The last six months in LLMs in five minutes | Hacker News

LLMs are increasingly good at producing compilable code and other pattern-based outputs, making them very useful for productivity.

But they still struggle with context, refinement, and tasks that require deeper abstraction or true understanding.

The post argues this marks a practical threshold: AI can speed up work, yet still miss user intent and reasoning-heavy goals.

That gap matters for how we evaluate current models and set expectations for future AI progress.