VS2026 recently added a feature to the copilot-instructions.md

[blockmodule]

🏷️ Discussion Type

Question

💬 Feature/Topic Area

Copilot in GitHub

Body

VS2026 recently added a feature to the
.gitHub
　copilot-instructions.md

The idea of the copilot-instructions.md file was really good, but if you wrote the restrictions and rules in copilot-instructions.md
Copilot's load would have increased terribly.

As a result of the introduction of the copilot-instructions.md file, it must have been quite detrimental to the model AI.
One individual can experience this increase in load, so if tens of thousands of people apply copilot-instructions.md every time, the load will have been increased by GitHubCopilot and Microsoft.

More likely, it was a release feature that was far from the intention of reducing the load.

[Priyanshu-byte-coder]

I don’t think copilot-instructions.md significantly increases model load in the way it might seem. These instruction files are typically handled as additional context, similar to how prompts or comments already guide Copilot’s behavior. The model isn’t retrained or permanently burdened — it simply conditions its responses on the provided rules during that interaction.

In fact, structured instruction files can reduce overall load in some scenarios because they make the intent clearer, which can reduce back-and-forth prompting and improve first-response accuracy.

So while it might feel like “extra work” for the AI, the practical effect is usually more efficient inference, not more expensive training. The main trade-off is slightly longer context processing, but modern systems are designed to handle this type of structured guidance efficiently.

Overall, the feature seems aligned with improving output consistency rather than increasing infrastructure strain.

[blockmodule]

Hello Priyanshu-byte-coder!
Thank you for your reply regarding copilot-instructions.md.
You said, "In practice, it does not increase training costs, but generally improves inference efficiency," which means that the AI's thinking costs go down, not up, as you say...
The copilot-instructions.md is very useful, but I felt that the overall cost of AI's thinking was going up because it slows down responses as the content expands and even when it is not related to the copilot-instructions.md description.

Not so, except that it is not.
I am convinced!
Thank you very much.

[AgentSeal]

the previous reply is mostly right but slightly oversimplifies. copilot-instructions.md does add tokens to every request, and more tokens = more compute, thats just how transformers work. but we're talking maybe a few hundred tokens of instructions vs thousands copilot already sends (open files, imports, surrounding code). the marginal cost is tiny.

only thing to watch out for is if your instructions file gets really long it competes for space in the context window, meaning less room for actual code context which could make suggestions worse. keep it concise and you wont notice any difference.

[blockmodule]

If there are many instructions in the copilot-instructions.md (long description and rules), the accuracy of the proposal is indeed reduced.
Conversely, if there are many code rules, even if they are written concisely, the speed seems to decrease.

[farizal099]

I think this concern might be a bit overstated.

The purpose of the copilot-instructions.md file in GitHub Copilot is not to significantly increase model load, but to provide better context and guidance for generating more accurate suggestions.

From a technical perspective, adding instructions is similar to providing additional prompt context. While it may slightly increase token usage per request, modern systems are designed to handle this efficiently, especially at scale by Microsoft.

Also, having structured instructions can actually reduce unnecessary back-and-forth or incorrect suggestions, which in the long run may optimize usage rather than worsen it.

So instead of being detrimental, this feature is more likely intended to improve developer productivity and output quality.

[Gecko51]

What you're observing is real: longer copilot-instructions.md files do slow down responses and can reduce suggestion quality. AgentSeal's explanation is accurate.

The practical fix is to split your instructions rather than keeping everything in one global file. VS Code Copilot recently added support for scoped instruction files:

File-specific instructions (.github/instructions/*.instructions.md) let you apply rules only to relevant files using a front matter header:

---
applyTo: "**/*.py"
---
Use type hints on all function signatures...

This way your Python-specific rules don't get sent with every TypeScript request, and vice versa.

Practical guidelines for keeping things fast:

• Keep the global copilot-instructions.md to your truly universal rules (team conventions, general code style). 50-100 lines is usually fine.
• Put language or domain-specific rules in scoped files under .github/instructions/
• Avoid repeating things the model already knows by default ("write clean code" adds tokens with zero benefit)
• If a rule only applies in certain chat contexts, use a prompt file (*.prompt.md) instead of a persistent instruction

The slowdown you're seeing with many rules is mostly a context window competition issue. The more tokens your instructions take, the less room there is for actual code context, which hurts both speed and accuracy.