Test-Driven Development with Claude Code, featuring Paul Hammond

In this episode, host Jonathan Hall sits down with fellow veteran software developer and early adopter Paul Hammond to discuss how to successfully integrate AI coding tools—like Claude Code—into a rigorous, professional engineering workflow without losing control or code quality.

Key Topics Discussed

• The Reality of AI Coding Assistants: Why early experiences with AI often feel like an "impressive parlor trick" that breaks more things than it fixes, and how to transition from chaotic "vibe coding" to disciplined engineering.
• TDD (Test-Driven Development) with AI: How Paul and Jonathan leverage Test-Driven Development practices to constrain AI scope, provide instant validation loops, and build comprehensive regression suites.
• Managing AI Context & Compaction: Strategies for dealing with context loss and compaction events, including the use of incremental plans (PLAN.md), architectural decision records (ADRs), and specialized custom agents or skills.
• Mutation Testing for AIs: Utilizing custom AI skills inspired by mutation testing frameworks like Stryker to ensure that AI-generated tests are actually robust and catching real defects.
• The Future of the Software Industry: An honest look at job security, the impact of AI on junior developers, the rising barrier to entry for the profession, and why core engineering fundamentals matter more than ever.

Guest Links & Resources

• Paul Hammond on LinkedIn
• Paul Hammond's GitHub Dotfiles: Explore Paul's custom configurations, skills, and agents on GitHub.
• Scenarist: Paul's open-source testing tool designed to help navigate modern frontend frameworks like Next.js (scenarist.io).
• Chippin: Check out Paul's upcoming micro-SaaS framework and application project at chippin.online.
• Ian Cooper's TDD Video: Referenced during the episode regarding behavior-based testing over rigid unit isolation (TDD Where Did It All Go Wrong).

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