Providing Context
Context is the background information that helps AI understand your situation. Without context, you get generic answers. With context, you get relevant, tailored responses.
Why Context Matters
The AI doesn't know:
- What product?
- What market?
- What's your cost structure?
- Who are competitors?
Context Categories
1. Situational Context
Where are you in the process?
2. Background Context
What led to this point?
3. Constraint Context
What limitations exist?
4. Goal Context
What are you trying to achieve?
Providing Effective Context
This context enables specific, actionable advice.
Exercise: Add Relevant Context
The RICE Framework for Context
Relevant - Does this information affect the answer? Important - Is it critical context or nice-to-have? Current - Is this information still accurate? Essential - Would the answer be wrong without it?
Context Formatting
Bullet Points (Most Common)
Narrative Style
Labeled Sections
Exercise: Format Context Effectively
How Much Context?
Too Little
Missing critical information that changes the answer.
Just Right
Everything relevant, nothing unnecessary.
Too Much
Information overload that dilutes focus.
Rule of thumb: If removing a piece of context wouldn't change the answer, remove it.
Context for Different Tasks
Problem Solving
Include: What you've already tried, error messages, environment details.
Creative Tasks
Include: Brand voice, target audience, examples you like/dislike.
Analysis Tasks
Include: Data sources, time period, success metrics.
Decision Making
Include: Options considered, constraints, stakeholders.
Practice: Context Audit
What context is missing? Think about:
- What type of website?
- How much did traffic drop?
- What changed last month?
- What traffic sources?
- What has been tried already?
Context transforms vague questions into specific, actionable conversations.