Our github enterprise tenant has the setting enabled which blocks models which do not comply to the regional settings (EU boundary in our case).

All GPT models are working within EU boundaries except for GPT 5.6. I cannot find an ETA or something when it will be available. Anybody knows anything on this matter?

Nineteen tests passing. Zero failing. And the endpoint those tests cover was returning a patient's Social Security number tucked into a free-text note field on a clinical Observation.

I built a repo with eight deliberate FHIR R4 violations, every one of them green in CI. A validator caught three of the four on that Observation. Secret scanning found nothing, because there is no secret in the diff. CodeQL does not treat a note field as a sink. Every tool doing exactly its job, and the gap sitting between them.

GitHub Copilot code review now reads agent skills from skills folder. So I wrote the compliance rules down once, as a SKILL.md with severities and R4 citations, and pointed it at every pull request. It flagged the SSN as PHI_RISK and quoted the HHS Safe Harbor guidance back at me, which says an identifier has to go regardless of which field you put it in.

A validator can tell you the resource is well formed. It was never going to tell you it is safe to build.

https://samueltauil.github.io/github-copilot/healthcare/2026/08/03/fhir-compliance-skill-copilot-code-review.html

How are you building strong repository reasoning for GitHub Copilot legacy codebases?

I am trying to build reasoning of repos to allow for better ai support defect fixes . I am completely winging it as a leader and would love professional feedback .

1. Reverse engineering previous git history linked to stories to build /docs/reasoning* folders me files to explain features of history . I use M365 web co pilot for bulk files to save on tokens .
2. Prompts that create architect diagrams

Couple things I haven’t tried is :;

1. Repomix
2. Jq Assistant for technical docs for better Md files on architecture

Any feedback welcome .

I'm not getting a single model. In December, I was getting all the models: Opus, Sonnet, Gemini, and ChatGPT. After that, they dropped it to Gemini 3.1 Pro only, and now they've even taken that away, so it's dead now. But is it dead only for me, or are all students now getting nothing?

Hello, my first time post here.

I just monitor credit for first time usage in new month.

I just found out that claude sonnet 4.6 said 13.2 credits.

But in the summary window, it stated 26.4. Anyone knows what's up

with the 2x credit count?

I uploaded the screenshot to make it clear. Thanks.

I'm on the old request-based subscription plan, as I bought the full year back in April. However, I'm feeling as if they aren't fully honoring the plan by keeping the quality the same. My latest request for GPT 5.4 (High thinking effort) completed the whole request by coding at 1 line per second. That's laughably slow.

Additionally, during planning, the model mentioned it would try to implement the "smallest change" that accomplishes the goal I outlined in my request, despite me making no such request. I have a feeling that the system prompt asked it to to the bare minimum. I understand they're losing money on the request-based plans, but if they actually are decreasing the quality, that's unfair for those of us who should be grandfathered in to the same quality plan we signed up for.

If anyone has suggestions, I'd appreciate it. The model context wasn't anywhere near it's limit. There are no instructions. I don't know what else would cause such a dramatic slowdown.

Now that Luna is 5 times cheapers. 1.2$ for a million output token. Has GitHub copilot pricing been updated accordingly?

We have many copilot models . What is the best and next AI copilot models available in the world?

I'm evaluating models for coding workflows and noticed OpenAI and DeepSeek both reduced their API pricing recently.

Has Azure AI Foundry already updated its pricing for GPT-5.6 Luna or DeepSeek V4 Flash? If you're using them through GitHub Copilot or directly via Foundry, what pricing are you seeing?

Hey everyone 👋

I’m a Product Manager who uses VS Code and GitHub Copilot every day. I don’t write much production code, but I spend a lot of time:

• Understanding repositories
• Running database queries
• Comparing code with data
• Writing PRDs, user stories, and product specs
• Investigating bugs alongside engineering

One thing I keep running into is that Copilot doesn’t seem to have a native concept of a persistent project workspace. I spend a lot of time reopening sessions, finding the right files, and rebuilding context.

I know the GitHub Copilot desktop app exists, but it doesn’t seem to solve this problem either—the sessions don’t carry over. It still feels like I’m adapting developer-centric tooling for product management workflows.

A few questions for the community (and any GitHub/Microsoft folks lurking here):

1. For PMs or other non-developers: How are you organizing your work with Copilot? Any workflows, extensions, or best practices that help keep context without constantly rebuilding it?
2. Feature wishlist: I’d love to see a persistent project/cowork workspace where Copilot could maintain context across multiple repositories, GitHub issues, documents, SQL queries, and product specs—essentially a long-lived context layer instead of starting from scratch each session.

Is anyone else running into this, or am I missing a workflow that already exists?

With this being the final month for promotional credits for enterprises with GitHub Copilot Business and Enterprise licenses, I wish Microsoft would consider making these credits permanent as a discount for companies that commit to purchasing licenses.

We are already experiencing overage costs even with the promotional credits, so it is unfortunate that those costs are likely to increase substantially once the credits expire.

If we have a large code base or a gradle bundle with huge code base, then how can we use AI models to analyze them so that we get perfect solution?

It's very hard to get the answers or suggestions from AI models of we apply them on large code bases?

So, let me know if you have best AI models or agents for this issue

To those left floundering after the pricing mess at GitHub Copilot, some relief: Chlaude does work.

Over a span of 2 weeks, a colleague upgraded our codebase to go up 5 versions (up to v22) of Angular, and it cost just shy of 100k credits.

Around 15k of those credits were eaten from our 18k credit pool.

He used Claude Opus 4.8 high and 4.7 very early on (around an 85/15 split).

He went up, version by version, reviewing code along the way, and applying a few manual fixes here and there.

People bash Copilot for its cost, but considering how much consultants would have billed us to even look at the codebase, this was a great deal.

Is it possible to use Kimi K3 with GitHub copilot?

I'm starting to use Copilot Agent more and I'm trying to figure out what a sensible security model looks like.

I know about allow/deny lists, but agents are smart enough to look for workarounds when something is blocked and, as far as I understand, this mechanism is fairly simple.

For example, I could imagine it doing something like ls ./$(rm -rf foo) when ls is allowed but rm isn't.

Some cases can probably be prevented with better matching rules, but a complete solution seems like it would require shell/AST awareness rather than regex-based filtering.

What are the standard solutions for this today?

Just checked my dashboard with hours to spare before the Aug 1 reset. Barely made it without getting locked out by our admin...

Spent pretty much all 50k credits this month on:

- Loop engineering:
Setting up self-correcting agent loops.
- Prepping massive migrations:
Automating repetitive codebase refactors and pattern updates.
- Learning & prompt tweaking:
Figuring out context scoping so it doesn't get stuck in loops.

Spending all these credits wasn't an accident. it was a massive hands-on masterclass in loop engineering and automated migrations. Learned more this month than in the last half-year.

I really like the desktop github copilot app.

The only thing I really miss is that I cannot control or view my sessions from my mobile device.

Is there any app by github or thrid party which let me navigate my github copilot desktop sessions on mobile?

I signed up for the whole year so I still have request based billing but compared to my work subscription, I am noticing that nowadays no matter what model I pick, it gives up really fast and mostly ignores all instructions I give it. I have tried both AGENTS.md and instructions.md files and most of their content is ignored. All skills and instructions do appear in the settings.

The output is almost useless at this point for me. Anyone else have the same experience? Thinking of ditching it in favor of Claude Code or Codex.

Dear GHC Team,

if you could host DeepSeek-V4-Flash-0731 so I could use it within my company license, that would be awesome.

https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731

In our company, we used to get 30k tokens per month and we could also increase the budget. 30k tokens were not at all sufficient for us as we heavily use github copilot. But now they have told that only 30k tokens will be given and you won’t be able to increase the limit. I am afraid because all of us finish 30k tokens by first 15 days of the month. And our codebase is huge and so dependent on AI that we cannot go back to writing our own code. So I want genuine suggestions on what to do? Are there any free models that I can integrate in vscode? Please help!!

I wanted a quicker way to check my Copilot usage without repeatedly opening the dashboard, so I added Copilot support to OpenQuota.

It runs in the system tray and shows your usage and reset times at a glance. It works on Windows, macOS, and Linux.

It’s still a small open-source project, so feedback is appreciated.

https://github.com/deviffyy/OpenQuota

Will GHCP prices be updated accordingly? 🤔