What makes intelligence? Is it the ability to solve puzzles, recall facts, or predict outcomes? A compelling view is that intelligence emerges from the union of two core abilities: the use of language and the use of memory. Language gives shape to thought. A sommelier can detect and describe subtle differences in wine not only because of sensory skill but also because of vocabulary. Words sharpen perception, making distinctions visible that might otherwise go unnoticed. Memor

For over a year, AI development seemed to revolve around refinement rather than reinvention. Each new release promised improvements: lower latency, smoother interfaces, more expressive conversations. It gave the impression of rapid progress, but underneath, the same foundation remained in place. GPT-4 was still the model powering it all, even when presented under new names like GPT-4 Turbo or GPT-4o. What changed was mostly how the model was delivered, not how it was taught.

Revisiting Agentic Intelligence in the Age of Execution In April, I wrote about a shift in posture. From reactive AI systems to autonomous ones. From tools that wait to systems that act. That article, Agentic Intelligence , sketched a near future where models would not just respond, but take initiative. It was about architecture, intent, and the structure of action. Now, that shift is no longer theoretical. With the release of ChatGPT Agent, the idea has entered the desktop.