5-Minute Overview

The essential concepts for effective AI-assisted coding. Read this first, then go deeper where you need.

The governing rule that determines everything:

"If you don't control context, you don't control outcomes."

1

Context Is Everything

What you give Claude determines what you get back. Every file you reference, every instruction in CLAUDE.md, every conversation turn: all of it shapes what Claude produces. A brilliant prompt in polluted context produces garbage. A mediocre prompt in well-curated context often produces something usable.

๐Ÿ’ก Start each session by explicitly telling Claude what you're working on and what you want to achieve. Point it at the relevant files: "Read src/auth/ and understand how authentication currently works."
2

Monitor Your Context Budget

Claude has a limited context window. When it fills up, Claude starts repeating itself, ignoring instructions, or claiming to have done things it didn't. Enable /statusline to see your context usage, and start fresh sessions around 60% capacity. Effective users reset context proactively instead of pushing through.

๐Ÿ’ก Clear context between unrelated tasks with /clear. Check what's consuming space with /context. Auto-compaction kicks in around 80%, but starting a fresh session is usually better.
/statusline /context /clear
3

Verify, Don't Trust

AI-generated code can look correct while being subtly wrong. The developers who get best results treat Claude's output as a draft, not a final product. Build feedback loops: run tests, check output visually, use a separate Claude instance to review. This verification step will 2-3x the quality of your results.

๐Ÿ’ก Use the TDD loop: have Claude write tests first, confirm they fail, then implement code to make them pass. The tests define "correct" before implementation starts.
4

Scope Control

Small, focused tasks succeed. Large, vague tasks fail. Claude excels when it has a clear target. If you've been going back and forth on a single task and context is climbing past 40-50%, something is wrong. Either the task needs decomposition, or you need to reset and try a different approach.

๐Ÿ’ก Good scope: "Add a logout button to the header that calls /api/logout"
Bad scope: "Implement user authentication"
5

Structure Needs Bookends

LLMs don't maintain architecture. They generate code. Without guardrails, complexity creeps fast. For anything beyond toy projects, you need bookends: architecture on one side (blueprints, design docs, constraints that guide generation) and tests on the other (suites with meaningful coverage as a safety net).

๐Ÿ’ก Create a CLAUDE.md file in your project root with build commands, key file locations, and non-obvious constraints. Keep it lean: include only essential info, avoid redundancy, and maintain a high signal-to-noise ratio. Bloated files make Claude worse, not better.

The Bottom Line

Claude Code doesn't reward clever prompting. It rewards system design. The developers who thrive aren't the ones who write the best prompts. They're the ones who design systems where prompts don't need to be perfect, because the structure does most of the work.

Try This

Run this now to see your current context state:

โฏ /context

Where to Go Next