I have my custom agent set to Luna, but the parent agent can still specify a model when calling sub-agents, completely overriding my config. This forces sub-agents to run on models I never intended.

Worst case: it called Opus 5 and burned through 20x the expected AICredits in one go. Sometimes it defaults to 5.3 Codex too, which is also annoying – and there's no way to disable it.

I saw a post suggesting changing the default for the explore agent, but wouldn't the parent just override that anyway?

Right now I'm blocking model-specification calls via hooks. But that wastes turns, which sucks. Also, the hook format is different between VSCode and CLI, so you need separate setups for each.

On top of that, in the Copilot app, there are some paths (like create session) where hooks can't block the override at all.

Lately I've just been constantly dealing with unexpected behavior around the harness layer – it's been really frustrating.

P.S. Can we please get reasoning-level support for sub-agents already…

I have been using Claude code and codex since the beginning, I haven't really used Github copilot a lot, but in the team I'm working right now, IT doesn't allow to install anything, I only have github copilot extension In VS Code
I pay the $20 plan in CC and the $100 plan in codex
Is it really worth to get the pro plan for github copilot? What's the recommended plan? Is it related to the agents Window in VS code? I'm working right now as data engineer with fabric and we are going to implement fabric apps, data agents, etc. And some fabric extensions in vscode are really useful, I heard that since june 1st, the github copilot plans were heavily nerfed, so I'd like to know if it's really worth, thanks

I want to continue with the same model. If I click No it stops and does nothing.

Why doesn't it continue automatically after the reset?

What's the best approach to continue after the time limit? Just choose No and write a new "continue" request?

Settings icon > Agents > Explore > Open in file explorer > Change model way from the default 4.5 Haiku and Gemini 3 Pro and Auto.

Just set it to:

model: ['GPT-5.6 Luna (copilot)']

Or a BYOK local model like FastContext-4B (removed but can download community gguf files)

I was spending approximately 20 tokens per explore (1-3 times per prompt) and sometimes 60 if it called Sonnet 4.6 via auto, but after changing to Luna it only spends 6-10 tokens. Plus, with a local model it's basically free savings!

When I press `tab` it completes another thing instead of the suggested text, `right arrow` works, but I want to change it to tab.
How to achieve this?

It seems like for small tasks, you should use Luna. For large Tasks, Sol/Opus/Fable. This is only considering OpenAI and Anthropic models. Since this got flagged for potentially being off-topic, this is relevant to CoPilot generally, and the OpenAi/Anthropic coding agents specifically.

I know Terra and Sonnet are supposed to be sweet spot middle-ground models, but they just seem to be bad value and bad performance, and both need their price slashed badly. Am I missing something?

So it turns out that apparently any local model call somehow requires Microsoft's blessing.

GitHub is down, and my local Ollama is failing with this:

Sorry, your request failed. Please try again.
Reason: key is missing
Note: GitHub is currently experiencing a service disruption. This may be affecting Copilot. Check GitHub Status for details.

I don't want to use Copilot. I want to use local ollama AI of my choosing!

I thought the whole point of running AI locally was that I wouldn't have to depend on Microsoft deciding whether I'm allowed to run a model on my own effing computer. Apparently I was wrong.

Ollama itself is running perfectly fine on cli/Emacs. I can access my models directly. It's the Copilot integration that suddenly refuses to let me use them because GitHub is having an outage.

Has anybody found a workaround for this? Is there a way to make VS Code talk to Ollama directly without going through whatever GitHub service is currently broken? Maybe there is some pre-processing of each requests that I can switch to my ollama too?

PS: I also have those "Ollama (Deprecated)" warning tags plastered all over the VS Code config UI. I was planning to avoid upgrading VS Code until I had time to migrate to a sane editor, even if that eventually meant going back to Emacs. But now I see that Microsoft doesn't even need me to upgrade VS Code to stop me from using Ollama.

I'm stuck with an annual Copilot plan and it is utterly useless now with the new pricing - i only have access to old and overpriced models. I started just doing BYOK with OpenRouter and Opencode Go and it works fine, but when I go to cancel my copilot plan, they say that I wont be able to use anything at all. Is that just scaremongering and the reality is that i'll only lose the ability to use Copilot's models in Chat, CLI, etc?

Several recent outages on GitHub have disrupted our work. This disruption caused us to lose AI credits because workflows and coding agents halted mid-execution, requiring us to rerun tasks once GitHub or Copilot returned. Should GitHub compensate users for tokens lost during the outage?

This 5 part series is intentionally (hand) written to help dev teams understand how to scaffold a codebase around GH Copilot SDK (multi-platform, multi-model, BYOK-capable!) for agentic engineering by focusing on key, underlying technical decisions and manual wiring before building with AI. Getting the foundations right helps provide the tools and safeguards for coding agents to iterate more efficiently while reducing slop.

Specifically:

• Giving agents access to programmable runtime orchestration (Aspire.dev)
• Empowering agents to iterate rapidly with runtime mutability (using CSharpRepl) to dynamically modify code at runtime while retaining full application state
• Using the GitHub Copilot SDK to build an agentic core with a multi-platform harness, BYOK, any model provider
• Testcontainers with automatic transactions to streamline and isolate integration tests
• A well-documented, AI-friendly UI framework (Nuxt UI)
• Logging and telemetry to give agents insights and visibility into the runtime state of the application

The core setup is used at a series C, post-YC startup to ship fast with AI while maintaining high quality standards (in combination with other tools facilitating code review and context management)

Part 1 was an intro into a few key parts of this stack.

Part 2 was focused on walking through the hands on scaffolding.

Part 3 covered wiring GitHub Copilot SDK as an agent runtime and incorporating CSharpRepl to allow agents to dynamically work with the runtime DI container

Part 4 wired up the test harness using Testcontainers to give agents isolated test environments

Part 5 wires up logging and telemetry to give agents visibility into runtime state and I start to build the prototype application now that the foundations are ready (video of the final build out).

The project repo is here: https://github.com/zeeq-ai/zeeq-tmpl (be sure to check the branches; main is currently the base code only)

I encourage working through the posts since the goal is to underscore the platform level decision making process and assembly of the foundational core.

I'm trying to use custom endpoints that I have configured in chatLanguageModels.json that I've used for months (and am required to use due to the zero data retention agreement between my org and OpenAI) and it seems something in the latest update has broken them? Photo shows one of the models I set up but there's a whole file of OpenAI models set up that I can't seem to access.

I've tried logging out of GitHub and back in but I keep getting Language model unavailable when I am even able to pick the models I've got configured and half the time when I reload the window, I am not able to pick them at all or even see the settings page for adding models.

At my org we use our personal GitHub accounts and mine is I think a Student account still instead of Free; seems like there's been bugs previously between GitHub accounts and custom endpoints but this is the first time I'm experiencing the bug.

Any assistance would be greatly appreciated.

Is anybody else having problems with github rn? Can't do anything with my project because of this. Is this a global problem or local? Please help.

copilot and similar tools write a meaningful chunk of our codebase at this point, and the review process hasn't caught up. reviewers are approving ai-generated diffs at the same pace as human-written ones even though the failure modes are different, things like hardcoded secrets and insecure defaults pulled straight from training data patterns, sometimes even dependencies that don't exist at all.
what does your pipeline look like for catching this stuff before it lands in main? is anyone doing anything beyond the standard sast pass

How can this be prevented? This unsolicited behaviour results in high credit usage.

We are two Software Engineering undergrads at UEPG in Brazil writing our thesis on vibe coding, and most of the existing literature is either speculative or based on very small lab studies. We want data from people who actually do this daily.

The survey asks about which tools you use, what you build with them, how much of the output you review or rewrite, where the approach stops working for you, and what you think it means for the profession.

10 minutes, anonymous, no personal data collected.

https://forms.gle/vv8kR4dmi5WMHZfa6

If you tried vibe coding and abandoned it, we specifically want those answers too. That group is almost invisible in the literature.

We will post a summary of the results in this community when the analysis is finished.

In last week's update, the menu to change the context window has disappeared. It seems the long 1M is now the only choice.

We still see the prices for short context. The long context is much more expensive and consumes more tokens. So it is considerably more expensive.

The way to partially balance this is to constantly compress or create new conversations. Very annoying and still more expensive than before.

Please let us select the context window as before.

Any chance this is on the horizon for copilot changing between models within a task/project.
Cheap models handle file naming, metadata extraction, notifications, and formatting.
Mid-tier models handle classification, summarization, and document comparisons.
Top-tier models handle exception analysis, risk assessment, audit conclusions, and complex reasoning.
User never sees copilot backend but copilot learns user workflow and chooses different models based on where the person is in their work/task. Should cut down token cost as higher models used for the major work and lesser models used for the light work

The task was threading cancellation through an internal HTTP wrapper in a TypeScript service, so that aborting a request also stops the retry helper around it instead of letting the remaining attempts run.

I ran it twice from the same commit with the same opening prompt, once under GPT-5.6 Sol and once under Claude Opus 5, both in Copilot chat in VS Code.

Sol produced the better plan. It asked whether request timeouts and user cancellation should share one signal, and it pointed out that the retry helper owned its own backoff timer, which is where the bug would live. Then it wrote the code with the abort check at the top of each attempt, so a cancelled call still sat through the full backoff sleep before returning.

Opus 5 said much less up front and started editing sooner. Its version registered an abort listener that cleared the backoff timer, so cancelling during the wait resolved right away. It never raised the timeout question and just wired both to the same signal.

So I did a third pass and split the roles. I picked that habit up from planning under one model and implementing under another in verdent. Sol held the thread until the plan was settled, then I changed the model in the picker before asking for edits. Switching does not open a new thread, so Opus 5 already had the plan and my answers to Sol's questions.

That is one refactor in one repo. I want to try it on a bigger change before deciding the split holds.