diff --git a/README.md b/README.md
index df8f42f5c43..8e803d31af8 100644
--- a/README.md
+++ b/README.md
@@ -19,11 +19,9 @@
 
 ## 🎉 What's New
 
-> **✨ OpenAI GPT OSS Support**: TRL now fully supports fine-tuning the latest [OpenAI GPT OSS models](https://huggingface.co/collections/openai/gpt-oss-68911959590a1634ba11c7a4)! Check out the:
->
-> - [OpenAI Cookbook](https://cookbook.openai.com/articles/gpt-oss/fine-tune-transfomers)
-> - [GPT OSS recipes](https://github.com/huggingface/gpt-oss-recipes)
-> - [Our example script](https://github.com/huggingface/trl/blob/main/examples/scripts/sft_gpt_oss.py)
+**OpenEnv Integration:** TRL now supports **[OpenEnv](https://huggingface.co/blog/openenv)**, the open-source framework from Meta for defining, deploying, and interacting with environments in reinforcement learning and agentic workflows.
+
+Explore how to seamlessly integrate TRL with OpenEnv in our [dedicated documentation](openenv).
 
 ## Overview
 
diff --git a/docs/source/index.md b/docs/source/index.md
index 7b6fbfaa480..0bdc0d76040 100644
--- a/docs/source/index.md
+++ b/docs/source/index.md
@@ -7,10 +7,16 @@
 TRL is a full stack library where we provide a set of tools to train transformer language models with methods like Supervised Fine-Tuning (SFT), Group Relative Policy Optimization (GRPO), Direct Preference Optimization (DPO), Reward Modeling, and more.
 The library is integrated with 🤗 [transformers](https://github.com/huggingface/transformers).
 
-Below is the current list of TRL trainers, organized by method type (⚡️ = vLLM support; 🧪 = experimental).
+## 🎉 What's New
+
+**OpenEnv Integration:** TRL now supports **[OpenEnv](https://huggingface.co/blog/openenv)**, the open-source framework from Meta for defining, deploying, and interacting with environments in reinforcement learning and agentic workflows.
+
+Explore how to seamlessly integrate TRL with OpenEnv in our [dedicated documentation](openenv).
 
 ## Taxonomy
 
+Below is the current list of TRL trainers, organized by method type (⚡️ = vLLM support; 🧪 = experimental).
+
 <div style="display: flex; justify-content: space-between; width: 100%; gap: 2rem;">
 <div style="flex: 1; min-width: 0;">
 
@@ -47,14 +53,6 @@ Below is the current list of TRL trainers, organized by method type (⚡️ = vL
 </div>
 </div>
 
-## 🎉 What's New
-
-**OpenEnv Integration:** TRL now supports **[OpenEnv](https://huggingface.co/blog/openenv)**, the open-source framework from Meta for defining, deploying, and interacting with environments in reinforcement learning and agentic workflows.
-
-Explore how to seamlessly integrate TRL with OpenEnv in our [dedicated documentation](openenv).
-
-------------------
-
 You can also explore TRL-related models, datasets, and demos in the [TRL Hugging Face organization](https://huggingface.co/trl-lib).
 
 ## Learn