Six Months of LLM Developments in Five Minutes

The last six months have seen tremendous growth in Large Language Models, with significant improvements in coding agents and the emergence of personal AI assistants. This rapid progress has been driven by advancements in Reinforcement Learning from Verifiable Rewards, leading to better code quality and more efficient coding processes. The November 2025 inflection point marked a critical period for LLMs, especially in coding, with models like Claude Sonnet 4.5, GPT-5.1, and Gemini 3 showcasing their capabilities.

## What happened The past six months have been marked by intense competition among the big providers, with each releasing new models that surpass the previous ones in terms of capabilities. The supposedly "best" model changed hands five times between the three big providers, with Claude Sonnet 4.5 being overtaken by GPT-5.1, then Gemini 3, then GPT-5.1 Codex Max, and finally Anthropic taking the crown back with Claude Opus 4.5. The coding agents got good, crossing a quality barrier where they could be used as a daily driver to get real work done without needing to spend most of the time fixing their mistakes. ## Why it matters The improvements in LLMs and coding agents have significant implications for the development community, enabling more efficient coding processes and higher quality code. The emergence of personal AI assistants, such as Claws, has also opened up new possibilities for developers, allowing them to automate tasks and focus on more complex problems. However, there are also concerns about the potential risks and limitations of these advancements, including the need for careful evaluation and responsible use. ## How to think about it When considering the advancements in LLMs and coding agents, it's essential to think critically about their capabilities and limitations. Developers should evaluate these tools based on their specific needs and goals, considering factors such as coding efficiency, code quality, and automation capabilities. By adopting a thoughtful and nuanced approach, developers can harness the potential of these advancements to improve their workflows and outcomes. ## FAQ