Questions,answered straight.

How to build production software with AI systems using the core pillars of AI-native engineering: avoiding the vibe-coding trap, context engineering, spec-driven development, MCP tooling, agent orchestration, and verification gates. Every chapter has concrete patterns, real code, and team playbooks.

Software engineers, tech leads, and engineering managers who already use AI coding assistants but want to move past ad-hoc usage into repeatable, production-grade practice.

No. The book assumes solid software engineering fundamentals and treats AI-native engineering as a discipline of software delivery, not as an ML research topic.

The focus is on patterns that outlive any single tool. Claude Code, Cursor, Copilot, Codex, Windsurf, Aider and whatever ships next all fit the practice. Specific tools appear as examples, never as requirements.

Vibe coding is ad-hoc AI usage that produces plausible code which fails in production. AI-native engineering is the disciplined alternative: explicit context, clear specs, verification gates, and team practices that ship reliable software.

No. Prompt engineering optimises one input for one output. AI-native engineering designs the whole system around the agent: the spec you write before the prompt, the rules that load every session, the tools that give the agent live context, the gates that check its output, and the team practices that make any of it repeatable.

Yes. The Early Release is on the O'Reilly learning platform, and chapters land as they are written. The code ANSE2026 gives you 30 days of free access to the platform.

Plenty. The foreword, the 7-day roadmap, the 8-area team canvas as a printable PDF, and the 40-question maturity assessment are all free and need no email address.

The manuscript is due 25 November 2026, with the print edition following. Early Release chapters are published as they are finished, so subscribing to the newsletter is the fastest way to know when a new one lands.