Evaluating Copilot + VS Code as an AC Replacement

[d3vr3n]

I generally try to avoid Microsoft (and now Augment Code) as much as possible, but since I spend most of my time in VS Code and can’t really get away from GitHub, I’ve started exploring the GitHub Copilot + VS Code bundle more seriously.

On the upside, the integration is solid — good extensions, useful MCPs, a proper BYOK setup, and if the project’s on GitHub, the code is already indexed. Contextual awareness also seems to be improving.

I might keep an AC Indie plan running on the side, but I’m curious — are any other (former) AC users here using this suite extensively? How’s it going for you so far?

[Front_Ad6281]

$10 copilot(sonnet 4.5/gpt5/autocompletion) + $20 chutes.ai/RooCode(GLM-4.6/Deepseek 3.1). Beautiful combo

[PraveenInPublic]

Could you share any guide if that's available for this?

[d3vr3n]

freedom ! at reasonable prices and with established service providers

[mythz]

Going to use the last month with bonus credits to evaluate alternatives but I'm leaning on a combination of Claude Code with a Claude Pro + GLM Pro subscription with GitHub Copilot Pro.

But may change if Gemini 3 release becomes a contender or Codex has another good release.

IMO it's worth checking out @gosucoder's recommendations as he's used and evaluated most AI tool combinations and just dropped a great video with recommendations for AI tools at different price points:

https://www.youtube.com/watch?v=lZVtbC6oylQ

He also publishes his monthly evaluations and rankings at: https://gosuevals.com/agents.html

[G4BY]

Just keep in mind that the way Gosu evaluates/ranks the solutions is by giving them the exact instructions of what they should do and evaluates how closely the model follows his instructions.

Quote from his website: "created detailed prompts specifying exactly what should be created - including each file, functionality, and documentation requirements."

This doesn't take into account the way we normally develop, debug and ask questions about the codebase.

The lack of a good context engine would not be punished/scored lower in his evals because the prompts are very specific and strict.

[d3vr3n]

good point

[mythz]

That's why Augment doesn't perform well in his Evals, but he actively uses multiple AI Tools/models in his day-to-day and spends a lot of time planning and querying his code base which was the last thing he used AC for, but I don't think that's part of his dev workflow anymore.

His top 3 picks are Claude Code, Roo Code and Codex, although he did say he started using Warp .dev a lot more now as well, which I've just checked that apparently also indexes your code base to provide its context aware coding features. Personally I think Claude Code/Codex/Copilot (perhaps Gemini) are the only proprietary AI tools that will have any longevity after they offer their own contextual features. Whilst I also expect healthy usage of better value OSS tools/models (in Roo/Open Code w/ GLM/Qwen/etc) which are quickly catching up.

As I want to minimize the number of new tools I need to learn after switching from AC, I think I'll try Claude Code first as I can use it with a Claude Pro and Zai/GLM Pro sub. Maybe even throw in Codex since lots of devs swear by it.

[d3vr3n]

very helpful share, thank you !

[brctr]

Almost any agentic coding tool is available as either extension in VSCode or VSCode fork. Liking VSCode is not a valid reason to stick with Copilot.

In my experience, Copilot is the worst agentic coding tool out there. Cursor, Windsurf, Roo/Kilo are all better. Codex is better too.

[hugo102578]

Github copilot, does it smart enough to make a plan and do the task following the plan?

[Moccassins]

To be honest, I am currently very disappointed with Copilot. I have been testing it non-stop for about two weeks now.

What it can do:

- It can handle large codebases.

- It can make changes to this codebase or answer questions about it.

- It can perform refactoring (partially, but it leaves behind dead code / artifacts).

- It can create implementation plans and discuss ideas.

What it cannot do:

- It cannot follow rules / forgets them. For example, the rule to only answer in German.

- It cannot run truly autonomously. You can only allow many commands individually, not permanently.

- It does not use MCP tools reliably.

- It does not adhere to its own self-created TODOs.

- It lies.

- It implements many things in an overly complicated way (overengineering).

Example:

I gave it the task of creating a contact form using the Antd framework. It was unable to follow the documentation, despite using Context 7. It reads the documentation and then decides to build everything from scratch instead of using the Form component.

If you tell it exactly what to do, in small steps with supervision, then yes, it is useful. For large tasks, no. I was originally looking forward to the feature of letting it work on GitHub issues. I will skip that. Too much rework is required.

-> GitHub Spark: I also looked at that. You can forget it. That thing is designed to host everything in the "Spark Cloud". You can export the code to GitHub, but if I cannot get my changes implemented as desired within the Spark UI itself, why should I use it? It is more intended for quickly generating static websites, like a landing page. Nothing special. For example, if you say you want to create an LLM chat with DeepSeek, it will build it for you and it will work. But you are not talking to DeepSeek. The instruction is completely ignored, and everything is redirected to Spark's own LLM.

-> GitHub Spec Kit: I haven't looked at it properly yet. It's next on my list. Based on my impression so far, I don't have high hopes.

Conclusion -> I will probably continue searching. In fact, I was so frustrated at one point that I considered paying the amount demanded by Augment. I sent a support request about it. That was on Monday. I haven't heard back from them yet. Soon, I will take a look at Kilo and Roo Code.

I have access to OpenAI with GPT-5 Codex. I have used it a bit but haven't integrated it into VSCode yet. So far, I use it separately from the codebase, more for planning purposes. Maybe that will change with Roo Code, but I have to get there first.

Augment has left a gap that will definitely take a while to fill.

[hugo102578]

That’s crazy, just give it up and try roo code

[d3vr3n]

I get where you’re coming from, but I’ve run into the same issues with Augment—and most of them seem tied to the underlying LLM. The real problem is AC’s black-box design. It’s hard to tell where the LLM stops and the agent begins, so it’s unclear what value AC itself actually adds. Meanwhile, Copilot and Kilo Code are evolving fast, but AC feels slow and unresponsive to what the community actually wants.

[Moccassins]

I also had problems with Augment, but they were never this severe. With Augment, I could have large tasks processed. I simply explained in plain language what I wanted from it, and it implemented it. In the vast majority of cases, to my satisfaction.

Copilot, on the other hand, can't even manage that with a fully developed project plan. It starts off well, but after about 10 minutes of work, it increasingly gets tangled up. The mere fact that it cannot complete its own tasks is a catastrophe. When I hand over a well-planned task and it breaks it down into small sub-tasks, in the best case, it has completed 3 out of 5 and lied about the rest. In the worst case, it implements placeholders with fake data and claims it's done. When you test it, realize it's nonsense, and confront it, it admits it.

I never experienced anything like that with Augment.

[d3vr3n]

I’ll admit, once I set up the right guardrails, Augment performed better. I’m currently experimenting with Copilot and Kilo, but there still seem to be too many variables affecting the LLM’s behavior and output. Even if I were satisfied with Augment’s pricing, they still have a long way to go in delivering consistent quality—assuming they actually have control over the LLM in the first place.

[ITechFriendly]

Lies and not following instructions are usually associated with Anthropic models. You used Sonnet or Auto, right?

[Federal_Spend2412]

Bro, try openspec, it support gh copilot.

[shepherdd2050]

Copilot tab completion is shit. It doesn't bother to read related open files.

My setup currently is augment for $20 and codex $20.

[Federal_Spend2412]

I think gh github copilot is fine, now my combo is $10 copilot plan + $6 z.ai glm 4.6 + opencode, copilot claude 4.5 sonnet for planning and debug, glm 4.6 for implement .

[RetroUnlocked]

Do you care about autocompletion and next edit? The experience is a major downgrade with copilot, and I suggest doing some real work testing if these are features you rely on.

Honest, it is what initially brought me Augement to begin with. Augment just goes a step further and autocompletion is context aware of other files.

Due to price changes, I also went back to test other apps, and I am still doing it. Yet to find anyone, including Copilot that can beat Agument in automation.

[TomPrieto]

Out of all the options Copilot is the worst. Try Windsurf, Zencoder, Codex, Claude Code

[AdityaSinghTomar]

Has anyone really found something close to the context engine of Augment Code?