AI doesn't write bad code. You're just prompting it wrong.

People keep whining that AI generates garbage code. Every time I see these complaints, one thought hits me: you're not outsmarting billion-dollar labs or models with hundreds of billions of parameters. You just haven't figured out how to wield them yet.

Here's the thing. When you understand what you're building and can direct an AI agent like you'd guide a junior developer, everything clicks. Trash code appears? You'll spot it immediately because you actually know your craft. Then you tell Claude Code exactly how to fix it.

Two real problems exist when shipping production software:

• First, scaling your app with proper architecture. Second, locking down security. Think SQL injections, insecure direct object references, DDoS mitigation, rate limiting. The usual suspects.

Security is pretty straightforward. Ask Claude Code how to prevent each vulnerability type and you're mostly covered.

• Architecture though? That's where things get spicy. Let me show you how I design systems using Claude's ecosystem so your product doesn't implode minutes after going live.

Quick disclaimer: I'm no software architect. Learning as I go. But this workflow actually ships working products.

My six-step architecture process:

1. Start with clarity on what you're building. Chat app? Social feed? Media platform? Check if someone's already built something similar. Scour public GitHub repos. Borrow liberally from what already works.
2. Have Claude Code dissect your codebase. Request a thorough audit. Get documentation showing current state versus what you need. This step deserves serious time because it anchors everything else. Next, have Claude Code write a detailed prompt for Claude's deep research mode. This prompt becomes your architecture design assistant.
3. Ship that monster prompt to Claude's deep research. Load up Claude (desktop or web version) with your prompt plus all generated documentation. Deep research mode will hand you an architecture blueprint. Plus references to real projects on GitHub and technical blogs you can study.
4. Decompose everything into markdown files. Each component gets its own file explaining implementation details and how it connects to other parts. Cover every angle from start to finish. You might want an architecture specialist agent here. I pulled a few that genuinely help with this phase.
5. Iterate relentlessly. Claude Code outputs a mix of genius and nonsense. Your brain filters which is which. Always supply official documentation. Paste links. Use Context7 MCP. Feed it quality sources because garbage in means garbage out.
6. Build methodically once paper design is solid. Implement one piece at a time. Run extensive tests before touching the next component. Resist the urge to rush. Spending two days getting feature X bulletproof beats a two-hour deploy followed by panic when users actually touch it.

As you can already tell.. this isn't some revolutionary framework. Just a practical approach that's working for my current SaaS build. The architecture is legitimately complex and will take weeks to finish. Building the whole thing with AI because I've learned how to control Claude Code instead of letting it control me.

Got questions? Fire away in the comments.