Software Development insights, articles and news

A Minimum Deliverable Value (MDV) is a lightweight, functional outcome that tests a core assumption or delivers operational insight without the bloat of a full MVP. This is ideal for validating a specific assumption, exploring a technical opportunity, or demonstrating early value before investing in a larger, traditional MVP or product build.

At a recent Sheffield AI meetup, I gave a talk that aimed to unpack a big question: Is AI coming for your job? Short answer? No. But not for the reasons you might think. Rather than fall into the trap of hyperbole, I approached the topic by stepping back and asking a different question: How have the skills and resources around building software changed over time?

Modern cloud environments provide several different mechanisms and services for deploying a web application. In a more traditional scenario, an application may be deployed to a bare metal server or a virtual machine (VM).

At The Curve we do a lot of talking about “The Internet of Things”, we offer IoT consultancy services, we even host IoT events, and at the office, there’s more often than not, a half-assembled “thing” sitting on a desk waiting for its life as a connected internet device to begin.

We’re often engaged by our clients to develop Minimum Viable Products (MVPs) of a given product or system. More often than not we see a common and recurring problem with the original brief – the “MVP” is packed full of features of varying shapes and sizes.

As a recently appointed Freeman at the Company of Cutlers in Hallamshire, The Curve were given the opportunity to attend their regular monthly Tuesday Breakfast members event, and present a topic which gives rise to some of the most pressing challenges and opportunities facing companies today.

Story points estimation is an estimation method that is often used in agile software development. Story points are a unit of measure used in agile project management to estimate and compare the complexity, effort, and relative size of features or user stories within a project.

Sometimes it can be useful to request a manual approval before a deploy is unleashed on production. GitHub supports manual approval when you use environments, but only on public repositories or private repositories for GitHub Enterprise. In this post, I look at how GitHub Actions and Microsoft Teams can be used to create a manual approval process.

We use continuous integration and continuous deployment techniques regularly in the delivery of our projects. Whilst our team predominantly uses GitHub Actions these days, we’ve supported a variety of CI tooling including Jenkins and GitLab Pipelines.

Estimating the effort involved in any project can be a challenge, and software projects are no different. Arriving at an accurate estimate and plan is tricky, to get right.