Not so long ago, I believed AI would merely assist programmers. Six months later, I'm not sure I can do my daily job without Claude — and I'm not alone: 84% of developers now use or plan to use AI tools. As early as February 2023, GitHub measured 46% of code in Copilot-enabled files as AI-generated, with Gartner predicting 90% of enterprise engineers will use AI assistants by 2028. A poll of fifty developers at Dev Bcn confirmed this uniformity.

Companies are shifting from unlimited tokens to metered models. Gartner forecasts worldwide AI spending to hit $2.5 trillion in 2026, driving finance departments to scrutinize token cost per feature and trust percentage in generated code. Trust splits work into core expertise (where I care about HOW) and non-expert areas (where I care about WHAT). The 2025 Stack Overflow survey shows adoption up but trust down: 66% cite "almost right but not quite" as top frustration, and 45% find debugging AI code more time-consuming.

The risks are real. Days after its January 2026 launch, vibe-coded social network Moltbook exposed 1.5M API tokens due to a client-side database key with Row Level Security disabled, discovered by Wiz Research. CloudBees 2026 found 92% were confident their code was production-ready, yet 81% saw production issues rise from AI-generated code. Accountability blurs: Andrej Karpathy insists responsibility unchanged, while Simon Willison admits the line between vibe coding and responsible engineering is blurring. As AI removes traditional frontiers, senior developers like Aiden building financial apps face verifying code they don't fully understand.