OutSystems CEO on how enterprises can successfully adopt vibe coding
Everybody is building AI agents. But the enterprises actually shipping them to production are learning that an agent on its own is rarely the answer. In this episode of The New Stack Agents, OutSystems CEO Woodson Martin explains why AI agents alone fail in production and how blending agents, APIs, workflows, and human oversight drives real ROI.
Week in review: 50 experiments, 0 humans, 1 wild week
The story that dominated our traffic charts this week at The New Stack was born in an unlikely place: a 630-line Python script. This report by Janakiram MSV is about Andrej Karpathy’s AutoResearch, which ran 50 AI experiments overnight on a single GPU without any human input.
The second-most read story of the week was Paul Sawers’ report on Anthropic quietly removing the long-context pricing surcharge for Claude Opus 4.6 and Sonnet 4.6. That change means 1-million-token context windows are now available at standard per-token rates. Also from Paul this week is a look at Tower, a startup founded by ex-Snowflake engineers who want to tackle a blind spot in data engineering.
Our story on how MCP’s four biggest production-use growing pains will soon be solved was also widely read. See what may be fixed in 2026.
Finally, Jessica Wachtel's beginner's guide to vibe coding held its own, boasting the longest average read time of any article in our top five.
Generative models alone aren’t enough for production-grade AI. Without a unifying control plane, scaling autonomous agents often leads to hallucinations, cascading errors, and unpredictable system behavior. Join us next week for a deep dive into the missing piece in the AI stack: the Control Plane.
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AI-powered K8s observability best practices in 2026 On-demand
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"Vibe Coding" isn't just about writing prompts. It's about evolving from a manual coder to a technical conductor. This brand-new Vibe Coding Roadmap from our sister site, roadmap.sh, offers a comprehensive guide to building software in the AI-first era! It outlines how to leverage AI agents to handle the syntax while you focus on architecture, logic, and product vision.