home / skills / coowoolf / insighthunt-skills / curiosity-loops

curiosity-loops skill

/user-research/curiosity-loops

This skill helps you gather contextual advice from diverse peers to navigate major decisions with clear questions and closed-loop outcomes.

npx playbooks add skill coowoolf/insighthunt-skills --skill curiosity-loops

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---
name: curiosity-loops
description: Use when facing a significant decision (career pivot, product direction, technical choice) and feeling stuck or indecisive, when seeking contextual advice rather than generic recommendations
---

# Curiosity Loops

## Overview

Curiosity Loops is a structured method for gathering **contextual advice** from a curated group of peers rather than relying on a single mentor or vague questions. It turns decision-making into a data-collection exercise.

**Core principle:** The best advice is contextual. Bad advice happens when advisors lack context about your specific situation.

## When to Use

- Facing a significant decision (career pivot, product direction, personal dilemma)
- Feeling indecisive or stuck
- Need diverse perspectives quickly
- Want to avoid "single point of failure" advice

## The Four-Step Process

```
┌─────────────────────────────────────────────────────────────────┐
│  1. FORMULATE     →  Ask specific, unbiased question            │
│                      (NOT "What should I do?")                  │
├─────────────────────────────────────────────────────────────────┤
│  2. CURATE        →  Mix Subject Matter Experts +               │
│                      People who know your context               │
├─────────────────────────────────────────────────────────────────┤
│  3. EXECUTE       →  Reduce cognitive load                      │
│                      (e.g., "Pick top 2 of 9")                  │
├─────────────────────────────────────────────────────────────────┤
│  4. CLOSE LOOP    →  Process data, share outcome with advisors  │
└─────────────────────────────────────────────────────────────────┘
```

## Quick Reference

| Element | Good Example | Bad Example |
|---------|--------------|-------------|
| Question | "Which 2 of these 9 topics resonate most?" | "What should I talk about?" |
| Audience | 10 friends (5 experts + 5 who know you) | 1 mentor |
| Format | Low friction (2 choices max) | Open-ended essay |
| Follow-up | Share what you decided and why | Ghost them |

## Common Mistakes

- **Vague questions** → Ask specific, structured questions
- **Single advisor** → Curate 8-12 people with diverse perspectives
- **No follow-up** → Always close the loop; thank advisors

## Real-World Example

Ada Chen Rekhi used this to select podcast interview topics: emailed 10-11 friends a list of 9 topics, asked them to pick their top 2, synthesized patterns, and closed the loop.

---

*Source: Ada Chen Rekhi (Notejoy, LinkedIn, SurveyMonkey) via Lenny's Podcast*

Overview

This skill guides you through Curiosity Loops: a structured approach to collect contextual advice from a curated group when you’re stuck on a significant decision. It turns decision-making into a short, low-friction data-collection process so you get diverse, relevant perspectives instead of generic answers. Use it to reduce bias, increase signal, and speed choices with real-world feedback.

How this skill works

You craft a specific, bounded question and assemble a curated audience of subject experts plus people who know your context. You present a low-effort task (e.g., pick top 2 of 9 options), collect responses, synthesize patterns, and then close the loop by sharing your decision and rationale with contributors. The method focuses on clear prompts, diverse participants (8–12), and simple response formats to minimize cognitive load and maximize actionable signal.

When to use it

  • Facing a major decision (career pivot, product direction, hiring, technical stack)
  • Feeling indecisive or overwhelmed by options
  • Needing fast, contextual input from multiple viewpoints
  • Avoiding dependence on a single mentor or advisor
  • Validating hypotheses before committing resources

Best practices

  • Ask specific, constrained questions (e.g., rank or pick top 2) rather than open-ended “what should I do?”
  • Curate 8–12 participants: mix domain experts and people who understand your context
  • Keep responses low-friction: binary choices, rankings, or short checkboxes
  • Synthesize patterns quantitatively and qualitatively—look for recurring themes, not outliers
  • Always close the loop: share your decision and how feedback influenced it, and thank contributors

Example use cases

  • Choosing which product features to prioritize among nine candidates
  • Deciding between staying at a job versus pursuing a new role
  • Selecting a podcast or content topic list by asking peers to pick top picks
  • Picking between technical implementations by asking engineers to choose preferred trade-offs
  • Narrowing a long list of target markets to the most promising two

FAQ

How many people should I include?

Aim for 8–12 contributors with a balance of experts and people who know your context; that mix reduces bias and adds practical relevance.

What format gets the best responses?

Low-friction formats like ranking top 2 of 9, yes/no choices, or a short checkbox list yield higher response rates and clearer patterns.