I Am an Engineer (anna.kiwi)

After watching Geoffrey Huntley’s “The future belongs to people who can just do things” at Engineering AI, the author realized that years of designing robust systems and APIs deserved the title they’d been avoiding: engineer. Working on Automattic’s charts library, they didn’t just write code — they designed composition APIs for extensibility, refactored positioning from absolute to flexbox for maintainability and responsiveness, built Chart Context and theme controls, consolidated Storybook sample data for scalability, and created an AI-friendly development guide. Those decisions involved thinking through backward compatibility, edge cases, migration paths, and incremental PR strategies — all hallmarks of engineering rather than “vibe coding.” The broader takeaway for the AI/ML community is cultural and technical: as AI blurs language- and stack-based identities, what matters is engineering thinking — system architecture, antifragility, and designing for unknown future uses — not formal credentials. That shift underlines two imperatives for teams using AI-assisted development: evaluate skills by systematic problem-solving and guard against over-reliance on generated output without architectural rigor. Claiming the engineer title here signals a move toward recognizing demonstrated capability and mindset, which will matter increasingly as AI changes how software is built and judged.