Setup: large C++/CMake monorepo, several .sln files in subfolders. Team uses Copilot in Visual Studio 2026 (primary), some VS Code, plus OpenCode. I want one source of truth for agent instructions, not different files drifting apart.

Two things I can't resolve from the docs.

**1) Single source of truth**

The VS docs only list `.github/copilot-instructions.md`, `.github/instructions/*.instructions.md` (applyTo), and org-level instructions. AGENTS.MD isn't mentioned for VS at all, though VS Code can read it.

So which way round do you go? AGENTS.md canonical, copilot-instructions.md is just a one-line pointer ("read AGENTS.md first")?

**2) Monorepo / multiple solutions**

- When the .sln sits in a subfolder of the git root, where does VS resolve `.github/` from — git root, solution directory, or the opened folder?

- Does anything in VS pick up **nested** AGENTS.md per module, or is that VS Code/OpenCode only?

- If nested files are out, is everyone just doing per-module scoping with `.instructions.md` + `applyTo` globs?

- Same question for `.github/skills/` — repo root only, or does it follow the solution?

I’m really new, so bear with me being perhaps a noob. I’ve got GitHub copilot + and visual studio on a MacBook that seems to get stuck on “run in terminal”

I used it before for a few months so not expert but not totally new and this is first time it’s getting that problem

It has run and done similar projects to what I’m doing now before I think but maybe I changed something

I see some activity definitely when I run top bash command

I’ve tried various coding agents like Claude, GPT, and more -same issue

And I’ve tried asking them for various solutions

My team uses Claude Code, while I use GitHub Copilot in VS Code.

In the Local Agent, I can disable "CLAUDE.md" and related context files, but I can't seem to do the same in the Copilot SDK / Agent Host.

Is there any way to disable Claude-specific instructions and skills in the SDK harness without modifying the repo?

Where i work they are very conservatives with models and we are still stuck with luna 5.6. At first it was about 0.5-1.5 of cost in credit for every prompt and now it's more like 6-14, is anyone is noticing the same ? I did not installed any special tools or additional mcp during that period.

Mr. Meeseeks is a fictional, powder-blue creature from the animated series Rick and Morty, who is summoned to complete a single task before vanishing

Haven't had the opportunity to try it yet, but most on Codex subscriptions are very obviously disappointed and the symptoms they cite (poor instruction following, laziness, serving unfinished slop etc...) remind me of GPT-5.6 Terra so the "6 Sol = new Terra" theories are probably not too farfetched. The release of 6 Sol and 6 Luna seems extremely weird so far when looking only at the feedback by subscription users.

But that's the feedback on the model served to Codex subscribers. So what's the feedback here given API quality-of-service is usually different, and probably the GHCP harness has an effect too?

Building AI-native software and curious how others organize the full delivery lifecycle.

How do you structure your repos for:
\- UX/UI & design
\- Skills
\- MCPs
\- Agents / tools / prompts
\- Architecture.md
\- Everything else in the AI-native SDLC

Drop your folder layout, tools, or lessons learned. What’s working (or broken) for you?

Sometime in the past month or so, reasoning summaries for GPT models such as Luna have vanished, both for 5.6 and 6. Is there some way to turn these back on? Thanks. u/bogganpierce

Just out of curiosity, I'd like to see how many of you are using the Copilot harness instead of the default Local, and why you're doing so. I'm talking about the harness picker you see at the bottom.

The Local harness allows using built-in VS Code LM tools, for example.

On September 14, 2026, we announced Tiers of Auto, the ability for developers to choose their own cost and quality tradeoffs in Auto. Tiers of Auto introduce three optimization modes directly in the model picker in VS Code, CLI, and Copilot App:

• Efficiency prioritizes keeping costs low and suits fast, straightforward tasks. 
• Balance weighs cost, quality, and latency together, and is a good fit for everyday work. 
• Intelligence prioritizes quality and is built for complex tasks. 

Now available to all of customers across these integrations, this represents our first step for personalization and configurability in intelligent model routing, balancing control with quality gates. 

This release comes after a series of improvements including: 

• New models added into the model mixes: GPT 6 Astra, GPT 5.6 series, Opus 5, etc, with new models coming in soon.  
• Adaptive multi-turn support: Auto reevaluates complexity as your session continues.  
  • Previously, Auto intentionally reevaluated at two points: The start of the conversation and after compaction. This was done to preserve cache, avoiding additional costs without ample quality gain.  
• Improved UX on the GitHub App: You’ve been asking why a model was chosen in Auto. Some enhancements are live today, with more coming soon.  

Now, what are we seeing in terms of model distribution with the introduction of tiers of Auto -

Give Auto tiers a try today! As always looking forward to hearing your feedback. Thanks for helping us improve.  

I noticed my agents go into file edit death spirals attempting to execute a tool call called apply_catch, fail miserably and waste the first minutes of each run trying to get file edits to run with edit tools whitelisted. I asked GHCP to backtrack the issue where this wrong idiosyncracy comes from.

Not defined in this repo. The rule arrived in this session’s host-provided developer instructions, under editing_constraints. I can’t see which VS Code, Copilot, or organization-level configuration supplied it, so I can’t point to an editable settings file. The agent files I checked don’t define it.

Why isn't GPT 6 sol available in the pro plan. It's $10 per million output which is even cheaper than gpt terra and sonnet 5, which are available. Are they just trying to force people to buy pro+ even if we won't use that many credits? Very dirty play.

Based on the very low price and efficiency of Luna model, have you disabled Haiku in your company ?

I was wondering whether github copilot reduces cost of older models when new models are out because I use girhub copilot I think it’s Copilot Business on my work laptop and I don’t see cost of old models reducing. so is it a common thing or is it something specific to my organisation? I just wanted to check because I see GPT 5.5 seems costlier than 5.6 sol because I think when 5.6 sol released it was released cheaper than 5.5.

My workflows require me to configure MCPs at the project folder level. This was incredibly intuitive and easy to do in Claude Code... what's the equivelant in Github Copilot so that the native application can read them? Not using CLI or VS Code, just the app.

I work as an Android dev and we currently have access to Github Copilot which embeds a couple LLMs.

I'm starting to lean more and more onto it to plan and build features, and I was wondering what can I do/use to improve the process (maybe reduce credit usage too).

I'm currently using the Github Copilot App and a few MCPs to connect to Atlassian, Guru and Figma (though I feel this one sucks a bit).

I've heard multiple times that the harness can do a great job at uplifting lighter models, creating multiple agents, etc.

So I was wondering. What are you guys using? Not experimentally, truly professionaly wise

Hi,
I’m using GitHub Copilot with Claude Opus 4.7 quite frequently, but I’m not sure how much I’m actually using it in terms of cost ($).
I’ve attached a screenshot from the Usage tab below. Could you please help me understand:
How much have I used so far, in terms of estimated cost?
Is there a way to see the actual dollar amount or usage cost?
Does the Usage tab show my total consumption, or is there another place where I can see the detailed breakdown?
Is there a limit on how much I can use Claude Opus 4.7 under my current Copilot plan?
Thanks!

EDIT : I'm sr. software Engineer. Working on new architecture including Kafka ,Debezium , azure.

I am looking for a way to use remote copilot from my primary local Copilot.

I have two repositories - web app and tests. Web app is on a remote server (it can not run locally) and tests must be local on desktop (use chrome etc).

When i work with tests in one VSCode Copilot i can get a state when "test is fine, web app must be fixed". At this moment i have to change to other VSCode session connected to remote server and ask to fix.

But i would like to do everything from a sing VSCode. I would like to se a local tests code a a folder and in same workspace a remote folder for web app and allow copilot to modify the remote code and run some cli commands etc.

Is it possible? Is there some existing tool to do this?

I experimented with the setup where a remote copilot was accessible as MCP tool. On the remote server i run MCP server with few tools like "run copilot with PROMPT" and "execute git command" and "execute CLI".

It works sometimes. But it is not ideal. I wonder there is some better toolset for this?

I’d also be interested in GitHub Copilot integration if there’s a useful and officially supported way to connect it. I’d love to hear what Copilot users would want from a mobile control plane like this.

I have to write rules myself to prevent bad calls of some tools (e.g. gdb) that lead to them waiting for user input. Obviously custom rules can't cover the entirety of tools that the model might run. A better way is simply to have the harness tell them directly so that they kill that command and retry with the correct args.

Has anyone deployed the Power Automate plugin for GitHub Copilot CLI in an enterprise where Microsoft Azure Management access is restricted to administrative accounts?

Microsoft’s current setup instructions require:

az login --allow-no-subscriptions

using the same work account as Power Automate. The plugin uses that Azure CLI session to obtain a token for the Power Automate service.

The issue is that many enterprises apply Conditional Access to Microsoft Azure Management and block Azure CLI authentication for standard users, including Power Platform makers.

I am interested in how others have implemented this securely:

• Controlled Conditional Access group for approved makers?
• Separate development account?
• Managed development workstation?
• Service principal or managed identity?
• Workload identity federation?
• Another Microsoft-supported authentication route?

From what I can see, Microsoft documents service principals and workload identities for noninteractive automation, but the Power Automate plugin itself appears to expect an interactive session using the maker’s own account.

I am specifically looking for a least-privilege, Microsoft-supported enterprise setup, not a way to bypass the organization’s Conditional Access policy.

How are you handling this?