[1.18] docs(agents): announce v1.0 release for dapr agents in docs (#5120)

* docs(agents): announce v1.0 release for dapr agents in docs

Signed-off-by: Samantha Coyle <sam@diagrid.io>

* style: updates for copilot feedback

Signed-off-by: Samantha Coyle <sam@diagrid.io>

* style: address feedback from mark

Signed-off-by: Samantha Coyle <sam@diagrid.io>

---------

Signed-off-by: Samantha Coyle <sam@diagrid.io>

Author: sicoyle

daprdocs/content/en/developing-ai/dapr-agents/_index.md

@@ -3,14 +3,18 @@ type: docs
 title: "Dapr Agents"
 linkTitle: "Dapr Agents"
 weight: 25
-description: "A framework for building durable and resilient AI agent systems at scale"
+description: "A production-ready framework for building durable and resilient AI agent systems at scale"
 aliases:
   - /developing-applications/dapr-agents
 ---
 
 ![Concepts Agents](/images/dapr-agents/agents-blue.png)
 
+{{% alert title="Dapr Agents v1.0 — Generally Available" color="primary" %}}
+Dapr Agents is **v1.0** and production ready. The framework provides stable APIs, enterprise-grade reliability, and support for building and operating LLM-powered agentic systems at scale.
+{{% /alert %}}
+
 ###  What is Dapr Agents?
 
 Dapr Agents is a Python framework for building LLM-powered autonomous agentic applications using Dapr's distributed systems capabilities. It provides tools for creating AI agents that can execute durable tasks, make decisions, and collaborate through workflows, while leveraging Dapr's state management, messaging, and observability features for reliable execution at scale.
- 
+ 

daprdocs/content/en/developing-ai/dapr-agents/dapr-agents-introduction.md

@@ -10,6 +10,9 @@ aliases:
 
 ![Agent Overview](/images/dapr-agents/concepts-agents-overview.png)
 
+{{% alert title="Dapr Agents v1.0 — Generally Available" color="primary" %}}
+Dapr Agents **v1.0** is production ready with stable APIs and enterprise-grade support for agentic workloads.
+{{% /alert %}}
 
 Dapr Agents is a developer framework for building durable and resilient AI agent systems powered by Large Language Models (LLMs). Built on the battle-tested Dapr project, it enables developers to create autonomous systems that have identity, reason through problems, make dynamic decisions, and collaborate seamlessly. It includes built-in observability and stateful workflow execution to ensure agentic workflows complete successfully, regardless of complexity. Whether you're developing single-agent applications or complex multi-agent workflows, Dapr Agents provides the infrastructure for intelligent, adaptive systems that scale across environments.
 
@@ -89,4 +92,4 @@ These capabilities enable teams to monitor agent performance, secure multi-agent
 
 Whether you're interested in enhancing the framework, adding new integrations, or improving documentation, we welcome contributions from the community.
 
-For development setup and guidelines, see our [Contributor Guide]({{% ref "contributing/dapr-agents.md" %}}).
+For development setup and guidelines, see our [Contributor Guide]({{% ref "contributing/dapr-agents.md" %}}).

daprdocs/content/en/developing-ai/dapr-agents/dapr-agents-why.md

@@ -8,7 +8,7 @@ aliases:
   - /developing-applications/dapr-agents/dapr-agents-why
 ---
 
-Dapr Agents is an open-source framework for building and orchestrating LLM-based autonomous agents that leverages Dapr's proven distributed systems foundation. Unlike other agentic frameworks that require developers to build infrastructure from scratch, Dapr Agents enables teams to focus on agent intelligence by providing enterprise-grade scalability, state management, and messaging capabilities out of the box. This approach eliminates the complexity of recreating distributed system fundamentals while delivering agentic workflows powered by Dapr.
+Dapr Agents is a production-ready, open-source framework (v1.0) for building and orchestrating LLM-based autonomous agents that leverages Dapr's proven distributed systems foundation. Unlike other agentic frameworks that require developers to build infrastructure from scratch, Dapr Agents enables teams to focus on agent intelligence by providing enterprise-grade scalability, state management, and messaging capabilities out of the box. This approach eliminates the complexity of recreating distributed system fundamentals while delivering agentic workflows powered by Dapr.
 
 ### Challenges with Existing Frameworks
 
@@ -134,4 +134,4 @@ By building on Dapr, platform and infrastructure teams can apply Dapr's [resilie
 
 ### Vendor-Neutral and Open Source
 
-As part of the **CNCF**, Dapr Agents is vendor-neutral, eliminating concerns about lock-in, intellectual property risks, or proprietary restrictions. Organizations gain full flexibility and control over their AI applications using open-source software they can audit and contribute to.
+As part of the **CNCF**, Dapr Agents is vendor-neutral, eliminating concerns about lock-in, intellectual property risks, or proprietary restrictions. Organizations gain full flexibility and control over their AI applications using open-source software they can audit and contribute to.