Blog Archives

The AI team take a deep dive into Donella H. Meadows’ Thinking in Systems: A Primer. This is a posthumously published book that introduces systems thinking concepts to a broad audience. The book uses clear language and diagrams to explain system dynamics, including feedback loops, stocks and flows, and delays. It explores common system structures and behaviors, such as growth limits and policy resistance, offering insights into how to manage and redesign systems effectively. Meadows emphasizes … Continue reading →

The AI team take a deep dive into a booklet by Niels Malotaux which details the TimeLine technique, a project management method emphasizing iterative, small changes to improve project outcomes. It advocates for defining a clear project goal, prioritizing tasks based on value, and using just-enough estimation with frequent calibration. The TimeLine approach addresses potential project delays proactively, offering strategies to save time and avoid common pitfalls like adding personnel to a late project. The … Continue reading →

The AI team does a deep dive into an online presentation made by Dr Joseph Kasser and Bruce Lerner to the British Computer Society (BCS) in 2023. The presentation exposes two common misconceptions about systems thinking.  First, it clarifies the proper application of reductionism, arguing that it’s a valuable analytical tool, not an opposing methodology to systems thinking.  Second, it explains that “open” and “closed” systems are not distinct types but rather different perspectives on … Continue reading →

The AI team takes a deep dive into the technical architecture and operational logic of Large Language Models (LLMs). They explain that these systems are trained through a multi-stage process; pre-training, fine-tuning, and human feedback, to predict text sequence. A central focus is the Transformer architecture, which uses an attention mechanism to understand relationships between words and manage linguistic nuances such as spelling errors. The team clarify that AI “memory” is actually a process where the entire conversation history is re-read … Continue reading →

The AI team take a deep dive into a book by Dr Howard Eisner which examines the attributes of highly successful systems engineers. It profiles prominent figures like Leonardo da Vinci, Isaac Newton, and Albert Einstein, analyzing their traits and contributions. The author then explores seven key attributes—synthesizer, listener, curious/systems thinker, manager/leader, expert (in systems engineering processes and domain knowledge), and perseverer—through case studies and analysis of various successful systems engineers. The text also incorporates … Continue reading →