AGI Bottleneck: Engineering, Not Models
2025-08-24
The rapid advancement of large language models seems to have hit a bottleneck. Simply scaling up model size no longer yields significant improvements. The path to artificial general intelligence (AGI) isn't through training larger language models, but through building engineered systems that integrate models, memory, context, and deterministic workflows. The author argues AGI is an engineering problem, not a model training problem, requiring the construction of context management, memory services, deterministic workflows, and specialized models as modular components. The ultimate goal is to achieve true AGI through the synergistic interaction of these components.