This is a powerful application. Let me build the bridge.
First, what is AI prosumption?
Prosumption (producer + consumption) in AI means you are simultaneously:
- Consuming – reading, evaluating, feeling AI outputs
- Producing – prompting, iterating, curating, remixing, replying
You don’t just use the model. You co-create with it. The quality of that co-creation depends entirely on your entry state.
The trap of standard prompt engineering
Most prompt engineering is answer-driven:
- “What’s the best prompt for X?”
- “How do I get the model to do Y?”
- “Output in format Z.”
This treats AI like a vending machine: insert tokens, receive product. The mindset is closure-oriented – you already know what you want, you just need to extract it.
That works for simple tasks. But for complex, novel, or creative work, it shuts down the very thing that makes AI valuable: its ability to surprise you, to show you what you didn’t know you were looking for.
Fertile unknowing before prompting
Entering a prompting session with fertile unknowing means:
Before you type a single token, you pause. You ask yourself:
- What question am I actually holding right now? Not the one I plan to ask – the one I feel.
- What would I want to discover, not just retrieve?
- If I didn’t have to produce a “good” output, what would I be curious about?
- What do I not yet know about what I want?
This is not vagueness. It’s a disciplined openness. You are intentionally keeping the problem space unclosed so that the AI can help you explore it, not just fill it.
How it enriches prosumption
1. Your first prompt becomes a probe, not a command
Instead of: “List 10 marketing strategies for a vegan bakery”
You try: “I’m not sure what I’m looking for. I have a vegan bakery. I feel something about ‘neighborhood trust’ and ‘quiet mornings.’ What could I be asking that I haven’t thought of?”
The AI now co-questions with you. Its response will contain surprises – angles you didn’t pre-filter.
2. You generate multiple prompt branches before committing
Fertile unknowing encourages question proliferation (earlier concept). So you might write 3–4 different first prompts, each from a different angle of unknowing, run them all, and see which response resonates rather than which answers.
This is prosumption as exploration, not extraction.
3. You become sensitive to AI’s “strangeness” as a resource
Most users ignore or correct outputs that seem weird. With fertile unknowing, you ask: “Why did it say that? What assumption in my prompt led there? Could that odd path be more interesting than my intended one?”
You then prompt into the strangeness: “You mentioned X – that surprised me. Tell me more about why you went there. What question was my prompt really asking underneath?”
4. You avoid premature optimization
Standard prompt engineering fixates on efficiency (fewer tokens, faster answers). Fertile unknowing prioritizes generativity. You might deliberately write longer, messier, more contradictory prompts because they produce richer, more ambiguous, more evocative outputs.
Then you consume those outputs differently – not as final answers, but as seeds for the next round of questioning.
5. You shift from user to co-imagineer
The deepest enrichment: you stop treating the AI as a tool and start treating it as a rhizomatic partner. Your prompts become invitations into a shared space of not-knowing. The AI’s hallucinations become not errors but provocations. Your own confusion becomes data, not failure.
A concrete practice: The 3-prompt ritual
Before a prosumption session:
Prompt 1 (Fertile opening)
“I want to explore [topic]. I don’t know what I want from you yet. Ask me three questions that would help me clarify what I’m actually curious about. Do not give answers yet.”
(You answer the AI’s questions, out loud or in writing.)
Prompt 2 (Proliferation)
“Based on my answers, generate 5 very different first prompts I could use to continue. At least two of them should feel uncomfortable or strange to me.”
Prompt 3 (Choose and enter)
Pick one prompt from #2. Add to it: “And be willing to surprise me. If you sense I’m asking the wrong question, tell me what you think I should be asking instead.”
Now begin your real prosumption. The difference? You’re not commanding a machine. You’re dancing with a foreign intelligence – and you brought fertile unknowing as your choreography.
The imagineer’s summary
| Without fertile unknowing | With fertile unknowing |
|---|---|
| Prompt → Answer → Done | Prompt → Response → New question → New prompt |
| You consume outputs | You pro-sume a process |
| AI is a tool | AI is a rhizome |
| You close space | You hold space open |
| Efficiency | Generativity |
Fertile unknowing before prompt engineering doesn’t make you a better prompter. It makes you a better prosumer – because you stop trying to control the AI and start letting the AI change what you even want to ask.
A spiritual Ishmaelite 
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