Heuristics That Almost Always Work An Article by Scott Alexander astralcodexten.substack.com Sometimes there’s a Heuristic That Almost Always Works, like “this technology won’t change everything” or “there won’t be a hurricane tomorrow”. And sometimes the rare exceptions are so important to spot that we charge experts with the task. But the heuristics are so hard to beat that the experts themselves might be tempted to secretly rely on them, while publicly pretending to use more subtle forms of expertise. …Maybe this is because the experts are stupid and lazy. Or maybe it’s social pressure: failure because you didn’t follow a well-known heuristic that even a rock can get right is more humiliating than failure because you didn’t predict a subtle phenomenon that nobody else predicted either. Or maybe it’s because false positives are more common (albeit less important) than false negatives, and so over any “reasonable” timescale the people who never give false positives look more accurate and get selected for. expertiseheuristicsprediction
The most rewarding iterations Initial designs for sophisticated software applications are invariably complicated, even when developed by competent engineers. Truly good solutions emerge after iterative improvements or after redesigns that exploit new insights, and the most rewarding iterations are those that result in program simplifications. Evolutions of this kind, however, are extremely rare in current software practice—they require time-consuming thought processes that are rarely rewarded. Instead, software inadequacies are typically corrected by quickly conceived additions that invariably result in the well-known bulk. Niklaus Wirth, A Plea for Lean Software So that you can get feedback on it and make it betterTo anticipate all the uses and abuses agileiteration