Remove accidental file from merge (#3715)

website/blog/2024-10-02-new-autogen-architecture-preview/index.mdx

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----
-title: New AutoGen Architecture Preview
-authors:
-  - autogen-team
-tags: [AutoGen]
----
-
-# New AutoGen Architecture Preview
-
-<center>
-
-![What are they doing?](img/robots.jpeg)
-
-</center>
-
-One year ago, we launched AutoGen, a programming framework designed to build
-agentic AI systems. The release of AutoGen sparked massive interest within the
-developer community. As an early release, it provided us with a unique
-opportunity to engage deeply with users, gather invaluable feedback, and learn
-from a diverse range of use cases and contributions. By listening and engaging
-with the community, we gained insights into what people were building or
-attempting to build, how they were approaching the creation of agentic systems,
-and where they were struggling. This experience was both humbling and
-enlightening, revealing significant opportunities for improvement in our initial
-design, especially for power users developing production-level applications with
-AutoGen.
-
-Through engagements with the community, we learned many lessons:
-
-- Developers value modular and reusable agents. For example, our built-in agents
-  that could be directly plugged in or easily customized for specific use cases
-  were particularly popular. At the same time, there was a desire for more
-  customizability, such as integrating custom agents built using other
-  programming languages or frameworks.
-- Chat-based agent-to-agent communication was an intuitive collaboration
-  pattern, making it easy for developers to get started and involve humans in
-  the loop. As developers began to employ agents in a wider range of scenarios,
-  they sought more flexibility in collaboration patterns. For instance,
-  developers wanted to build predictable, ordered workflows with agents, and to
-  integrate them with new user interfaces that are not chat-based.
-- Although it was easy for developers to get started with AutoGen, debugging and
-  scaling agent teams applications proved more challenging.
-- There were many opportunities for improving code quality.
-
-These learnings, along with many others from other agentic efforts across
-Microsoft, prompted us to take a step back and lay the groundwork for a new
-direction. A few months ago, we started dedicating time to distilling these
-learnings into a roadmap for the future of AutoGen. This led to the development
-of AutoGen 0.4, a complete redesign of the framework from the foundation up.
-AutoGen 0.4 embraces the actor model of computing to support distributed, highly
-scalable, event-driven agentic systems. This approach offers many advantages,
-such as:
-
-- **Composability**. Systems designed in this way are more composable, allowing
-  developers to bring their own agents implemented in different frameworks or
-  programming languages and to build more powerful systems using complex agentic
-  patterns.
-- **Flexibility**. It allows for the creation of both deterministic, ordered
-  workflows and event-driven or decentralized workflows, enabling customers to
-  bring their own orchestration or integrate with other systems more easily. It
-  also opens more opportunities for human-in-the-loop scenarios, both active and
-  reactive.
-- **Debugging and Observability**. Event-driven communication moves message delivery
-  away from agents to a centralized component, making it easier to observe and
-  debug their activities regardless of agent implementation.
-- **Scalability**. An event-based architecture enables distributed and
-  cloud-deployed agents, which is essential for building scalable AI services
-  and applications.
-
-Today, we are delighted to share our progress and invite everyone to collaborate
-with us and provide feedback to evolve AutoGen and help shape the future of
-multi-agent systems.
-
-As the first step, we are opening a [pull request](https://github.com/microsoft/autogen/pull/3600) into the main branch with the
-current state of development of 0.4. After approximately a week, we plan to
-merge this into main and continue development. There's still a lot left to do
-before 0.4 is ready for release though, so keep in mind this is a work in
-progress.
-
-Starting in AutoGen 0.4, the project will have three main libraries:
-
-- **Core** - the building blocks for an event-driven agentic system.
-- **AgentChat** - a task-driven, high-level API built with core, including group
-  chat, code execution, pre-built agents, and more. This is the most similar API
-  to AutoGen [0.2](https://github.com/microsoft/autogen/tree/0.2) and will be the easiest API to migrate to.
-- **Extensions** - implementations of core interfaces and third-party integrations
-  (e.g., Azure code executor and OpenAI model client).
-
-AutoGen [0.2](https://github.com/microsoft/autogen/tree/0.2) is still available, developed and maintained out of the [0.2 branch](https://github.com/microsoft/autogen/tree/0.2).
-For everyone looking for a stable version, we recommend continuing to use [0.2](https://github.com/microsoft/autogen/tree/0.2)
-for the time being. It can be installed using:
-
-```sh
-pip install autogen-agentchat~=0.2
-```
-
-This new package name was used to align with the new packages that will come with 0.4:
-`autogen-core`, `autogen-agentchat`, and `autogen-ext`.
-
-Lastly, we will be using [GitHub
-Discussion](https://github.com/microsoft/autogen/discussions) as the official
-community forum for the new version and, going forward, all discussions related
-to the AutoGen project. We look forward to meeting you there.