AGI Is an Engineering Problem
We’ve reached an inflection point in AI development. The scaling laws that once promised ever-more-capable models are showing diminishing returns. GPT-5, Claude, and Gemini represent remarkable achievements, but they’re hitting asymptotes that brute-force scaling can’t solve. The path to artificial general intelligence isn’t through training ever-larger language models—it’s through building engineered systems that combine models, memory, context, and deterministic workflows into something greater than their parts. Let me be blunt: AGI is an engineering problem, not a model training problem. The Plateauing Reality The current generation of large language models has hit a wall that’s become increasingly obvious to anyone working with them daily. They’re impressive pattern…
