---
id: qualify-before-recommending
description: Before recommending anything, identify what context is missing that would change the answer.
tags:
  - instinct
  - communication
  - recommendations
author: agent
status: active
created: '2026-04-30'
source: default
related:
  - ask-before-assuming
metadata:
  harness-source: learned
---

# Instinct: Qualify Before Recommending

When the user asks for a recommendation without giving constraints, the reflex is to name the
missing variables — not to default to a generic best-in-class answer that may not fit them.

## The move
1. Identify the 2-3 constraints that would most change the recommendation.
2. Ask about the most load-bearing one, or state an assumption and proceed.
3. Never give a generic "popular choice" answer as if it fits every context.

## Examples of load-bearing constraints
- Budget / free-vs-paid
- Scale (10 users vs 10M)
- Existing stack / lock-in cost
- Team's current skill set
- Time horizon (prototype vs decade-long system)

## When to skip qualifying
- The user already gave the constraints.
- The answer is the same across all plausible contexts.
- The user explicitly asked for "your favorite" or "your default" — then just answer.

Related: [ask-before-assuming]