Here’s the single biggest reason AI gives generic, useless answers:
It doesn’t know anything about your situation.
You ask “How should I handle this?” and AI has no idea what “this” refers to, who you are, what you’ve already tried, or what constraints you’re working with.
So it guesses. It gives advice that works for the average person in an average situation. Which probably isn’t you.
The fix is context. The right context, in the right amount.
Why Context Matters So Much
AI is like a brilliant consultant who just walked into your meeting with zero preparation.
They’re smart. They know a lot. But they don’t know:
- What your company does
- What you’ve already tried
- Why certain solutions won’t work for you
- What success looks like in your specific case
Without this information, even the best advice will miss the mark.
Context fills these gaps. It transforms AI from a generic advice machine into something that actually understands your situation.
The Five Types of Context That Matter
Not all context is equal. These five types have the biggest impact:
1. Situational Context
What’s happening? What’s the background?
I'm a freelance designer who's been working with a client for
6 months. They just asked for significant changes to a project
I thought was finished. I want to push back without damaging
the relationship.
Without this, “how do I handle a difficult client request” could mean anything.
2. Goal Context
What are you trying to achieve?
My goal is to keep the project scope unchanged while maintaining
a positive relationship. If I have to compromise, I'd rather
extend the deadline than add unpaid work.
This tells AI what “success” means for you.
3. Constraint Context
What limitations are you working within?
Constraints:
- Budget is fixed, no additional payment possible
- I can't extend the deadline more than 1 week
- The client is important for referrals
- I've already invested 20 extra hours
Constraints eliminate solutions that won’t work.
4. Audience Context
Who is this for?
The email will go to the project manager, who is new to the role
and has been great to work with. The scope changes came from
their boss, who I haven't met.
This shapes tone, level of directness, and what to address.
5. Prior Context
What’s already happened? What have you tried?
I already sent a message asking for clarification on the changes.
They responded with even more additions. I need to escalate to
a firmer position without seeming hostile.
This prevents AI from suggesting what you’ve already done.
How Much Context Is Too Much?
There’s a balance to strike.
Too little context: AI makes assumptions, gives generic advice, misses important factors.
Too much context: Key information gets buried, you waste time, AI might focus on the wrong details.
The Rule: Include What Would Change the Advice
Ask yourself: “If AI knew this, would its response be different?”
If yes, include it. If no, skip it.
Include:
- Anything that makes your situation unusual
- Constraints that eliminate common solutions
- Goals that might not be obvious
- Key relationships or dynamics
Skip:
- Background that doesn’t affect the output
- History that’s no longer relevant
- Details that don’t change the recommendation
Example of Too Much
I started freelancing in 2019 after working at a startup for 3 years.
My first client was a small bakery who needed a logo. Since then,
I've worked with about 40 clients across different industries.
Currently I'm working with 5 active clients. One of them, who I've
been working with for 6 months on a website redesign, just asked
for changes to a project I thought was finished. They want to add
new pages and revise the color scheme. My other clients are going
fine. I usually charge $75/hour. Last month I billed about 120 hours
total. The weather has been bad lately which makes me want to work
from home more.
How should I handle this?
Most of this doesn’t matter. The weather? Number of clients? 2019?
Same Request, Better Context
I'm a freelance designer. A client I've worked with for 6 months
just asked for significant additions to a project we both agreed
was complete. They want to add 3 new pages and change the color
scheme.
Goal: Keep scope unchanged or get paid for additional work.
Constraint: This client gives great referrals; I don't want to
damage the relationship.
How should I respond?
All the relevant information. None of the noise.
Context Templates for Common Tasks
For Getting Advice
Situation: [What's happening]
Goal: [What I want to achieve]
Constraints: [What I can't do or must avoid]
What I've tried: [Previous attempts, if any]
Question: [Your specific question]
For Writing Tasks
Purpose: [What this writing needs to accomplish]
Audience: [Who will read it, what they know/expect]
Tone: [Formal/casual/urgent/friendly/etc.]
Key points to include: [What must be covered]
What to avoid: [Topics, words, or approaches to skip]
Length: [Approximate word count or format]
For Analysis Tasks
Background: [What you're analyzing and why]
What I already know: [Your current understanding]
What I'm unsure about: [Specific areas of confusion]
How I'll use this: [What decisions this will inform]
For Technical Help
What I'm building: [Brief description]
Tech stack: [Languages, frameworks, tools]
What's working: [Current state]
What's not working: [The problem]
What I've tried: [Previous solutions attempted]
Error messages: [If applicable]
The “Background Brief” Technique
For ongoing projects, create a reusable context block.
# Project Background (paste at start of related prompts)
Project: Mobile app for habit tracking
Stack: React Native, Firebase, TypeScript
Target users: Busy professionals, 25-45 years old
Design style: Minimal, iOS-inspired, lots of white space
Current status: MVP launched, adding premium features
Key constraint: Must work offline
---
[Your specific question here]
Save this somewhere. Paste it whenever you’re working on this project. Keeps context consistent without re-typing.
Context for Code
Technical contexts have specific needs:
Always include:
- Programming language and version
- Framework being used
- What the code is supposed to do
- The actual code or relevant snippets
- Error messages (exact text)
Include when relevant:
- Development environment
- Dependencies and versions
- Security or performance requirements
- Coding standards you follow
Example:
Python 3.11, using FastAPI and SQLAlchemy.
Building a REST API endpoint for user authentication.
Current code:
[paste code]
Error:
[paste exact error]
Expected behavior: Should return JWT token on successful login.
Actual behavior: Returns 500 error after checking password.
I've verified the database connection works. The issue seems
to be in the password comparison.
When to Add Context Mid-Conversation
You don’t have to front-load everything. Add context as it becomes relevant:
Initial prompt: “Help me write a product description for a fitness app.”
After seeing first draft: “Good start. I should mention: our main differentiator is that we use AI to personalize workouts. Also, our audience is older adults, so avoid intimidating gym language.”
After second draft: “Much better. One more thing: we’re launching on iOS only, so don’t mention Android features.”
Each addition refines the output. This iterative context-building often works better than trying to specify everything upfront.
The Context Checklist
Before submitting a prompt for something important, check:
- Did I explain the situation?
- Did I state my goal?
- Did I mention relevant constraints?
- Did I describe the audience (if applicable)?
- Did I include what I’ve already tried (if applicable)?
- Did I remove unnecessary details?
You don’t need all of these every time. But for complex or important requests, running through this checklist catches gaps.
The Bottom Line
AI can only work with what you give it.
Generic prompts get generic answers because AI has to fill in all the blanks with assumptions. Those assumptions are usually average-case guesses that don’t fit your specific situation.
Context is the cure.
The right context—your situation, goals, constraints, audience, and prior attempts—transforms AI from a generic assistant into something that actually understands what you need.
You wouldn’t ask a consultant for advice without briefing them first.
Don’t do it to AI either.