For some reason the response gets cut abruptly. The model returns "Thinking..." and then simply stops.
Is this a known issue on VS Code Insiders? How do I debug the root cause?
On Windows, it looks like Copilot uses PowerShell and the integrated terminal interchangeably. Well, to be honest I've noticed it tends to prefer opening the integrated terminal instead of running PS directly in the chat session in newest releases.
What's the best way to instruct it to always run PowerShell commands in the chat session itself? If there is any that doesn't involve adding yet another point to the copilot-instructions file as it's already too big.
Next Edit Suggestions in VS Code are great, probably one of the better implementations around.
However, what bothers me is ghost suggestions do not take into account a max line length, so the workflow is always accepting + manually wrapping if required. This is valid especially for comments.
It would be nice to be able to configure a max line length. Or, is there a way to do so already?
As you may know at this point, VS Code releases have shifted from monthly (+ recoveries) to weekly (+ hotfixes) starting from March.
I'm still skeptical about whether that's a good change, but most posts I see tend to revolve around "hey now it's all AI slop". So I had a quick look at milestones, both monthly ones and weekly ones.
On average we have the following number of closed issues/PRs:
I've also peaked at some of those PRs, and as far as I could see they are still pretty small/focuses and accompanied by test cases most of the times.
In the end it seems it did not change as much as I thought it would. We get changes sooner, albeit with an higher chance of bugs slipping through since people might say "let's fix this next week". Although, people were probably saying "let's fix this in next recovery" anyways in the past.
I had a pretty long session with GPT 5.4. Left VS Code open overnight with no connectivity. Reconnected this morning and prompted on the same open session.
The model began doing all kind of actions like opening the GitHub PR tool window, opening a PR view, scanning the entire codebase, applying code to unrelated files or at incorrect location.
Well, wasted a bunch of credits.
Restarted the laptop and it was all good again. Anyone has experienced something similar?
Has anyone experimented with tools like rtk to compress input tokens?
Before attempting to add it to my pipeline, I'd like to see whether other users are happy with it.
This is more of a feedback for MS folks. I know some of them like u/isidor_n see comments and posts from time to time.
Too keep it short, I develop tools for developers/sysadmins, and most of our customers are moving away from Eclipse to VS Code to have a more straightforward and lightweight user experience, and to be able to use Copilot with its first class integration with the workbench.
However, and this is a big however, customers are also experiencing higher and higher AI operational costs. Thus we must optimize how we interop with Copilot.
Customers like to prompt autonomously, but they also like action-driven workflows: they open a custom editor that offers AI-powered actions, and they use those to more rapidly spawn chat sessions.
Extension developers are currently limited in what they can offer to customers. For example, we cannot contribute chat context programmatically (not only text based, think about custom editor providers), or we cannot contribute contextual symbols (think about a `#currentreport` symbol to reference a custom report that's currently open and focused).
That's to say VS Code should help us create the most straightforward UX to avoid unnecessary prompting. We do have Chat Participants, but most users simply forget they exist and instead end up relying on MCP tooling.
Visto che un po' tutti i provider di LLM stanno aumentando i prezzi per token o per subscription, come sta evolvendo il consumo di token nelle vostre aziende?
Mi vengono in mente alcune PMI che si erano posizionate come "AI-first", ma visto i costi attuali e futuri mi domando come possa essere sostenibile la cosa.
Anche in multinazionali, dove prima l'uso di IA era incoraggiato per velocizzare gli sviluppi, si sta arrivando a situazioni dove i token/crediti allocati per utente finiscono dopo pochi giorni, rendendo del tutto inutile l'utilizzo.
I guess this isn't strictly related to Copilot, but I'm wondering how others manage generated code and its understanding.
Example: I had the LLM spit out some code related to JSON parsing using jsonc-parser, to handle autocomplete in a lenient context (incomplete/unparsable content). The generated code is well documented, pretty much sequential without strange abstractions, and accompanied by a test suite.
I'm also familiar with lexers and parsers. However, I'm not familiar with jsonc-parser, so the only way for me to verify whether the code actually made sense was to debug each use case and inspect local state.
30 minutes to write a good plan, hours to manually verify the solution, and I'm not yet fully convinced the code is simple enough to be maintenable. My brain just doesn't have the full understanding of these changes, thus I haven't merged it yet.
That's why I generally use Copilot to refine and augment manually written code.
How do you guys overcome that feeling of unsatisfaction when having the LLM generate an entire feature? And how do you cope with the fact you don't fully understand the solution?
I don't think it's a situation comparable to reviewing human-produced code.
This is a question for the Copilot team I guess.
Is it correct the Semantic indexing for Non-GitHub Repositories feature isn't yet available to Enterprises? And if not, is there a timeline to bring in the preview?
I'm setting up Copilot in a decently big Nx monorepo. Instructions clearly point it to execute Nx tasks when validating changes. However, the problem I've noticed is Copilot doesn't wait until Nx commands finish before interpreting the terminal result, causing inconsistent behaviors. Nx tasks may take a while to complete given the size of the monorepo, with an average of 20 seconds per command.
Is there any specific Copilot configuration to change in VS Code to accomodate the longer terminal execution times?
Well folks, here we are again with another supply chain attack. I wasn't even aware of it until an hour ago.
My 2c is the "nicer" experience of auto-updating extensions doesn't justify the security risks. There should at least be a minimum age, just like with the various package managers.
I've been running Copilot with my own OpenAI key for a while now, maybe more than a month. Daily usage with mostly GPT 5.4-mini (medium reasoning).
Of the 10$ I charged my profile with, I still have 5 left. 5.4-mini is cheap af as you may already know.
Today I got access to a Business account with 300 premium requests and immediately started using 5.4-mini. Well, I've already burned through 15% of the premium requests in a day.
Doesn't that translate to an overall better spending management with token-based billing? I understand MS may charge slightly more than going straight through OpenAI, but still I'd expect more mileage.
Thoughts?
Hey folks, I have the possibility to get enrolled into the Business plan right now at 19$/month. However, I'm not sure if I should wait June or not. Will the Business/Enterprise cost be changed, or will it be a transparent change on my side (only visible to the Enterprise that pays for the plan, in terms of usage limits)?
Guardando il sub di GitHub Copilot ho visto che i costi del nuovo sistema basato sull'utilizzo dei tokens sono assurdi.
C'è gente che con 39 euro spenderebbe 500/1000/5000 euro a giugno 💀
Credo che questi costi prima o poi si propagheranno anche agli altri providers.
A bit of background first: I'm currently leading the development of client-facing products (e.g., browser-based UIs, IDE plugins). We develop solutions on top of what server-side teams build, but we also develop independently to ensure that our customers enjoy the best client UX that is reasonably obtainable.
The independent approach, despite its definition, is still influenced by architectural decisions taken by other teams. I typically meet with others to discuss what's going on and what are the next steps, and I'm definitely one of those folks that answers with "no" more than "yes", especially when dealing with teams that want to "own" as much as possible without a real reason or advantage for customer experience.
I took a month off after years of working non-stop pretty much, and coincidentally I see many architecture-related meetings going on while I'm away. I do have another person that can join discussions, but not a person that has the full understanding of involved technologies and what a decision may mean for our team on the long run.
Maybe I'm overthinking, but I've been bitten by not accurately vetting every third-party decision in the past...
Wondering how other architects/leads handle long time off. Do you just say "f* it" and then eventually spend energy unscrewing the situation?
I'm not an LSP user as I develop in IntelliJ, but I have colleagues that don't want to pay yet another subscription or simply don't want to switch between VS Code (web dev) and IntelliJ (Kotlin).
So I'm just wondering, what's the LSP status right now? Is any of you using it daily without noticing any critical issue?
I recall reading somewhere, probably under a YouTube video, the idea of using Code With Me (which is now deprecated unfortunately) as a mean for AI agents or for simple AI-powered file editing to appear as virtual pair programmers.
You'd be able to follow edits, and why not interact with the process live. Doesn't sound like a bad idea to be honest.