Four Trust States Built to Stop LLM Agents From Getting It Wrong
This shipped quietly last week. A trust layer system for LLM outputs, four states, MIT license on GitHub. The person […]
This shipped quietly last week. A trust layer system for LLM outputs, four states, MIT license on GitHub. The person […]
Empty isn’t always broken. Sometimes it’s the most deliberate thing you can send. A developer ran an experiment with 11
Quick summary: a psychology grad built a Bayesian reasoning prompt that forces ChatGPT to hold multiple competing solution paths open
Four months of documented research just dropped, and the model ranking at the end is going to start some arguments.
Here’s the premise: one tiny system prompt occasionally swaps the word “which” with “witch” so you can never fully trust
Most people blame the model when AI debugging goes sideways. Wrong diagnosis. The model isn’t the problem. The context is.
TL;DR: A Reddit user posted a structured AI prompt that finds, packages, and launches a digital product idea. They say
Anthropic is laying out how AI agents could move from helping with biology research to actively driving parts of it.
Amazon just plugged AI into its print-on-demand business. The company is rolling out AI-generated custom designs through Alexa for Shopping,