u/jukasper

What are they? A dynamic workflow is a program that defines how a task is carried out. It can combine automated steps with the work of one or more agents. Steps can run one after another, in parallel, or as a mixture of both.

Where they help most: complex, multi-step tasks, or anything you want to repeat the same way every time. For example, when investigating an outage, a workflow can collect logs and telemetry, have separate agents analyze different systems, and merge their findings into a timeline and root-cause report.

This started as something we used internally, and we're excited to finally get it into your hands.

Docs and changelog

Give it a try and let us know what you think!

HydraFusion is now available in Visual Studio Code and the GitHub Copilot app, expanding beyond Copilot CLI.

What’s improved

Bringing HydraFusion to more surfaces was the top request from early feedback. This release also improves the overall experience:

• Greater transparency: See more clearly what HydraFusion is doing at each step of a workflow.
• Real-time progress: HydraFusion now sends more frequent progress updates while it works.
• Clearer status during long tasks: Progress updates make it easier to tell that HydraFusion is still working, even when a task takes longer.

Let us know what you think!

https://github.blog/changelog/2026-09-30-hydrafusion-in-vs-code-and-the-github-copilot-app/

We are excited to introduce Project HydraFusion, a research preview that delivers frontier intelligence through runtime orchestration. It creates a full execution plan, choosing from models across multiple providers to draft, critique and revise, or cascade to more powerful models to complete your task.

Check out this blog post to learn more about HydraFusion.

Most importantly, let us know what you think!

To try HydraFusion in Copilot CLI:

1. Run /update to install the latest version
2. Run /experimental on
3. Run /model, then select HydraFusion (Research Preview)

Please post feedback in here.

The VS code team just published a deep dive blog post on the Agent Host, the dedicated process that now owns agent sessions in VS Code.
The post covers:

• Why we are moving agent sessions out of the extension host
• Adopting the GitHub Copilot SDK for the Copilot harness, so behavior is consistent across VS Code, Copilot CLI, and the Copilot app
• How one live session stays in sync across the editor, the Agents window, and even a browser
• Running the host on a remote machine
• Supporting multiple harnesses without flattening what makes each one distinct
• AHP, the open protocol behind it and how anyone can build their own client

Check it out

Feedback, questions are more than welcome! Let us know what you think

Following OpenAI’s latest pricing announcement, we are excited to share that we have updated our pricing accordingly. 

What does this mean based on the announcement we had yesterday "GPT-5.6 Sol is 50% cheaper until September 3 in GitHub Copilot"

• The 50% promotional discount will apply to the newly reduced price through September 3 - giving customers the benefit of both reductions.

Links:

• ⁠Documentation

Kimi K3, an open-weight model, is now generally available in GitHub Copilot. The model shows frontier-level abilities on agentic coding with highly cost-effective pricing.

Changelog

We're sharing an early look at how MAI-Code-1-Flash performs in production and what the data suggests about coding quality and token efficiency in real developer workflows.

Check out our blog post and let us know what you think!

We are continously looking for feedback on MAI-Code-1-Flash and we'd love your opinion. A few quick things we're curious about:

• How's it working for you overall?
• What's it great at, and what could be better?

Drop your thoughts below 👇 . Thanks!

We A/B tested different system prompts for GPT-5.5 in VS Code, and just changing the prompt made it faster and more token-efficient.

We figured this was worth sharing because we don't think people realize how much work continues after a model launches. Launch day isn't the finish line and our engineering teams keep iterating on prompts, validating changes, and improving things behind the scenes.

Check it out: https://code.visualstudio.com/blogs/2026/07/06/optimizing-vscode-coding-harness-model-providers

Previously available only on individual plans, it's now ready for teams at scale.

Built for coding and optimized for GitHub Copilot, MAI-Code-1-Flash delivers fast, low-latency responses. Making it well-suited for high-volume, iterative agentic coding workflows where speed and efficiency matter most.

Read the changelog

Over the last 6 months we ran a very simple say_hello task (part of our internal vscbench benchmark suite) over 50k times, and we wanted to share some insights we got from the data. It was super interesting to us how differently models approach even the simplest tasks.

Read the full post here

Let us know what you think :)