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Users need stronger "harnesses" and better interfaces for AI models, specifically to handle context and memory management more effectively, as current solutions are perceived as weak.
We are spending way too much energy arguing over which AI model is the smartest. It’s like obsessing over engine horsepower while completely ignoring that vehicles are being completely reinvented from first principles. The quiet truth of the last few years is that AI only looked magical because humans were acting as the runtime: silently stitching fragmented outputs together, catching mistakes, and doing the invisible labor required to make a tool actually useful. That phase is over. Intelligence is moving out of the text box and into the execution layer. The durable advantage won't belong to whoever happens to rent the best model on a random Tuesday afternoon. It’s going to belong to whoever builds the strongest systems around it. Let's face it, prompt chains are not software architecture. Once an AI is allowed to touch live state, you need authority gates, deterministic truth cores, and verification built as actual infrastructure. Raw autonomy without control isn't a product. It’s just an incident report with good PR. I wrote about why the real battle in AI is no longer model quality, but the operating principles around it. 🔗 https://lnkd.in/grHQUMXx