I build production software with Claude Code. Every day.
Not tutorials. Not demos. Real products shipping to real users — built with AI agents as a core part of the engineering workflow. Architecture decisions, workflow patterns, and the lessons you only learn by doing it daily.
30 years of engineering discipline applied to AI-augmented development. The tool is new. The engineering principles are not.
Most AI coding content is demos. This is production.
The gap between “look what AI can do” and “here is how I ship products with AI” is enormous. I write from the production side.
Patterns from building with Claude Code daily.
Architecture, workflows, and the engineering discipline that makes AI agents productive.
Command-driven development
Structured prompting patterns, CLAUDE.md configuration, and the logging discipline that turns Claude Code into a predictable engineering tool.
Multi-tenant architecture with AI
Building complex SaaS platforms with AI agents — tenant isolation, security patterns, and database design that AI can navigate safely.
AI workflow design
Designing repeatable workflows where AI handles scaffolding, testing, and documentation while humans direct architecture and creative decisions.
Code review for AI output
Review processes, linting gates, type checking, and the quality assurance patterns that keep AI-generated code production-ready.
Roadmap and project management
Using Claude Code for roadmap tracking, progress documentation, and the structured project management that keeps complex builds on track.
Agent orchestration
Multi-agent patterns, task delegation, and the prompt architecture that makes AI agents work together on complex features.
Read the real-world experience.
Deep dives into building production software with Claude Code.
What Two Weeks of Real-World Building with Claude Code Revealed
The honest assessment after intensive daily use — what works, what breaks, and what changes about how you think about code.
Read postCommand-Driven Development with Claude Code
How structured logging and command patterns turn Claude Code from a chat tool into a production engineering workflow.
Read postClaude Code for Roadmap Management
Using Claude Code to manage project roadmaps, track progress, and maintain development momentum across complex projects.
Read postBuilding an 80s Easter Egg with Claude Code
A fun deep-dive into building a creative feature with Claude Code — showing how AI handles creative coding challenges.
Read postVibe Coding Is Not the Problem — Vague Thinking Is
The real issue with AI-assisted development is not the tools. It is the lack of clear thinking before you start prompting.
Read postCommon questions
What engineers and leaders ask about Claude Code in production.
How is building with Claude Code different from using ChatGPT or Copilot?
Claude Code operates as an autonomous agent with full codebase access — it reads files, runs commands, edits code, and commits changes. Copilot suggests completions. ChatGPT generates snippets. Claude Code builds features end-to-end. The skill is in directing it, not in typing prompts.
Can Claude Code handle production-grade architecture?
Yes, with the right guidance. I build multi-tenant SaaS platforms, API systems, and complex frontend architectures with Claude Code daily. The key is providing clear architectural constraints and reviewing output critically — the same way you would review a junior developer with exceptional speed.
What are the biggest mistakes teams make with AI coding tools?
Treating them like magic. No clear architecture before prompting. No code review process for AI output. No structured workflows — just ad-hoc "ask it to build something" chaos. AI agents amplify whatever process you already have. If your process is messy, AI makes it messier faster.
How do you handle code quality with AI-generated code?
Same way I handle code quality with any developer — structured review, automated linting, type checking, and testing gates. AI-generated code needs the same rigor as human code. The difference is volume — AI generates more code faster, so your review processes need to scale.
Is Claude Code replacing developers?
No. It is replacing tasks, not people. Writing boilerplate, scaffolding components, implementing known patterns, running through checklists — these get automated. Architecture decisions, user empathy, debugging novel problems, and creative problem-solving remain human. The developer role is shifting from typist to director.
Can you help our team adopt Claude Code?
Yes. I design structured AI workflows for engineering teams — prompt libraries, review processes, architecture patterns, and the training that turns ad-hoc usage into repeatable productivity. The goal is consistency, not just speed.
Find out how AI agents fit into your engineering workflow.
A 30-minute review of your current development workflow and where structured AI patterns can replace ad-hoc prompting with repeatable, production-quality output.
You will leave with specific workflow patterns, not vague advice.
Schedule an AI Workflow ReviewFree 30-minute review. Production-tested patterns. Daily AI experience.