Meta is converting its entire internal operation, every tool, every workflow, every employee interaction, into a living laboratory for AI post-training.
Pre-training teaches an AI model how language works. Post-training teaches it how to be useful. Meta has decided that the best classroom for “useful” is the daily grind of roughly 70,000 employees spread across the globe.
Turning the office into a training gym
Meta is systematically instrumenting its internal tools and workflows so that every interaction an employee has with AI-powered systems generates feedback data. That data then flows back into improving the company’s foundational models, including its open-source Llama family.
In practical terms, when a Meta engineer uses an AI coding assistant and accepts, rejects, or modifies its suggestions, that signal becomes training signal. When a product manager asks an internal AI agent to summarize a document and then corrects the output, that correction feeds the loop. Scale that across tens of thousands of workers performing thousands of distinct tasks daily, and you have something that looks less like a tech company and more like a purpose-built post-training environment.
