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Coding Is the Easier Part: Makers, Machines, and the Mess in Between

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Coding Is the Easier Part: Makers, Machines, and the Mess in Between

De: Kresimir Koncic
Narrado por: Matt Quandt
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 Were told to put Artificial Intelligence into everything. This book is about figuring out where to leave it out. The AI pitch is oddly seductive and a bit too convenient. Think of software that writes itself, medical bots that cure cancer, and a civilization that only needs to collect its universal basic income once a month. But step inside the craft, and the evidence gets messier: A patchy server that wont restart, a coding agent that is always apologizing, and Alexa that will probably misread Krešimirs name. Coding Is the Easier Part is about that overlooked reality, where people, incentives, abstractions, and hidden forces shape software long before and long after a line of code is synthesized.Drawing on unusual stories from the Incas first databases, Cold War cybernetics, the Ethereum Merge, WordPress drama, and todays AGI benchmark theater, Krešimir Končić closes the gap between what the industrys loudest panelists promise and what makers actually have to build, repair, and adapt. Written for developers, designers, managers, entrepreneurs, and curious readers trying to make sense of AI without the hype or the doomsday narrative, the book explores an increasingly capable braid of makers and machines it calls speckled intelligence. As that braid reshapes our virtual worlds, its human makers remain irreplaceable, with an increasingly important role and more work to do. So, whether Coding Is the Easier Part sounds like heresy, cope, a lazy jab, or a combination of all three, a dilemma remains. What if coding isnt the easier part for us, but simply the easiest part of software making to give away? About the Author Krešimir Končić started programming in 1996 and has been writing about software ever since. An engineer, longtime columnist, and owner of Neuralab, he has worked with his team on over 200 projects, all across two unusually wild decades of software making. He was training neural networks in the early 2000s, well before they became sort of religion, and he still writes from inside the machine, where the work is less magical and considerably stranger than most polished AI stories admit.©2026 Neuralab Inc. (P)2026 Neuralab Inc. Historia y cultura
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