Saw this in r/PromptEngineering: a fill-in-the-blank artifact creation template that forces you to spec out a request before the AI generates anything. Clean idea, minimal setup.
Most AI outputs are inconsistent not because the model is bad, but because the prompt left too much room for interpretation. The model fills gaps with confident guesses. Sometimes those guesses land. Usually they don’t, and you end up iterating five times to get what you could have specified upfront in two minutes.
How it works
Six sections, each closing a different failure gap:
- Mission: one sentence, what to create and what it must do. The tighter this is, the less the AI has to guess. “Write a product description” is vague. “Write a 150-word product description for a B2B SaaS tool, focused on time savings for operations teams” is a mission.
- Win Criteria: checkboxes that define success before output starts. Think of these as your acceptance tests. If the AI cannot check every box, the output is not done. This is where you lock in format, length, tone, and structure requirements so they are not negotiable later.
- 📋 Required Inputs: the AI cannot generate anything until every input is marked COMPLETE. This is the gate that most prompts skip entirely. Without it, the model will invent plausible-sounding details, company names, statistics, whatever it needs to complete the task. With it, it waits. That single behavioral change eliminates a whole category of hallucination.
- Instructions: numbered steps the model follows in order. Sequencing matters here. If you need research before writing, or a brief before a draft, the numbered list enforces that order. The model does not skip steps when they are explicit.
- Negative Prompt: explicit rules for what NOT to do (no roleplay, no invented data, no output before inputs are ready). AI models are trained to be helpful, which means they default to producing something even when they should not. The negative prompt is your permission to say “stop and wait” without the model interpreting that as a failure state.
- Verification: the AI confirms at the end that all criteria were met and no rules were broken. This is not just a summary. It is a forcing function. When the model knows it has to audit its own output against your criteria, it tends to catch its own gaps before you do. You are building a self-check into the workflow itself.
The Required Inputs gate is the real win. Most prompts fail because the AI fills gaps with confident assumptions. This template makes it wait instead.
Use Cases
- SOP documents where missing details produce generic garbage. Without the gate, you get a polished-looking SOP that describes a fictional version of your process. With it, you feed in the actual steps and the model structures them correctly.
- Code templates where context gaps break the output. Tell the model what stack, what the function should accept, what it should return, and what edge cases to handle before it writes a single line. The code comes out closer to production-ready.
- Repeatable deliverables like proposals, audits, or reports. Once you have built the template for a client proposal, you run it every time. Swap the inputs, keep the structure. Consistent output without rebuilding the prompt from scratch.
- Any task where “close enough” output creates more rework than starting over. If you have ever spent 45 minutes editing an AI output that would have taken 20 minutes to write yourself, this is the fix.
🛠️ Prompt of the Day
Copy this shell. Fill in your Mission, Win Criteria, and Required Inputs. Leave the rest as-is unless your task needs specific tweaks.
A few notes on filling it in well: keep the Mission to one sentence and resist the urge to over-explain there. Save the detail for Instructions. For Win Criteria, think about the last time an AI output frustrated you and work backwards. What was missing? Put that in the checklist. For Required Inputs, list every piece of context the model would otherwise guess at. Names, numbers, formats, constraints, audiences. If it is not in the list, assume the model will invent it.
## Mission
[State exactly what to create and what it must accomplish.]
## Win Criteria
- [ ] [Criterion 1]
- [ ] Output is in Markdown inside a single code block
- [ ] Includes a verification section
- [ ] No roleplay or "you are" language
## Required Inputs
Do not generate until all inputs are provided.
- [ ] [Input 1]: [Description]
Status: [INCOMPLETE / COMPLETE]
## Instructions
1. Wait until all required inputs are present.
2. Follow the mission exactly.
3. Satisfy every win criterion.
4. Keep output practical and reusable.
5. Include verification at the end.
## Negative Prompt
- No "You are" framing
- No invented inputs
- No output before inputs are complete
- No skipping verification
## Output Structure
1. Title
2. Main Artifact
3. VerificationTakes about five minutes to fill in. Cuts the back-and-forth with the AI by a lot. The five minutes you spend upfront saves you from three rounds of “that’s not quite right, try again” that each cost you another ten.
If you are building repeatable AI workflows, this kind of upfront structure pays off fast. Save it, adapt it, run it. Build a small library of filled-in versions for your most common tasks so you are not starting from blank every time. The template becomes the asset, not just the output.
Was board so I made this Artifact Control Templet. From ya boy, let me know if it’s good, bad or ugly.
by u/og_hays in PromptEngineering