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Homepage > News > Tech > How AI reshapes programming, building applications This post is a guest contribution by George Siosi Samuels, managing director at Faiā. See how Faiā is committed to staying at the forefront of technological advancements here. I’ve been diving into how artificial intelligence (AI), especially the rise of large language models (LLMs) and probabilistic thinking, is changing how we build software. It’s a full-on paradigm shift, and it’s got me thinking: Are we finally catching up to the way humans naturally think, or are we paving a new path altogether?  Let’s unpack this with a nod to Manus AI, JSON’s fading relevance, XML’s quiet comeback, and where LLMs like Claude might land in the next 12–18 months. Oh, and let’s throw scalable blockchains into the mix since they will become increasingly important in the AI space over the next five years. AI’s probabilistic thinking: A mirror to human nature Technically, humans are probabilistic thinkers at the core. We make decisions based on incomplete information, gut feelings, and patterns—think of how beliefs, cultures, and values act as our own “guardrails,” steering us through uncertainty. However, we have become used to setting our world up in more deterministic ways because it provides us with more certainty, even if illusory. AI’s evolution, particularly with LLMs, is starting to reflect this. Probabilistic models don’t need pristine, structured data to shine—they thrive on messiness, inference, and context, much like we do in real life. But it certainly helps if the data itself is “clean” (think organic food over fast food but for data).  This is a loud and clear signal: We need to build applications that leverage AI’s probabilistic strengths, not fight against them with rigid, deterministic frameworks. Take JSON parsing, for instance. For years, we’ve leaned on structured formats like JSON (and XML before it) to wrangle data for apps—clean, predictable, and…

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Filed under: News - @ April 3, 2025 7:21 am