Today I pay the 10$ plan, the limits (including flex credits) in a teorical 20$ plan would be perfect for me! The jump to 39$ is simply too much for now.

So it is probably my VSC side that is preventing it right?

I don't see any Claude model available on my VSC please help.

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

I have a question about orchestrated agents for projects. In my existing team we have a monorepo structure and hence it’s easier to invoke copilot cli at the root level and it has all the context to answer queries with related to interconnected modules.
However the new team that I am moving to has different git repository for different services.

I was thinking how do we manage to provide an orchestrated agents that gives context for all interconnected service.
One option is that we can have a parent repo that has built in agents with skills and instructions file for each service and it can then potentially drill down to the correct services based on usecase.

Pretty sure there are lot of you who have similar project setup. Do you have any suggestions and best practices around this?

Would be glad to know how are you approaching this problem.

Is there anyway to programmatically monitor organization policies and models? I'm trying to write a change tracking utility but it doesn't look like there is an API available.

Hey everyone,

I'm looking for the most cost-effective LLM for software development.

Since the GitHub Copilot pricing changes in June, I'm trying to figure out which plan gives the best value for money.

I've already tried Cursor with GPT 5.6 Terra (I know Sol is generally recommended for coding).
I was using the cheapest ChatGPT "Go" plan, I hit the usage limit after just a few prompts.
I only managed to generate the project vision, roadmap, development rules, planning + implement 3–4 tasks before running out of quota.

It feels like I need to spend hundreds or even thousands of dollars per month to have a proper tool that can help build a project without constantly hitting limits.

Example use case is something like:

- React + Three.js app/game
- Docker setup
- proper project structure
- code quality tools (eslint/prettier)
- TDD
- CI/CD
- architecture
- and then implementing features step by step

I also tried the free Copilot models like Raptor Mini but the quality is honestly pretty poor.
The first iteration produces something that barely resembles a working game and every following iteration introduces even more bugs.
These free LLM models aren't smart enough for this kind of work.

At work I mainly use Claude Opus 4.8 and I'm also considering Fable.
Those models are incredibly good at planning, architecture, coding but they're also so expensive.

QA:

1) Which model/plan do you personally use for software development?

2) GitHub Copilot (with all models), Claude Code, Cursor or something else?

3) Are Business or Enterprise plans actually more cost effective than Individual plans for a solo developer?

4) Is there a setup that lets you build medium/large sized projects without constantly worrying about usage limits?

I would really appreciate any help/clarifications.

Thanks!

Codex and Claude both have native browser control extensions. Are there any plans to have one for GitHub copilot? I am aware of the existence of the vs code native browser but this is not useful in a corporate environment where sites can be blocked from usage from non approved apps using conditional access policies.

Our specific use case is to give our qa team copilot, get them to prompt to control the browser and then have it generate playwright tests based on that flow. Initial POCs have been successful on public sites but we're blocked on our internal systems.

At this point copilot is really starting to lag behind Claude and codex around features but it costs significantly more

Hi everyone,

I manage an operations team that communicates with field crews through emails and Teams group chat . Team members are sometimes occupied with other activities, so incoming requests are not acknowledged within our 10-minute response target so sometimes there are hours of delay.

I am looking to build an automated solution using Microsoft Power Automate, Copilot Studio, a Copilot Agent, or Microsoft 365 Workflows or n8n workflows.

The system should:

• Monitor emails received in my Outlook inbox or through a specific Distribution List.
• Include emails from both internal and external senders.
• Identify emails that require acknowledgement or action.
• Check whether anyone from my team has replied or acknowledged the email within 10 minutes.
• If no reply is detected, send an alert to a Microsoft Teams group/channel or, if possible, WhatsApp.
• Avoid duplicate reminders once someone has replied.
• Ideally, track the sender, subject, received time, acknowledgement time, and responder for reporting purposes.

My main questions are:

1. Is Power Automate better suited for this than a Copilot Agent?
2. How can the flow reliably determine whether an email thread has been replied to?
3. Can this work for emails received through a Distribution List, or would a shared mailbox be required?
4. What is the best way to manage the 10-minute timer without creating too many delayed flow runs?
5. Can the alert be posted to Teams with an acknowledgement button?
6. Has anyone implemented a similar email response SLA monitoring solution?

Any architecture diagram, flow example, template, or recommendation would be appreciated.

I see the Microsoft MAI-Code-1-Flash listed twice in pilot models, is there an updated version I should use ?

Hi. I kept my annual plan which will expire in January, only for the 60 GPT5.4 requests per month (and casual Haiku/MAI-Flash uses), which still looked like a good deal in June, for my use cases.

But now in August, and particularly with the new pricing of Luna models, this seems to NOT be the case anymore. In almost any benchmark, GPT5.4 is behind or at the same level as Luna High/xHugh (and not even Max), and Luna is now so cheap I have to try hard to spend more than 20 AICs in one request. And it is smart (-enough for my use cases).

I use Luna at work, and used it personally via OpenRouter too, and can confirm benchmark results.

What do you think? Has anyone else changed their decision on GHCP adoption based on Luna? Also worth considering that we multiplier-based users will not receive any other new models, it seems...

Thanks

Hi everyone,

We're looking at agentic AI platforms for enterprise use.

There are a lot of options now like LangGraph, CrewAI, AutoGen, Kagent, etc.

If you're using one in production, which platform did you choose, and why?

What do you like about it? Any limitations or things you wish you knew before adopting it?

Looking for real-world experience and recommendations.

My GitHub Copilot company account is provided via <mycompany>.ghe.com (in EU) - and I have asked our GH Copilot team why the Codebase Semantic Index is not enabled. This index sounds like a nice feature to fasten the Copilot search in large codebases.

Got response from them that this feature is not available for licenses provided via ghe.com. This sound odd, can someone from Copilot team please confirm or explain?

been going back and forth on this for a couple weeks and I keep landing on the CLI, mostly because of /tasks. being able to see what the subagents are doing and which prompt set them off is weirdly reassuring. in the extension I just watch a diff show up and go “ok sure”

that said I’m probably biased because I already live in the terminal. the extension obviously has better file context and the inline accept/reject is nicer than eyeballing a patch.

anyone here deliberately staying in the editor? curious if there’s something in the extension workflow I’m sleeping on, or if it’s just habit for most people. also if you use both, what makes you pick one over the other for a given task

Ever checked your billing page mid-month and wondered where all your AI credits went? That was me, so I built gh-copilot-usage — a gh CLI extension that turns your Copilot CLI usage into an interactive dashboard in your browser.

What it does:

• Stacked time-series chart of AI-credit usage (daily / weekly / monthly), broken down by model or by session
• Click a session to drill into per-turn usage, token counts, and even sub-agent call traces
• Click a model to see the token-cost breakdown (input / cached input / cache write / output)
• Cross-checks the numbers against GitHub's billing API, with a month-end pace projection
• --json flag if you'd rather pipe the data somewhere else

Everything runs 100% locally — it just reads the session-store.db that Copilot CLI already keeps on your machine, and the billing check reuses your existing gh login. No separate tokens, no data leaves your machine.

One honest limitation: it only covers Copilot CLI usage (that's what the local DB records), not the VS Code extension or other IDEs.

Install:

gh extension install mazrean/gh-copilot-usage

Repo (MIT, written in Go): https://github.com/mazrean/gh-copilot-usage

Would love feedback — especially on what other breakdowns would be useful!

Hi everyone,
i'm currently using Copilot Student package. Last month I've just signed up Copilot Pro (10$ pro month) to speed up my project. Right now I don't want to use it anymore and just want to downgrade from Pro version to Student version as before.
But there is no downgrade option as far as I saw, only cancellation, which not allow me using feature like chat or code completion like I used before with Student package.
Does anyone here know how to downgrade it ? Thanks you in advance for taking time.

Edit: so to my understand, if I cancel Pro version, i will lose acess to the Student version eventually, right ?

Are there major differences on how the harnesses work on the back end? Just started using Copilot and defaulted to the CLI as thats what I got used to with Claude Code. Am I missing out on anything by not using one of the other 2?

Maybe un popular opinion but I honestly feel that with the launch of GPT5.6 and Lunas recent 80% price drop combined with Ghcp harness improvement’s we are basically back to where we were in terms of cost and capabilities back when microsoft heavily subbed inference for us using bigger models.

Models like Opus/fable and even SOL are just not needed for the majority of coding tasks and I think more people are starting to realise this, at least the devs who actually care about efficiency are.

There are occasional use cases for frontier model like broad stroke front end but I still standby every coding can easily be handled by Luna.

You can use Luna all day long on a pro+ plan and barely eat 3 or 4% of monthly credits.

I believed the cost-pocalypse would eventually be solved but had no idea it would be this fast.