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Dialectic Agent Networks: A Human-Inspired Approach to AI Development
Most AI agents are trained to agree: same dataset, same goals, same outputs. But humans don't work like that. We grow by encountering disagreement, adapting, and evolving our perspectives. I'm working on a new approach I've coined: Dialectic Agent Networks (or D.A.N.
Do We Still Need Human-Readable Code in an AI Future?
Do We Still Need Human-Readable Code in an AI Future? For 70+ years we’ve climbed the readability ladder—from raw opcodes to assembly, to C, to Python and TypeScript. Every step was a concession to human limits: short-term memory, syntax fatigue, cognitive load. But what happens when the authors
AI Made It Easy… But Did We Get Better?
AI made it easy. Tasks that once took hours (writing code, drafting content, even debugging) now take minutes. But here's the uncomfortable question: Did we use that time to get better? Or just to do the same things faster? As someone who started programming with books, print statements,
Work Hard, Rest Smart: Why Generations Clash at Work
Are younger generations too focused on fun? Or did they just learn from watching older generations burn out? Growing up, they saw hustle glorified at the expense of health. So they chose something different—intuition, flexibility, and boundaries. But sometimes, that intuition overlooks the depth that experience brings. On the