February 2026: Delivered cross‑platform Reinforcement Fine‑Tuning (RFT) capability in aws-samples/amazon-bedrock-samples, establishing a unified workflow across OpenAI‑compatible APIs and AWS Bedrock. Implemented end‑to‑end notebooks and infrastructure support (Lambda setup and IAM roles) to enable GSM8K-targeted RFT experiments on OpenAI‑compatible models. Introduced and stabilized GPT OSS 20B and Qwen RFT examples, with integrated training/validation data and benchmarking hooks. Refined configuration, removed hardcoded regions, and consolidated shared datasets to improve reproducibility and maintainability. Moved training data to shared datasets, cleaned up imports, and addressed reviewer comments to boost notebook reliability. These deliverables enable faster experimentation, repeatable results, and scalable RL fine‑tuning with Bedrock, delivering higher quality models at lower cost.

July 2025 monthly work summary for awslabs/amazon-bedrock-agentcore-samples. This period focused on delivering core integration features with AWS Bedrock AgentCore, plus targeted notebook and documentation improvements. Key features and fixes delivered across Strands, AutoGen, LangGraph, and ADK integrations, along with robust cleanup to improve maintainability and deployment readiness. Result: faster onboarding for developers, expanded agent capabilities, and clearer guidance for managed agent deployment.