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Facilitating the Spread of Knowledge and Innovation in Professional Software Development

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  • Managing High-Performing Software Teams

    High-performing teams expect their leader to enable them to make things better, Gillard-Moss said at QCon London. Independence in software teams can enable decision-making for faster delivery. Teams need empathy, understanding, and guidance from their managers.

  • How a Sustainable Mindset in Software Engineering Can Increase Team Performance and Prevent Burnout

    A sustainable mindset in software engineering matters because software is still primarily built by humans, and we must prioritize their well-being, Marion Løken said at NDC Oslo. Integrating the team more deeply into discovery work, discussing feedback collectively, and fostering a culture of psychological safety helped to engage her team and mitigate burnout.

  • Setting up a Data Mesh Organization

    A data mesh organization: producers, consumers, and the platform. According to Matthias Patzak, the mission of the platform team is to make the lives of the producer and consumers simple, efficient and stress free. Data must be discoverable and understandable, trustworthy, and shared securely and easily across the organization.

  • How to Improve Software Team Performance with Experimentation

    According to Terhi Aho, experimentation is a way of thinking that guides action. By experimenting we can develop ways of working without a major change process. It can help software teams to solve problems in small steps, relieve their workload, and foster self-management.

  • Measuring and Reducing the Environmental Impact of Software

    Software applications often manage big amounts of data; most of them are internet-based applications, and incorporate artificial intelligence. According to Coral Calero, these three aspects improve the capabilities and functionalities provided by software but they have also increased the amount of energy needed. We need to measure energy consumption of software to control its environmental impact.

  • Enabling Fast Flow in Software Organizations

    Resolving impediments to flow and removing unnecessary sources of cognitive load can make culture issues disappear in organisations, Nigel Kersten argued. Start with a clear strategy that is easy to communicate, then follow the path to creating stream-aligned teams and platform teams, he suggested.

  • The Value of Using Timeless Testing Tools

    According to Benjamin Bischoff, developers find new tools much more interesting than old ones, as they offer an opportunity to learn new technologies and approaches and to expand their tool belt. Using tools that have been around for decades, however, can save time and budget. When evaluating tools, it is more important to understand the problem to be solved than to jump straight into the tools.

  • How Tech-Enabled Networks of Software Teams Work

    To maintain agility at scale, software teams can use technological and organizational solutions to reduce dependencies and work autonomously. According to Fabrice Bernhard, collaboration technology can be leveraged to create a distributed network of teams. To empower their teams, leaders can support them with a systematic problem-solving culture aimed at delivering good products to customers.

  • Experiences from Doing DORA Surveys Internally in Software Companies

    Doing DORA surveys in your company can help you reflect on how you are doing software delivery and operation. The way you design and run the surveys, and how you analyze the results, largely impact the benefits that you can get out of them. Carlo Beschi shared his experiences from doing DORA surveys at Agile Cambridge.

  • Ideas for Crafting Inclusive Public Software Platforms

    Public software platforms should be inclusive and accessible to everyone, where people feel comfortable using them. It’s a big challenge to design a platform for everyone, from digital newbies to natives, with varying knowledge and experience of administrative processes. Government platforms must ensure their users' trust so that they feel safe using government services online.

  • Increasing Productivity by Becoming a Dual-Purpose Stream Aligned and Platform Software Team

    To manage their increased workload effectively and maintain quality and efficiency, a software team decided to become dual-purpose: stream-aligned and platform. They rewrote their main application to be API-first and implemented micro releases with their customer-facing products, to provide value to their end users quickly and maintain a steady flow of accomplishments for the team.

  • How Testing in the Metaverse Looks

    The "metaverse" typically refers to a collective virtual shared space that is created by the convergence of a virtually enhanced physical reality and a persistent virtual reality. According to Jonathon Wright, testing requires a mix of manual testing, automated testing, user testing, emulators, and simulators. Real-world testing environments are used to cover as many scenarios as possible.

  • How Building a Platform as a Product Empowered Software Engineers

    Platform engineering is about accelerating and empowering developers to deliver more product value faster over time. According to Jessica Andersson, most companies don’t invest in platform engineering until they reach a certain size. At QCon London she presented how their startup adopted platform engineering, what strategy they took, and what they did to gain platform adoption from developers.

  • Transforming Software Product Teams into Tech Investors

    The key responsibility of an organisation lies in balancing user value with profitability. In a product organisation, software product teams invest their own time. According to Fabrice des Mazery, software developers are much more than stakeholders; they are the main investors as they are part of the product teams.

  • How Data Mesh Platforms Connect Data Producers and Consumers

    A challenge that companies often face when exploiting their data in data warehouses or data lakes is that ownership of analytical data is weak or non-existent, and quality can suffer as a result. A data mesh is an organizational paradigm shift in how companies create value from data where responsibilities go back into the hands of producers and consumers.

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