Jan Bosch
In earlier posts (such as here), I have discussed different approaches to software development and one of the key models for this is the HoliDev model where we combine requirements driven development, outcome-driven development (e.g. A/B testing) and AI-driven development. In the figure below, the HoliDev model is shown graphically. It may easily seem that … Read more
As I’m spending an increasing amount of time in the AI field with a variety of companies, I’ve noticed an interesting misconception in the ML/DL space. Many have a tendency to focus on data sets, experimenting with different models using a specific set of data and, finally, deploying a model in a specific context. This … Read more
Data-driven decision making frequently requires experimentation as a mechanism to acquire the necessary data. When working with companies in transitioning from opinion-based to data-driven decision making, however, I frequently run into push back. The typical comment is that we already know the answers to the specific questions at hand and since we already know this … Read more
During the last week I was reflecting on the change processes ongoing in several of the companies that I work with. Although I don’t want to generalize too aggressively, it seems to me that most companies are on a similar journey. Starting from a situation where the key value proposition of the company was expressed … Read more
In last week’s article, I outlined the first phase of adopting machine & deep learning (ML/DL) which is concerned with experimentation and prototyping. In the figure below, we show the steps that companies typically evolve through while adopting AI,ML and DL solutions. As shown in the figure, the next step is the careful use of … Read more
This week I got the opportunity to speak at the initiative seminar organized by the Chalmers AI Research center (CHAIR). The key message in my presentation was that working with artificial intelligence (AI) and specifically machine & deep learning (ML/DL) constitutes a major software engineering challenge that is severely underestimated by companies that start to … Read more
As I have been writing about adopting data-driven decision making in the broad sense and data-driven development more narrowly over the last weeks, several people have reached out to me, discussed with me and more generally explored the subject with me. During these engagements, I realized that many products and services exist for the sole … Read more
We live in a world that is driven by a Need for Speed and when leaders mention agility, continuous integration and continuous deployment, often speed is mentioned as the key driver. Having worked with dozens of companies, my learning is that companies go through a number of evolution steps in order to work with speed. … Read more
In the posts from the last weeks, I discussed the first two steps in adopting data-driven development (see figure below), i.e. modeling feature value and building the necessary infrastructure. Once we have described the value that we expect from a feature and have constructed the infrastructure required to capture the data coming back from the … Read more
In last week’s blog post, I discussed the first step in adopting data-driven development (see figure below), i.e. modeling feature value in quantitative terms. Once we have described the value that we expect from a feature, the next step is to ensure that we can indeed measure and collect the necessary data in order to … Read more
