Vibe coding is out; orchestration is in

The fast way to build with artificial intelligence is no longer the hard part; the new work is wiring models into review, test and approval steps that teams trust. (developers.openai.com) In plain terms, “vibe coding” means asking a model for code in natural language and iterating by prompt instead of writing every line yourself. The phrase was coined by Andrej Karpathy in February 2025, and by November 2025 Collins Dictionary had named “vibe-coding” its word of the year. (tech.yahoo.com) The newer pitch from toolmakers is orchestration: one model writes code, another checks tests, another scans for security issues, and the workflow can pause for a human before anything ships. OpenAI’s Agents documentation says these systems “plan, call tools, collaborate across specialists,” while Anthropic’s Claude Code docs describe subagents that isolate context, run in parallel and carry specialized instructions. (developers.openai.com) (platform.claude.com) That shift follows a year in which AI coding tools became common enough that raw code generation stopped being a differentiator. Stack Overflow’s 2025 developer survey found 84% of respondents were using or planning to use AI tools, but 46% said they distrust the accuracy of the output and only 33% said they trust it. (survey.stackoverflow.co) The delivery problem is not just whether a model can write a function; it is whether a team can ship changes repeatedly without breaking production. DORA’s 2024 report, based on more than 39,000 professionals, framed software performance around stable delivery systems rather than one-off bursts of productivity. (dora.dev) That is why the new language around coding assistants sounds more like factory design than chatbot prompting. OpenAI’s SDK docs point developers to “orchestration and handoffs,” “guardrails and human review,” and server-owned control over tools, state and approvals as workflows get more complex. (developers.openai.com) Anthropic is making the same case with different labels. Its Claude Code webinar for advanced users says teams are moving to subagents, hooks and Model Context Protocol connections for “multi-step work,” including automated pull request review, test generation and checks that catch regressions before a human sees them. (anthropic.com) Security is one reason this structure is showing up now. Anthropic’s Claude Code Security reviewer for GitHub pull requests says it analyzes changed files, comments on findings and is “not hardened against prompt injection attacks,” so the company recommends running it only on trusted pull requests and requiring approval for external contributors. (github.com) Anthropic also began limited testing of Claude Code Security with enterprise and team customers in February 2026. CyberScoop reported the product is designed to scan codebases for vulnerabilities, suggest patches and keep a user approval step before deployment. (cyberscoop.com) GitHub’s 2024 enterprise developer survey pointed in the same direction inside large companies. In the United States sample, 92% said they use AI coding tools to generate test cases at least some of the time, 100% reported using AI to automate security reviews to some extent, and 99% expected AI coding tools to improve security. (github.blog) The result is a quieter definition of progress than the early “just prompt it” demos promised. Teams still use models to write code, but the work that now stands out is the workflow around that code: who checks it, what tests run, which tools can act, and where a human has to say yes. (developers.openai.com) (platform.claude.com)