From vibe coding to agentic engineering: PEV, context, and evals that ship
Production teams are moving from vibe coding to agentic engineering that plans, executes, and verifies work with tight context and evals. A practical guide to agentic engineering argues for a Plan → Execute → Verify loop, with humans acting as architects and supervisors while agents plan, write, test, and ship; it cites real adoption signals like TELUS time-savings, Zapier-wide usage, and Stripe’s weekly PR throughput ([guide](https://www.nxcode.io/resources/news/agentic-engineering-complete-guide-vibe-coding-ai-agents-2026)). Context discipline is emerging as a make-or-break factor: a new study shows repo-level AGENTS.md/CLAUDE.md files can degrade agent performance, pushing teams toward slimmer, task-scoped context that’s validated in CI ([AGENTS.md breakdown](https://www.youtube.com/watch?v=miDg-3rSJlQ&t=75s&pp=ygURU1dFLWJlbmNoIHJlc3VsdHM%3D), [DevOps context engineering](https://devops.com/context-engineering-is-the-key-to-unlocking-ai-agents-in-devops-2/)). Architecturally, vibe coding is “already dead” at scale; production agents enforce planning, tests, PR gates, and continuous evals before code lands ([Stripe agent deep dive](https://www.youtube.com/watch?v=V5A1IU8VVp4&pp=ygUYQUkgY29kaW5nIGFnZW50IHdvcmtmbG93)). For hands-on operating patterns—self-checks, context management, and when to escalate to humans—see this practitioner’s playbook ([effective coding agents](https://hackernoon.com/how-to-use-ai-coding-agents-effectively?source=rss)).