
- What to generate (deliverable)
- How to evaluate (3 checks)
- What to log for the next iteration (state)

Keep it tool-agnostic. Assume we can generate text + images but need consistency over time.

This is directly aligned with the "orchestrate, verify, iterate" approach argued in Vibe AIGC [2].

Finally, a constraint/validation prompt inspired by Generative Ontology's emphasis on structural validity [3]:

You are a strict validator.

Given:
1) The Intent Spec
2) The Draft Output

Find:
- 5 alignment failures (where output contradicts intent)
- 5 missing structural elements (things required for usability)
- 3 places where the output is fluent but underspecified

Then propose a minimal patch plan:
Only list changes that preserve what already works.

This keeps you from doing the classic "rewrite everything" loop that nukes good accidents.

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Practical example: "prompts aren't assets; workflows are"

A Reddit post put it bluntly: hoarding prompts for AI art didn't scale; building a repeatable system (they used n8n plus parameter stacks) did [5]. I'm cautious citing community anecdotes as truth, but as a symptom it's dead on: people are independently reinventing orchestration because one-shot prompting doesn't produce consistent, client-grade output.

What the research adds is the "why." One-shot systems struggle with intent alignment and long-horizon consistency [2]. Structured intent representations increase control and support iteration [1]. And humans are still better at steering across iterations than AI systems left to self-direct [4].

So if you want GenAI to be part of your creative practice-not just a toy-optimize for repeatability and steering, not clever phrasing.

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Closing thought

Here's the experiment I'd run this week: stop trying to write "the best prompt" for 30 minutes. Instead, write an intent spec you'd be proud to hand to a human collaborator, then make the model argue with it, validate against it, and iterate with it.

You'll feel the difference immediately.

You're no longer prompting for outputs.

You're designing a practice.

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References

Documentation & Research

1. ToMigo: Interpretable Design Concept Graphs for Aligning Generative AI with Creative Intent - arXiv - http://arxiv.org/abs/2602.05825v1
2. Vibe AIGC: A New Paradigm for Content Generation via Agentic Orchestration - arXiv - https://arxiv.org/abs/2602.04575
3. Generative Ontology: When Structured Knowledge Learns to Create - arXiv - https://arxiv.org/abs/2602.05636
4. Why Human Guidance Matters in Collaborative Vibe Coding - arXiv - https://arxiv.org/abs/2602.10473

Community Examples

5. Stop hoarding prompts. Start building "Architectures". (My move from Midjourney to n8n workflows) - r/ChatGPTPromptGenius - https://www.reddit.com/r/ChatGPTPromptGenius/comments/1qhzx9b/stop_hoarding_prompts_start_building/