We all know that digital business requires both efficiency and a quality-driven mindset. While Jez Humble's CALMS (Culture, Automation, Lean, Measurement and Sharing) framework can help us pave the way to more efficient delivery, the pursuit of quality necessitates a continuous testing and quality assurance strategy. Both of these principles must be pursued within a context of limited resources, which makes it critical to constantly analyze, reason, prioritize, and choose between alternatives.
As writer John Ruskin put it, “Quality is never an accident. It is always the result of intelligent effort”. Indeed, the term "intelligence" derives directly from the Latin words intelligentia and intelligere, which mean “to understand, comprehend, come to know” and it is the combination of two primary words: inter (between) and legere (choose). In summary, delivering IT solutions takes intelligence to maintain a constant balance of risk and quality when delivering business value.
In this chapter, we propose a strategy for developing an intelligence base to support and enrich project quality gates. Naturally, a set of enhanced metrics is also needed to augment our intelligence, which we will examine further in the next chapter.
 R. Marselis, B. van Veendendaal, D. Geurts y W. Ruigrok, Quality for DevOps teams, Sogeti, 2020
 Sogeti, «Continuous Testing Report,» 2020
 A. Tort, «Is (Artificial) Intelligence Needed for Testing?,» SogetiLabs blog, 2018