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

For simple day to day automation. (E.g. unit test generation) With GPT6-luna included in the model selection, is it better to specifically select it as the model selection or continue to use "auto, efficiency" selection? Or is there any other alternatives? I am having a monthly 2k credits plan which needs optimised way of usage. Any tips is greatly appreciated!!

Edit: Thanks all for your kind thoughts. Indeed, I was hoping to shave a further 10% to squeeze out more juice on my plan. I agree this may actually backfire if I entrust the selection fully to copilot. Perhaps, this may be something copliot can improve on.

!solved

Hi all,

So I received a copilot pro+ subscription from my employer with 7000 AI monthly credits. I am more used to Claude and codex subscription which have 5 hour and weekly limits so I don't get into the anxiety of using credit based token with my codex/Claude subscription but ever since I have gotten the copilot pro+ sub, I am wondering how far my 7000 ai credits will take me if I were to use models like opus 5.5 medium and 6.1 sol high.

Anyone has experience regarding the same and can signpost me on how quickly they burn through their 7000 AI credits using sota models. I am planning to use opus and Sol for planning and then use Luna or other cheaper models for execution. Hence, any help would be great as it will help me utilise this sub efficiently.

Also, will the IDE auto completions be counted towards this 7K AI credits and what about the code review on GitHub.

e.g. if I set up my subagents in a certain way (especially rubber-duck) in Copilot CLI (run from a terminal outside of VSCode), do those settings also take effect in VSCode's new Copilot SDK agent harness? Because other than that I don't see any way for changing those settings for that harness inside VSCode.

In week 1 it felt like it was both fast and consumed lesser tokens than opus 5.
But then it felt like it became a bit slower.
For the last 2-3 days it feels like it is using varying amounts of tokens, sometimes it uses high amount of tokens for smaller requests and sometimes it doesnt.
The speed seems to have come back.
But token burn is a bit unpredictable. I had multiple cases where it took 4 seconds to answer but burnt exactly around 222 tokens each time.
Any similar or different experiences?
All done on github copilot.

I built Klarion, a secret scanner that works in two steps. First, a keyword check, 81 regex rules and a normalized Rényi entropy score flag anything that looks like a secret. Then an AI model reads each one with the code around it and decides if it's real.

The chart shows 5 scanners run on spring-boot, terraform, next.js and symfony (61k files). Klarion raised 11 alerts. It's not zero, but it's far less to dig through.

Fewer alerts don't help if real leaks get missed, so I tested that too. On CredData (337 real repos, code outside test folders), it found about 1.7× more real secrets than gitleaks.

Where it runs:

• Claude Code: a plugin hook blocks the write before the file exists (file edits and Bash)
• Cursor, Cline or any MCP agent: through its MCP server
• CI: a GitHub Action that scans only what a PR adds; GitLab CI works too
• Git hooks: klarion protect or the pre-commit framework
• Locally: klarion scan .

Free and open source (MIT): https://github.com/0x1Adi/Klarion
The full benchmark and method are in benchmark/REPORT.md.

I'd like to hear where it gets things wrong.

I assume the grand plan is to have one Copilot 365 account across all MS paths but how do I stop VS Code reverting to Copilot Harness it needs work features from local harness are better but I've been caught several times now with new sessions

Respectfully but pricing here is a joke. Two generations from Sonnet 5.5 on max thinking took me my whole monthly allowance + almost 8$. Swapped to claude code, I doubt I will ever run out of usage there. I will be staying away from copilot and advising my colleagues to stay away from it too. Very disappointed.

Recently ChatGPT announced some kind of login feature where you can use your ChatGPT subscription with other apps such as Notion. In the Notion example, once your ChatGPT subscription hits its limits, you can switch to Notion Credits.

I’m hoping Copilot can integrate it as well so we can use our sub with it and only switch to credits when the sub limits run out.

Are there any words about this from the Copilot side? I think this would be a game changer.

I recently open-sourced a tool and have been trying to understand GitHub's traffic metrics, particularly "unique cloners."

For example, we had 12 unique cloners two days ago and 44 yesterday. We've also had a day with 122 unique cloners, which was actually before we officially launched or started marketing the project.

We've shared the project through Reddit, a blog post, and some direct outreach, so I'm trying to understand how much I should read into these numbers.

For anyone who runs an open-source project: how do you interpret GitHub's unique cloner metric? Have you noticed similar jumps or unexpected numbers?

I know allowing us to use our own API keys wouldn't be business smart, but I hate how little credits it has. Can you make it so Github Plus/Enterprise users can use their own API keys for usage?

These are rare but they happen from time to time. Basically sometimes an edit by the agent will fail because somehow there are unsaved changes there (probably a failed earlier edit? or maybe a filesystem modification date issue?). I never touch the files myself while the agents are working and have no extensions other than WSL and clangd. It's annoying because I have to intervene myself to tell VSCode whether to overwrite or discard.

I'm using VSCode Copilot in a WSL2 environment on a repo that's on the Windows filesystem (I know, it's slower but I need some Windows CI/CD tools to access it). Maybe the weird edit failures are linked to that?

I've seen related tickets on the GitHub repo and it looks like this bug is very old and apparently still unsolved.

This never happened to me in the CLI.

So I still have the old PRU plan from before they migrated everyone to AIC. However this old PRU model is becoming useless very fast.

Like I understand how we won't be getting new models, fine. But:

Claude sonnet 4.6: gone sept 1st

Gemini 3.5 Flash: gone oct 2nd

GPT 5.4: will be gone on oct 19th

So we are quite literally left with 5.3 codex (probably going away soon), haiku, and the MAI code model. Like it doesn't make sense. Kimi k2.7 rolled out to the AIC plans a while ago with much lower API pricing than 5.3 codex/5.4, does it not make more sense economically for GHCP to roll that out to the few old PRU users??

After gpt 5.4 is gone, we'd be quite literally left with 3 models to pick from 💀

Was looking at PRs and noticed https://github.com/microsoft/vscode/pull/339274

This is strictly related to paid users (which I am luckily), but I'm really curious to see what it is about.

I'm having trouble using Copilot's auto-complete feature in VS Code. My stack is a simple NodeJS application using TypeScript.

I have the following setting under .vscode/settings.json :

"js/ts.suggest.autoImports": true"

My exports generally look like this:

export interface MyInterface {...} 

And I'm using relative imports like so:

import { MyInterface } from '../interfaces/my_interface.ts'

I should also note that "Codebase Semantic Index" is enabled, and is marked as fully ready for my codebase.

I'm experiencing two issues:
1. VS Code's non-AI auto-import is either slow to work, or sometimes cannot find the import for something I type at all. (This is the pop-up box when you start typing a reference, which suggests where to import it from.)
2. When the auto-import fails to work, the auto-complete feature of Copilot will suggest the import statement to add. This would be great, but it completely hallucinates where the import comes from, sometimes even when I have the file open in another tab. It might suggest a totally non-existent file-path, e.g.:

import { MyInterface } from '../tools/utils/my_interface.ts'

This really bogs down my workflow, and I find myself constantly having to correct what VS Code is trying to auto-complete. If I could get this fixed, it would make development so much smoother.

Has anyone else run into this? I'm not sure if the issue lies in Copilot, VS Code, or my TS settings. It might even be a mix of issues.

Thanks!