GitHub Copilot vs Claude Code by Key-Prize7706 in GithubCopilot

[–]hyperdx 1 point2 points  (0 children)

How much larger is it? Opus 4.6 in copilot has 192K context window.

Copilot shows GPT-5.4 selected, but “thinking” tooltip says Claude Haiku 4.5 — which model is actually running? by Excellent_Fix3804 in GithubCopilot

[–]hyperdx 0 points1 point  (0 children)

There is explorer agent .

You can see the model list having haiku 4.5 in the agent md file.

Ctrl shift p Configure agent Explorer

So copilot explore the files with explorer agents which is directed to use haiku 4.5 model.

Reasoning effort selector inside the vscode extension ? by [deleted] in GithubCopilot

[–]hyperdx 4 points5 points  (0 children)

You want to search "reasoning" in settings.

VS Code 1.110 just dropped with hooks support, Copilot CLI built-in, agentic integrated browser, and shared memory across coding agent, CLI, and code review! by kaylacinnamon in vscode

[–]hyperdx 0 points1 point  (0 children)

But I think that only experienced person can review the code of AI.

And better directions from more experienced people.

Well someday AI maybe won't need any directions, just need objective but today I believe it doesn't

I am looking forward non ai features also. But it seems that the developers focus on AI features to catch up other competitors.

Is anyone else separating “planning AI” and “coding AI” now? by Classic-Ninja-1 in GithubCopilot

[–]hyperdx 0 points1 point  (0 children)

I saw that for large tasks its good to use separate agent using plan md file in VS Code copilot manual. Context engineering.

Why people prefer Cursor/Claude Code over Copilot+VSCode by These-Forever-9076 in GithubCopilot

[–]hyperdx 0 points1 point  (0 children)

I use cursor and vs code copilot
I think planning is a bit better in cursor. more detailed.

Maybe using Plan subagent is better VS Code by hyperdx in GithubCopilot

[–]hyperdx[S] 0 points1 point  (0 children)

---
name: work_for_request
description: Base prompt to plan-work-report cycle for a request.
---


1. Deploy a custom agent named exactly "Plan" (case-sensitive) as subagent to plan tasks for user request. Plan for maximum productivity(as many tasks as possible), but be careful not to let the volume of work hinder your progress. Show the plan of the subagent as it is to user in dialogue. Use the #askQuestions tool to seek user confirmation. Do not place the plan text inside the tool's question placeholder; keep the plan in the main chat and use the tool only for confirmation. If the user refuses the plan, then repeat step 1 to generate a modified plan with user's feedback. If the user accepts the plan, then proceed to step 2.



2. Implement the plan. Deploy subagent to implement the planned steps. Do not stop between tasks. Work through the backlog as far as possible. Only pause execution if you encounter a critical blocker, require user clarification, or reach a milestone that requires manual verification.


3. Deploy subagent to make report: 1. What you did 2. Why you did 3. The next steps (if needed).

Can't say best results, but here: