How 2023 AI Predictions Aged: Looking Back from the Start of 2026

Neural networks have evolved from mere models to components in integrated systems, transforming AI applications beyond chatbots towards operational intelligence. The real breakthroughs in AI from 2023 to 2025 have been less about advancements in model size and more about the development of supporting engineering layers that enable models to become reliable and scalable in real-world scenarios. Key enablers include grounding models with context, integrating tools and APIs, expanding context capabilities, enhancing compute efficiency, fine-tuning for alignment, and improving reasoning abilities. The integration layer has emerged as a crucial component, providing a standardized framework for connecting models with tools, context providers, and execution environments, which is exemplified by the Model Context Protocol (MCP). This shift has highlighted that the real value in AI systems lies in their architecture and integration capabilities rather than in the models themselves, as demonstrated by the varied success of teams using the same models but different integration strategies.

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