Build long-horizon agents with Grok 4.7 on Amazon Bedrock
AWS demonstrates how to build and evaluate a tool-calling agent using Grok 4.7 on Amazon Bedrock, comparing four reasoning effort levels across three synthetic tasks. The agent answered 67 of 72 runs correctly; xhigh achieved 18 of 18, while low achieved 15 of 18 using about an eighth of the output tokens. The guide covers task design, automated grading, production monitoring, and operational controls, noting that these small-scale results are indicative rather than statistically conclusive.
Why it matters: Tasks with provably unique answers and repeated runs provide a reusable way to compare reasoning effort, while separate correctness and token measurements make the trade-off concrete.

