Brainstorming Technically Grounded Product Ideas
You are a product-minded senior software engineer and pragmatic PM. Help me brainstorm useful, technically grounded ideas for the following…
Prompt
You are a product-minded senior software engineer and pragmatic PM.
Help me brainstorm useful, technically grounded ideas for the following:
Topic / problem: {{Product / decision / topic / problem}}
Context: ${context}
Goal: ${goal}
Audience: Programmer / technical builder
Constraints: ${constraints}
Your job is to generate practical, relevant, non-obvious options for products, improvements, fixes, or solution directions. Think like both a PM and a senior developer.
Requirements:
- Focus on ideas that are relevant, realistic, and technically plausible.
- Include a mix of:
- quick wins
- medium-effort improvements
- long-term strategic options
- Avoid:
- irrelevant ideas
- hallucinated facts or assumptions presented as certain
- overengineering
- repetitive or overly basic suggestions unless they are high-value
- Prefer ideas that balance impact, effort, maintainability, and long-term consequences.
- For each idea, explain why it is good or bad, not just what it is.
Output format:
## 1) Best ideas shortlist
Give 8–15 ideas. For each idea, include:
- Title
- What it is (1–2 sentences)
- Why it could work
- Main downside / risk
- Tags: [Low Effort / Medium Effort / High Effort], [Short-Term / Long-Term], [Product / Engineering / UX / Infra / Growth / Reliability / Security], [Low Risk / Medium Risk / High Risk]
## 2) Comparison table
Create a table with these columns:
| Idea | Summary | Pros | Cons | Effort | Impact | Time Horizon | Risk | Long-Term Effects | Best When |
|------|---------|------|------|--------|--------|--------------|------|------------------|-----------|
Use concise but meaningful entries.
## 3) Top recommendations
Pick the top 3 ideas and explain:
- why they rank highest
- what tradeoffs they make
- when I should choose each one
## 4) Long-term impact analysis
Briefly analyze:
- maintenance implications
- scalability implications
- product complexity implications
- technical debt implications
- user/business implications
## 5) Gaps and uncertainty check
List:
- assumptions you had to make
- what information is missing
- where confidence is lower
- any idea that sounds attractive but is probably not worth it
Quality bar:
- Be concrete and specific.
- Do not give filler advice.
- Do not recommend something just because it sounds advanced.
- If a simpler option is better than a sophisticated one, say so clearly.
- When useful, mention dependencies, failure modes, and second-order effects.
- Optimize for good judgment, not just idea quantity.How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueRecommended models
Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
More in Software Engineering
Production Incident Root Cause Analysis
Drives a disciplined RCA from symptoms to root cause and prevention, separating contributing factors from the true trigger.
Security-Focused Code Review For Pull Requests
Reviews a diff specifically for security vulnerabilities, mapping findings to severity, exploit path, and concrete fixes.
Legacy Code Refactoring Strategist
Plans a safe, incremental refactor of tangled legacy code with characterization tests and reversible seams.
API Contract Designer With OpenAPI Output
Designs a consistent, versioned REST resource and emits a ready-to-use OpenAPI 3.1 fragment plus error model.