In the early days of generative AI, AI-driven programming seemed to promise endless possibility, or at least a free pass to vibe code your way into quick wins. But now that era of freewheeling experimentation is coming to an end. As AI works its way deeper into the enterprise, a more mature architecture is taking shape. Risk-aware engineering, golden paths, and AI governance frameworks are quickly becoming the new requirements for AI adoption. This month is all about the emerging disciplines that make AI predictable, responsible, and ready to scale.
Top picks for generative AI readers on InfoWorld
What is vibe coding? AI writes the code so developers can think big
Curious about the vibe shift in programming? Hear from developers who’ve been letting AI tools write their code for them, with sometimes great and sometimes disastrous results.
The hidden skills behind the AI engineer
Vibe coding only gets you so far. As AI systems scale, the real work shifts to evaluation loops, model swaps, and risk-aware architecture. The role of AI engineer has evolved into a discipline built on testing, adaptability, and de-risking—not just clever AI prompts.
