Reasoning Is Not Model Improvement

Summary

How tool use became a substitute for solving hard problemsWhen OpenAI released o1 in 2024 and called it a "reasoning model," the industry celebrated a breakthrough. Finally, AI that could think step-by-step, solve complex problems, handle graduate-level mathematics.But look closer at what's actually happening under the hood. When you ask o1 to multiply two large numbers, it doesn't calculate. It generates Python code, executes it in a sandbox, and returns the result. Unlike GPT-3, which at least attempted arithmetic internally (and often failed), o1 explicitly delegates computation to external tools.This pattern extends everywhere. The autonomy in agentic AI? Chained tool calls like web searches, API invocations, database queries. The breakthrough isn't in the model's intelligence. It's in the orchestration layer coordinating external systems. Everything from reasoning to agentic AI is just a sophisticated application of code generation. These are not model improvements. They're engineering workarounds for models that stopped improving.This matters because the entire AI industry (from unicorn valuations to trillion-dollar GDP projections) depends on continued model improvement. What we're getting instead is increasingly elaborate plumbing for fundamentally stagnant foundations.GPT-5: The Emperor's New ReasoningAugust 2025 should have been a triumph. OpenAI promised "PhD-level intelligence in everyone's pocket." What they delivered barely moved the needle on code generation, the one capability that everything else depends on. And that's the bottleneck: code generation is the kingpin. Better code → better reasoning (via execution) → better agents → higher productivity → trillion-dollar markets. When the kingpin doesn't move, the entire chain stalls.The disappointment was palpable among developers using AI coding tools. AI coding tools building on OpenAI's models (like Cursor, GitHub Copilot, Replit) had bet billions on exponential improvement with each release. GPT-5 ...