Claude Code in Production: From Basics to Building Real Systems

The Foundation: Think Before You Type

Most people jump straight to asking Claude for code. They describe a problem and expect a solution. This almost always produces worse results than planning first.

I learned this through painful repetition. When I use Plan Mode, the output is dramatically better. Not a little better. Significantly better. Like, not even comparable.

Here’s why: asking Claude to jump straight to implementation is like asking a junior engineer to design and build a feature with no requirements discussion. They’ll start coding without understanding constraints, architecture, or what actually matters. They’ll build something that technically works but doesn’t fit your system.

Plan Mode (Shift+Tab twice) forces Claude into architect mode before touching any code. It can read your codebase, analyze structure, think through dependencies, and come back with a comprehensive plan. And crucially, you review the plan before execution. You catch architectural mismatch before code gets written.

The workflow is simple:

Enter Plan Mode
Describe what you need
Let Claude research and propose a plan
Review and refine (often multiple iterations)
Exit Plan Mode and execute

This adds maybe 10 minutes to a task. It saves hours of debugging.

CLAUDE.md: Your Leverage Point

Here’s a secret: you can teach Claude about your project in a way that makes every subsequent interaction better.

Create a file called CLAUDE.md in your project root (and optionally in subdirectories for specific context). Every time you start a Claude Code session, it reads this file. Everything in it shapes how Claude approaches your codebase.

Most people either ignore this completely or stuff it with walls of documentation that make Claude worse instead of better. There’s a real threshold where too much information means Claude starts ignoring things randomly.

Here’s what actually works:

Keep it short. Claude can reliably follow around 150-200 instructions at a time. Your system prompt already uses about 50 of those. Every instruction competes for attention. If CLAUDE.md is a novel, parts of it will get ignored. You won’t know which parts.

Make it specific to your project. Don’t explain what a components folder is. Claude knows what components are. Tell it the weird stuff. The bash commands that matter. Your deployment quirks. The way you handle errors. Everything that’s specific to this codebase.

Tell it why, not just what. Compare these:

“Use TypeScript strict mode”
“Use TypeScript strict mode because we’ve had production bugs from implicit any types”

The second version is better. The why gives Claude context for judgment calls you didn’t anticipate. Claude will apply that reasoning to situations you didn’t explicitly cover.

Update it constantly. Every time you find yourself correcting Claude on the same thing twice, that’s a signal it should go in CLAUDE.md. Use the # prefix in your prompt and Claude will add instructions automatically. Over time it becomes a living document of how your codebase actually works.

How it works in practice: When you’re in a Claude Code conversation and you notice Claude keeps making the same mistake (or forgetting some project-specific rule), you do not have to:

Open CLAUDE.md yourself
Write a new section
Save the file
Restart or hope it picks it up

Instead you simply write something like: # Always use TypeScript strict mode because we've had production bugs from implicit any types

Claude (the agent) sees the line starting with # + space, understands this as “add this to my persistent memory”, and automatically appends that content to the project’s CLAUDE.md file (usually at the end or in a logical place).

Bad CLAUDE.md looks like documentation written for a new hire. Good CLAUDE.md looks like notes you’d leave yourself if you knew you’d have amnesia tomorrow.

The Hard Truth About Context

Opus has a 200,000 token context window. Here’s what most people don’t realize: quality degrades way before you hit 100%. Keyword: context rot.

Around 20-40% context usage is where output quality starts to chip away. It’s not dramatic at first. But if you notice Claude Code compacting and then still giving terrible output? The model was already degraded before compaction happened. Compaction doesn’t fix degraded reasoning - it just removes noise from already-degraded context.

This is the reality: every message you send, every file Claude reads, every piece of code it generates, it all accumulates. Once quality starts dropping, more context makes it worse, not better.

What actually helps:

Scope your conversations. One conversation per feature or task. Don’t use the same conversation to build auth and then refactor the database layer. The contexts bleed together and Claude gets confused.

Use external memory. For complex projects, have Claude write plans and progress to files (plan.md, SCRATCHPAD.md). These persist across sessions. When you come back tomorrow, Claude reads the file instead of starting from zero. The key is keeping these at the top of your hierarchy so they stay in the file search.

The copy-paste reset. When context gets bloated, copy everything important from the terminal, run /compact to get a summary, then /clear entirely, and paste back only what matters. Fresh context with critical information preserved. Way better than letting Claude struggle through degraded context.

Know when to clear. If a conversation goes off the rails or accumulates irrelevant context, just /clear and start fresh. It feels counterintuitive - you’re throwing away the conversation - but it’s almost always better than pushing through confusion. Claude still has your CLAUDE.md, so you’re not losing project context.

The mental model that works: Claude is stateless. Every conversation starts from nothing except what you explicitly give it. Plan accordingly.

Prompting is Everything

People spend weeks learning frameworks. They spend zero time learning how to communicate with the thing actually generating their code.

Being clear gets you better results than being vague.

Be specific about what you want. “Build an auth system” gives Claude creative freedom it will use poorly. “Build email/password authentication using the existing User model, store sessions in Redis with 24-hour expiry, and protect all routes under /api/protected” gives it a clear target.

Tell it what NOT to do. Claude has tendencies. It likes to over-engineer - extra files, unnecessary abstractions, flexibility you didn’t ask for. If you want something minimal, say “Keep this simple. Don’t add abstractions I didn’t ask for. One file if possible.”

This matters because Claude will make mistakes. That’s not a flaw in the tool - it’s the reality of working with AI. You need to be able to recognize these mistakes and course-correct. Cross-reference everything Claude produces because technical debt compounds fast.

Give context about why. “We need this fast because it runs on every request” changes Claude’s approach. “This is a prototype we’ll throw away” changes what trade-offs make sense. Claude can’t read your mind about constraints you haven’t mentioned.

When Claude Gets Stuck

Sometimes Claude just loops. It tries the same thing, fails, tries the same thing again, fails, keeps going. Or it confidently builds something that’s completely wrong and you spend twenty minutes trying to explain why.

The instinct is to keep pushing. More instructions. More corrections. More context. That’s the wrong move.

The better approach is to change strategy entirely:

Clear the conversation. The accumulated context might be confusing Claude. /clear gives a fresh start.

Simplify the task. If Claude is struggling with something complex, break it into smaller pieces. Get each piece working before combining. But if Claude is struggling with complexity, your plan mode was probably insufficient. Go back to planning.

Show instead of tell. If Claude keeps misunderstanding what you want, write a minimal example yourself. “Here’s what the output should look like. Now apply this pattern to the rest.” Claude is extremely good at understanding what success metrics look like and following them.

Reframe the problem. Sometimes the way you described the problem doesn’t map well to how Claude thinks. Reframing - “implement this as a state machine” vs “handle these transitions” - can unlock progress.

The meta-skill is recognizing when you’re in a loop early. If you’ve explained the same thing three times and Claude still isn’t getting it, more explaining won’t help. Something needs to change.

Building Systems, Not One-Shots

The people getting the most value from Claude Code aren’t using it for one-off tasks. They’re building systems where Claude is a component.

Claude Code has a -p flag for headless mode. It runs your prompt and outputs the result without entering the interactive interface. This means you can script it. Pipe output to other tools. Chain it with bash commands. Integrate it into automated workflows.

Enterprises are using this for automatic PR reviews, support ticket responses, documentation updates. All of it logged, auditable, and improving over time based on what works.

The flywheel: Claude makes a mistake, you review the logs, you improve CLAUDE.md or your tooling, Claude gets better next time. This compounds. After months of iteration, systems built this way are meaningfully better than they were at launch - same models, just better configured.

If you’re only using Claude Code interactively, you’re leaving value on the table. Think about where in your workflow Claude could run without you watching.

Practical Patterns That Work

A few specific things I’ve learned make a big difference:

Use git constantly. Version control becomes even more critical when you’re moving fast with AI. You can’t just reverse the last two messages worth of edits - once Claude makes changes, they’re made. Git is your safety net.

External documentation. Have Claude write thoughts, task specifications, designs, to intermediate markdown files. These serve as context later and scratchpad for now. Using these documents in later sessions regains important context when your session grows long.

The thinking levels. Claude has different reasoning depths: “think” < “think hard” < “think harder” < “ultrathink”. Use them strategically. “think” for straightforward features. “think hard” for complex business logic. “think harder” for performance optimization. “ultrathink” for when you’re stuck. Don’t throw ultrathink at everything - you’ll pay in tokens and time.

Fast feedback loops. Provide verification mechanisms for Claude to achieve fast feedback. Write tests alongside features. Have Claude run them immediately. This prevents reward-hacking where Claude takes shortcuts to make it look like it succeeded without actually solving the problem.

Multiple instances in parallel. For larger projects, you can run Claude Code instances for different components simultaneously. Frontend + backend. Different services. This works better if you use git worktrees so each instance works on its own branch without conflicts.

The Workflow That Works

Here’s the actual process I use:

Plan Mode. Describe what I need. Let Claude research the codebase. Review the plan. Refine it.
Exit Plan Mode and execute. Now Claude actually changes files.
Test immediately. Write tests alongside features. Run them right away to catch issues.
Review output. Check what Claude produced. Cross-reference for mistakes.
Iterate. If something’s wrong, either show Claude an example or try a different approach.
Commit frequently. Don’t wait until the feature is done. Commit working states so you have a safety net.
External memory. If the task is complex, have Claude document progress in a file you can reference in the next session.
Scope conversations. When a feature is done, start a fresh conversation for the next one.

This sounds like it takes time. It doesn’t. It saves time by preventing the mess that comes from not thinking things through.

What to Actually Expect

Claude Code is useful. Genuinely useful. But it’s not magic.

It’s extremely good at:

Boilerplate and repetitive tasks
Reading and understanding code (it can scan a large codebase in seconds)
Refactoring when you’ve already decided on an approach
Implementing features where the architecture is clear
Debugging when you give it good context

It’s less good at:

Making architectural decisions without guidance
Understanding your system without explicit context
Handling ambiguous requirements
Making judgment calls about trade-offs

The reality is that Claude Code works best when you’re doing the thinking and Claude does the execution. You decide the architecture, Claude builds it. You decide the trade-offs, Claude implements them.

That’s not a limitation. That’s actually how you get the best results.

The Mindset Shift

If you’re using Claude Code and getting bad results, the problem is almost never the model. Models like Opus are genuinely capable. The problem is almost always on the human side: how you structure your thinking, how clearly you communicate, how well you’ve set up your project context.

This is the hard truth: if you’re getting mediocre output, you’re giving mediocre input.

The shift from “vague prompt, hope for the best” to “clear thinking, detailed context, clear communication” is huge. And it’s entirely in your control.