RLHF taught a model to answer one question well. Agentic RL asks a harder thing: take fifty actions in a live environment, most of them invisible in the final reward, and still learn which ones mattered. That single change, from …
Before MCP, connecting five agents to twenty tools meant writing a hundred bespoke adapters. A protocol turns that multiplication into an addition, and the math is the whole story.
Fifty-seven percent of organizations now run AI agents in production, yet quality remains the top deployment barrier. This is the field guide for the engineers shipping those systems: frameworks compared, patterns catalogued, fai…
Language models generate text one token at a time by sampling from a probability distribution over their entire vocabulary. Constrained decoding intervenes at that sampling step, masking out every token that would violate a targe…
A frontier model can write a function. An agentic runtime can read a codebase, plan a migration, edit forty files, run the tests, fix what broke, and open a pull request. The difference is not intelligence; it is the system that …