Capturing token IDs during agentic interactions for better reinforcement learning
Amazon just solved a hidden problem in agent training: token-level visibility. Most teams are flying blind.
Why it matters
Amazon Science's Turnstile proxy enables fine-grained reinforcement learning on agentic systems by capturing token IDs lost in text-only logs. This addresses a critical gap in agent training methodology that affects model performance at scale.
The key facts
11 to knowAmazon Science introduces Turnstile, a Rust proxy for token ID capture
Designed to capture information lost in text transcripts during agentic interactions
Enables reinforcement learning at token level rather than transcript level
Sits between model backend and agent harness
Published by Amazon Science (credible, peer-facing research division)
New Rust proxy called Turnstile
Captures token IDs during agentic interactions
Designed to retain information lost in text-only transcripts
Focus on reinforcement learning optimization for agents
Published by Amazon Science
Published July 9, 2026
Go to the source
Amazon Scienceamazon.science
Publisher excerpt: A new Rust proxy called Turnstile sits between the model backend and the agent harness to capture information lost in mere text transcripts.