10 essential trends finance leaders need to know - intheblack
<a href="https://news.google.com/rss/articles/CBMiqAFBVV95cUxNanpYeGZ4clVJbmkwWnplaFZkQXEtVE5GNHVyZ0t3TmZ1TW0yVENXQ1dWR05MZlk5R3R2S296enIxSGF2WGJoN3dFazlkNS00czBld2RaZmhCSXJQMHNBQWhlS21QYzZxWVRPVy1xQmFDZGpZVGVuSm1qdzZyYXd2bEJkYkJtM3BhY0x1aDVnZzI1UkRfb01RRVI3US0tbmVrZkpJT3o2Tko?oc=5" target="_blank">10 essential trends finance leaders need to know</a> <font color="#6f6f6f">intheblack</font>
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The Bottleneck Was the Feature
Mario Zechner — the creator of libGDX, one of the most widely-used Java game frameworks — recently published "Thoughts on slowing the fuck down" . His argument: autonomous coding agents aren't just fast, they're compounding errors without learning . Human developers have natural bottlenecks — typing speed, comprehension time, fatigue — that cap how much damage any one person can do in a day. Agents remove those bottlenecks. Errors scale linearly with output. He names the pattern Merchants of Learned Complexity : agents extract architecture patterns from training data, but training data contains every bad abstraction humanity has ever written. The default output trends toward the median of all code. And because agents have limited context windows, they can't see the whole system — so they r
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