Author(s): Suraj Pandey

Originally published on Towards AI.

Vibe Coding Has a Ceiling. Cadence Is the Floor

There’s a specific moment every team hits with AI coding assistants. The first few weeks feel like magic — features that took days now take hours. Then something breaks in production, nobody can explain why the agent made the choice it made, and the retro turns into a debate about whether the tool is the problem or the process is.

Cadence is presented as a skill that addresses the real bottleneck of AI coding: validation capacity. Instead of treating “vibe coding” and heavy engineering ceremony as the only options, it uses a decision procedure to determine the cheapest level of process that still provides sufficient confidence for each specific change. The article explains how Cadence organizes work into three lanes—Quick, Standard, and Assured—based on risk, and how it enforces a verification hierarchy so criteria are only marked complete when evidence exists. It also outlines why Cadence is more than a prompt library, highlighting structural differentiators like risk-adaptive escalation, a continuous architecture loop, different postures for greenfield vs. brownfield work, and “no hidden writes.” Finally, it provides acknowledgments/lineage, quick-start instructions for multiple agents, and a concluding argument that Cadence makes AI coding honest about required confidence to prevent technical debt.

Read the full blog for free on Medium.

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

Published via Towards AI