We also introduce an agentic streaming inference framework that supports thousand-second-scale generation while mitigating drift.

what changed after the December 2025 model inflection , and why "spec to pull request" is now becoming a real production workflow.

Progress is saved as the run goes, so a job that's interrupted picks up where it left off instead of starting over. Because the coordination happens outside the conversation, the plan stays on track no matter how big the task gets.

Weirdly though, those things have started to blur for me already, which is quite upsetting.

Weirdly though, those things have started to blur for me already, which is quite upsetting. I thought we had a very clear delineation where vibe coding is the thing where you're not looking at the code at all. You might not even know how to program. You might be a non-programmer who asks for a thing, and gets a thing, and if the thing works, then great! And if it doesn't, you tell it that it doesn't work and cross your fingers.

LLMs accelerate the wrong part

the more you rely on AI to write code, the less you're able to oversee what the AI writes

The model kept finding better approaches the longer it ran, which connects directly to the long horizon behavior that makes agentic models actually useful in production.

If ChatGPT was the moment consumers discovered AI could talk, OpenClaw may be the moment they discovered AI could act.

Agentic AI is increasingly judged not by fluent output alone but by whether it can act, remember, and verify under partial observability, delay, and strategic observation.