A curated collection of links covering software architecture, unit testing pitfalls, Scrum practices, AI's impact on creativity, and personal tech learning.
Explains how the software development practice of 'grooming' can be applied to boost productivity in any project by preparing work ahead of time.
Explains the distinct roles, responsibilities, and focus areas of Scrum Masters, Delivery Managers, and Project Managers in software development and project management.
A consultant provides 20 questions to assess the maturity, predictability, and effectiveness of software development teams and their processes.
A developer critiques the blind adoption of Scrum, arguing it's often misapplied and becomes a rigid, unproductive ritual rather than a useful framework.
A satirical guide on how to misuse and distort the Scrum framework, leading to failure, to highlight common Agile anti-patterns.
Argues that Kanban is more adaptable and effective than Scrum for software teams, explaining how Kanban principles enhance responsiveness and decision-making.
Analyzes why daily stand-ups often fail in software teams and provides actionable advice to fix them by refocusing on core Agile principles.
A guide to essential developer team workflows covering Git branching strategies, Agile methodologies, and CI/CD practices for effective collaboration.
A software engineer reflects on their career evolution as an Individual Contributor across agency, consulting, and product team environments.
A former Microsoft intern shares five key lessons learned about productivity, teamwork, and coding during their summer internship.
A data scientist shares how adopting Scrum, despite initial resistance, improved project management and delivery for data science teams.
A comic strip depicting a daily standup meeting, highlighting common time-wasting behaviors in agile development.
Explores adapting Agile/Scrum frameworks for data science teams, covering effective practices and necessary adjustments for the unique challenges of data science work.
Analyzes how Agile methodologies like Scrum can be applied to data science teams, highlighting effective practices and inherent challenges.
An inside look at Heroku's agile engineering culture, focusing on small team structures, self-chosen tools, and collaborative practices.
