Delivering software quickly while keeping quality intact can feel like a tightrope walk! I find that breaking tasks into sprints using Agile helps us tackle smaller pieces and allows for continuous quality checks. Automating testing is a game changer, catching bugs early and saving time for critical tasks. Plus, prioritizing must-have features ensures we deliver impactful elements without compromising on quality. Keeping communication open with the team is crucial, it helps everyone stay aligned and supported under pressure.

"Delivering high-quality software within tight deadlines requires a strategic approach. By adhering to robust development methodologies, prioritizing automated testing, and fostering effective communication, we can ensure that speed and quality go hand-in-hand. A focus on continuous improvement and a commitment to excellence are essential to meet the demands of today's fast-paced digital landscape.

Achieving faster software delivery while maintaining quality requires practices for rapid, reliable releases. Streamlined workflows and automation allow frequent, small updates, reducing risk and simplifying error detection. Key questions include: How fast can we release? How long it takes from idea to production? How often do releases cause issues? How quickly can we restore service after incidents? DORA metrics help measure these. A CI/CD pipeline with automated tests, code checks, and security analysis ensures standards. Feature toggling and quick recovery processes support fast, stable releases. A culture of quality, collaboration, and continuous improvement ensures shared ownership and optimised processes for fast, stable releases.

I would start by trying to define "faster software delivery" in your context. How many features can you release in a period? Or how many experiments you can do? Or another metric? For example, if you are pressured to deliver more features, it's logical that if you can decrease the "size" of the feature, you might be able to deliver more features, even if the development speed didn't change. Less size also means fewer risks, requirements, and complexity, so more quality will come. If experiments measure your speed, then an intelligent approach is leveraging other validation methods, like using no-code or low-code platforms or other strategies requiring minimal complex development.