AI PROGRAMMING GUIDE
AI Pair Programming: The Complete Guide
Master AI-assisted programming with Copilot, ChatGPT, Claude, and other tools. Learn context management, prompt engineering, and how to avoid AI coding hallucinations.
The gap between "can" and "cannot" is context. The more relevant context you provide, the better the AI performs.
The Reality of AI Coding Tools
AI Can Do
- Generate code from descriptions
- Explain existing code
- Suggest refactors
- Find bugs in snippets
- Write tests
- Answer technical questions
AI Cannot (Without Help)
- Understand your full codebase structure
- Know what calls what across files
- See the impact of changes
- Understand architectural patterns
- Know your team's conventions
Context Is Everything
AI generates based on what it sees. If it only sees one file, it generates code for one file—potentially breaking relationships with everything else.
Local Context
The file you're working on. AI tools usually have this automatically.
Relationship Context
What calls this code? What does it call? Often missing—and critical.
Pattern Context
How does your codebase handle similar situations? Conventions matter.
Domain Context
What does the business do? Domain knowledge shapes correct solutions.
How to Provide Better Context
Include Related Files
When asking about code, include files that interact with it. The interface, the callers, the utilities it depends on.
Poor:
"Refactor this function" (just the function)
Better:
"Refactor this function. Here are the 5 places that call it..."
State the Constraints
Tell the AI what it can't change. What signatures must stay stable. What patterns must be followed.
"This function's signature can't change—it's called from 23 places."
Explain the Why
Don't just ask for code. Explain why you need it. Purpose shapes better solutions.
Poor:
"Add error handling here"
Better:
"Add error handling here. This is called during checkout, so errors should be logged but not crash the process."
Show Examples
If you want code that matches your patterns, show examples. "Make it like this other function" is powerful context.
Code Intelligence + AI
This is where LOOM transforms AI-assisted development. Query LOOM for callers, dependencies, and context. Include that information in your AI prompt.
AI now knows the relationships. Suggestions become safe. Refactors preserve compatibility. The gap closes.
LOOM provides what AI lacks. AI provides what you need. Together: effective AI-assisted development.
Common Mistakes to Avoid
Trusting Without Verification
AI-generated code can be wrong, outdated, or subtly broken. Always review, test, and verify.
Ignoring Side Effects
AI suggests a change. It works locally. But what about the 30 other places that depend on that code?
Copy-Paste Without Understanding
If you don't understand what AI generated, don't use it. You'll need to maintain it later.
Assuming Complete Knowledge
AI doesn't know your codebase unless you tell it. Fill the gaps explicitly.
Using AI for Everything
Some tasks are faster manually. Judgment matters. AI is a tool, not a replacement for thinking.
Skipping Impact Analysis
Before accepting AI suggestions that modify existing code, check what else depends on it.
Best Practices Summary
Before Asking AI
- Understand what you're accomplishing
- Gather relationship context
- Identify constraints and patterns
- Prepare examples from your codebase
While Prompting
- Be specific about what you want
- Include relevant context
- State constraints explicitly
- Ask for explanations, not just code
After Receiving Output
- Read and understand every line
- Check against existing patterns
- Verify it doesn't break dependents
- Test thoroughly
Give Your AI the Context It Needs
LOOM provides the relationship context that makes AI coding tools actually work. Complete intelligence for complete solutions.
Free tier available. No credit card required.
Go Deeper: Our AI Methodology
These white papers detail the frameworks and methodologies behind effective AI-assisted development.