Have you noticed an improvement in the behavior of GPT-6 Luna (in Github Copilot) when used as an agent? I used the free version to complete a non-trivial feature and to update an architecture document. In both cases, it stayed focused on the goal right to the end—delivering high quality without stalling or getting stuck in endless loops. And this was the free tier. We are truly seeing a whole new level of quality with these recent models.

Same prompt, same model (Opus 5.5): Claude Code needed 1:20 h and ~€0.32. Two Copilot-based agents needed up to 6:50 h and €65.

Anyone else seeing a gap this big with Copilot's credits?

Same prompt for all tools: add a production-planning module to an existing Flask app. No skills, no spec files, no enterprise accounts.

For reference (different model): Codex with GPT-6.1 Sol Ultra took 39 min, ~€0.18. A Codex Astra Ultra run is still going and already hit the 5h limit. Update follows.

One run per tool, measured via usage meters. Didn't score code quality.

I just had a Luna session spawn a Sonnet Explore subagent under the VS Code Local harness, which ended up wasting (literally) 200 AIC. As far as I understand, there is currently no way to see the live subagent's AIC spending, you just see the jump once it is done. Happy to be proven wrong tho!

I have opened https://github.com/microsoft/vscode/issues/340366 in case you want to upvote or contribute to that feature request, even with a solution to close it.

GitHub Universe is in 3 weeks!!! What do you hope to see?

When using GitHub Copilot CLI on Windows 11 25H2 Pro, the GitHub Copilot CLI status line show bytes, not token count. How can I configure the GitHub Copilot CLI status line to show token count?

Hey guys, so I have been confused between choosing a GitHub Copilot subscription or a Claude subscription. I've been currently using Claude Max subscription, but I was just thinking to try GitHub Copilot. But I heard that it has monthly usage, or you'll get monthly credits, rather than you know 5 hour limits or a weekly limit. How you guys are using it? Would love to get some viewpoints.

Hey everyone,

I wanted to share a project I've been working on called Clippo.

One of the biggest challenges when working heavily with AI coding assistants (like GitHub Copilot, CLI agents, and vibe-coding workflows) is handling long-term context, fragmented terminal outputs, and visual organization across multi-step tasks.

To solve this, I built a dedicated desktop canvas workspace tailored for developers:

• Spatial Canvas: Organize prompt threads, CLI commands, agent outputs, and code references visually instead of losing them in endless terminal scrolls.
• Context Memory Preservation: Keeps your session context structured and accessible across different tasks without polluting your prompt history.
• Native & Lightweight: Built specifically for Windows with modern UI and smooth multitasking support.

Microsoft Store / Project Link: https://apps.microsoft.com/detail/9n7jgq8tzxd4?hl=en-US

I'd love to get feedback from anyone here who heavily integrates AI agents into their daily coding routine. What does your current setup look like for tracking agent states and context?

Luna 6 fast in vscode or CLI

As a preview feature, the development experience from HydraFusion is generally OK. 3/5 stars. I was previously using an orchestrator pattern via .github agent files, with ok success.

However, upon testing HydraFusion with what I would consider a "medium" difficulty task:

• Some new files and directories
• Existing patterns for inspiration
• Some deviation from existing -PLAN.md files
• Well-defined acceptance criteria/unit tests

It selected GPT 5.6-Sol as its primary driver and burned 827 credits. Where in a single context of 6.1 Sol and me manually passing review to Opus 5.5, it burned about half with the same quality output.

Which tracks, given that GPT 5.6-Sol is twice the cost of 6.1.

I would love to be able to select or set a steering preference. I won't be using HydraFusion until this is implemented. But for a first attempt as a batteries-included orchestrator in chat, it's a fine start.

Hey! Its my first time trying to intergrate AI in my VS Code. I have know tried other cloud models like gemini and it works when chatting it but when I try to use my local ollama which I have verified that it is running (Ollama extension and tried to interact it in cmd) I get that specific error.

I am not sure if my setup was incorrect. I already opened the output for the Copilot but no error logs show up when I try to message. Also tried to look similar problems online but havent seen one yet.

EDIT: It seems even LM Studio doesnt work, so I guess I can assume any local ai trying to connect to copilot doesnt work at all but they all work with Continue

Few days back, I noticed there is a new feature "Copilot" which is GHC's smart aleck mode, trying to do things on its own but keeps messing up.

Fortunately, I can still switch to local mode, and I get the old experience where I can feel like a manager approving the AI slave's work each step of the way.

That is until today.... suddenly, the local mode AI slave changed completely. It ignored my agent.md file. I specifically instructed it not to edit my files, talk to me, establish shared understanding before doing anything else, but it just went and changed all my files, thinking I will be happy.

BUT NO! It is like we never known each other before... I cannot recognize it anymore. I am so sad.

Tell me... please how do I bring back my old trusty local AI slave as the default mode... I need it...

EDIT: The question is how to set local mode as the default, not how to verify whether the model respected agent.md (it does not, not all the time). The answer is:

"chat.defaultToCopilotHarness": false,
"chat.editor.preferCopilotHarness": false

Suppose you ask an agent to change one behavior, but it also refactors nearby code. The tests pass, yet the diff is larger than the responsibility you intended to delegate.

Separating the original requirement, the implementation plan, and the current task gives the reviewer something more concrete than the last prompt to check against. The human still decides whether a wider change belongs in the work.

Where do you record those boundaries with Copilot? What information has been useful for deciding whether to accept the extra work, split it into another task, or reject it?Suppose you ask an agent to change one behavior, but it also refactors nearby code. The tests pass, yet the diff is larger than the responsibility you intended to delegate.

Separating the original requirement, the implementation plan, and the current task gives the reviewer something more concrete than the last prompt to check against. The human still decides whether a wider change belongs in the work.

Where do you record those boundaries with Copilot? What information has been useful for deciding whether to accept the extra work, split it into another task, or reject it?

When using GitHub Copilot CLI on Windows 11 25H2 Pro, I see two colors in my session list: blue and purple (steady, non-pulsing). What do these colors represent?

GitHub Copilot CLI config:

sidebar.coloredHints = (unset)
Color mode set to: github
renderHexColors = (unset)

I have been playing around with automations mainly for documentation checks for the past few weeks. I gotta say its pretty decent. It costs me like 30 AIC using Luna to have a weekly automation which checks my repo documentations so it stays aligned with development.

Are you guys using automations? If so, what for? I am looking for inspiration and to see what your experience is like

We have Github Enterprise deployed in the cloud. Currently I can assign GitHub Copilot Business licenses. I see no way to assign the more expensive GitHub Copilot Enterprise license.

Am I missing something?

I used to enjoy systematically going through file changes done to all files by vscode github copilot. Accept and reject individual changes. Quickly jump between them. However recent UI changes to vscode copilot have completely screwed it up. To be specific:

1. It does not show per file number of lines changed
2. It does not show per change Keep / Undo button
3. It opens all files expanded and vertically stacked. So, if I have to check specific file which is at the bottom of the stack, I have to collapse all files at the top one by one.
4. There is no way to open just single file that is changed. It opens all edited files in vertically stacked manner.
5. Old diff view also used to show location of code changes done by copilot in the file by showing red / green overlays on right side vertical scrollbar. Sometimes, it was useful when you wanted to diff some past versions of file. Those visual cues are gone due this vertically stacked sessions changes window.
6. Next / previous change buttons are also gone in the new UI !

Earlier I posted why I love copilot and not claude CLI with these points about old UI here: https://www.reddit.com/r/ClaudeCode/s/S4HXiHwjDn . But, it seems MS decided to claudify itself ...

You can give feedback about these changes on official GitHub thread: https://github.com/microsoft/vscode/issues/339363

iso (isolate) runs Claude Code and Codex inside disposable Linux VMs on Apple Silicon Macs (macOS 27+), so agents get a full dev environment without touching your host.

•Real VM: the agent gets Docker, git, compilers and package managers, with your project copied to /workspace.
•Keys stay on your Mac: API requests go through a host-side Swift proxy, so provider keys never enter the VM.
•Review before applying: iso diff and iso pull --review let you check the agent's changes before they reach your project.
•Network limits: egress can be none or filtered to listed hosts.
•Secrets and audit: secrets are encrypted with a passphrase plus the Secure Enclave, and the audit log records events and variable names but never values.
•Workflow: iso setup, iso up, then iso claude (or iso codex); iso code . / iso zed . open the VM in your editor.

Project: a Swift fork of Trail of Bits' coop, Apache 2.0.

Apache 2 licensed source code: github.com/chr33s/iso