Debiasing Your Software Design Decision-Making

Every significant software design choice—whether you’re designing a bounded context, deciding on the system boundary, settling on an architectural style, selecting a complex system integration approach, and even evaluating a block of AI-generated code—has a moment where one path just feels right. But what if that powerful 'gut feeling' is actually a cognitive bias in disguise?

The human mind is a powerful tool, yet it is systematically prone to errors. These errors aren't just abstract ideas; they are design flaws in our own decision-making that can lead directly to fragile architectures, ballooning technical debt, and costly rework, regardless of whether the code was human or machine-generated. Biases like the anchoring effect (getting stuck on the first idea) or the sunk cost fallacy (clinging to a failing project) are constantly shaping your software.

Join us to move from a reactive, bias-driven approach to a deliberate, resilient, and ultimately more effective design process. This talk explores how cutting-edge research from behavioural economics can be applied directly to software architecture and development, with or without AI assistance.

We will move beyond simply being aware of biases. We will introduce a practical, five-step checklist designed to systematically 'debias' your design choices, helping you build both better software and a better decision-making habit for all your technical work.

You will learn how to:

• Be Decision-Ready: Recognize when Myopic Misery is rushing you into action, or when Status Quo Bias is trapping you in inaction due to cognitive load—ensuring you make choices based on strategy, not mental fatigue.
• Broaden the Frame: Combat Functional Fixedness and Additive Bias to uncover the elegant solutions your brain naturally ignores—breaking the cycle of solving every problem by simply adding more complexity.
• Seek Independent Advice: Move past Overconfidence Bias and Correlation Neglect to stop mistaking echoed opinions for independent proof, ensuring you are acting on diverse data rather than a single weak signal amplified by the group.
• Test Your Assumptions: Inoculate your team against the Authority Bias of AI-generated code and the Illusion of Control it fosters, replacing the dangerous comfort of "black box" certainty with rigorous stress-testing that withstands real-world chaos.
• Establish Simple Rules: Avoid the Law of Triviality (bikeshedding) to dramatically increase velocity, ensuring your team stops debating low-risk choices and focuses their cognitive energy on the decisions that actually stick.