VS Code Copilot (Agent) vs Google Antigravity (Planning) & More

This entry is part 2 of 2 in the series Golang AI kata comparison

Back in July 2025 I did a little comparison of various AI code assistants with a small Golang kata (with some content stripped out), and I’m back for a second attempt using the same kata, but focusing on some of the newer Copilot models, as well as cloud agents, and a run through with Google Antigravity. All runs have been screen recorded, very generic time metrics extracted, and the code is also all up in branches in the code repo if you are curious…

The prompts used will also be the same as i my last blog post, starting with…

The code repository is going to be a small Library application.
There are CSV files in the resources directory that contain the content of the library.
Create a user interface that allows display of all books and magazines with detailsCode language: Access log (accesslog)

And continuing to guide the agent through adding a couple of features such as searches, ordering, writing some basic tests, allowing adding data and having a companion application (either CLI or UI, depending on what it chose to do first). You can expand the second below to see them all…

Great! Now I want to add to the interface that you created to allow searching for a book or magazine by its ISBN.
I still want to be able to easily list all books and magazines without any filters / searches too.Code language: Access log (accesslog)
Add an additional way to find books and magazines, by using their authors email address.Code language: Access log (accesslog)
Add the ability to sort all books and magazines, with all of their details displayed, sorted by title.
The sort should be done for magazines and books in combination.Code language: Access log (accesslog)

And as a follow-up …

Write unit tests for the project where appropriate.
If the code is not very unit testable, refactor it, maintaining functionality.Code language: Access log (accesslog)
Add one final feature that allows a user to add books, magazine and or authors to the library.
This should update the CSV files to show the data for future library lookups.
Don't let them just add to each file separately (such as author first), create a sensible form for adding things in a single action.Code language: Access log (accesslog)

And for the second application…

If you didn't yet create an interactive WEB UI, do so now.
If you didn't yet create an interactive CLI UI, do so now.
This can be very simple without much or any styling, but must be functional for the required features:
 - read data from CSV files
 - display all books and magazines with details
 - search by ISBN or author email
 - print them sorted by title
 - add things to the library (persisting to the CSVs)Code language: Access log (accesslog)

You might also have seen me occasionally send this hint to try harder…

Allow the user to choose the sort directionCode language: Access log (accesslog)

Before diving into details, overall the 5.2 Codex model as part of Copilot seems to be my favourite, though to be honest, if you can structure your prompts and repositories to work well within the GitHub Copilot cloud agents setup, that looks very appealing.

The numbers

These numbers all come with a pinch of salt, and you need to read the blurbs next to each video below to learn about that salt. Each number roughly summarizes how long that stage took according to the video replay. Some setups do more validation which takes more time, some just hope they got it right, others get stuck in the same problems over and over again, and some one shot it…

IDE & AssistantModelMain tasksTestsEditingSecond appTotal
VS Code & GitHub CopilotGrok Code Fast 16:341:491:53CLI 1:20 ~ 12 minutes
VS Code & GitHub CopilotClaude Haiku 4.511:573:207:27CLI 3:41~27 minutes
VS Code & GitHub CopilotClaude Opus 4.52:454:041:19CLI 7:21~16 minutes
VS Code & GitHub CopilotGPT 5.2 Codex5:491:212:46CLI 0:55~ 10 minutes
Google AntigravityGemini 3 Pro19:154:154:56CLI 1:56~ 32 minutes

It turns out figuring the timings for the individual steps for the cloud agents was rather hard, so I’ll only note their complete times…

IDE & AssistantModelTotal
Cloud – GitHub CopilotAuto?17 minutes
Cloud – Google JulesGemini 3 Flash31 minutes

The shortest overall time from my last post was around 18 minutes which was Roocode in VS Code with GPT 4.1, so seeing that GPT 5.2 Codex in Copilot did it all in around half the time and came up with a “better application” hints at a great improvement in the last 6 months.

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AI Code assistant experience comparison (golang-kata-1)

This entry is part 1 of 2 in the series Golang AI kata comparison

If you’re reading this, and thinking about trying an IDE integrated coding agent, or thinking about switching, maybe stick around, have a read and watch some of the videos. There is at least 6 hours worth of experience wrapped up in this 20 minuite read!

I’m watching a thread on the GitHub community forums, where people are discussing how GitHub Copilot has potentially gone slightly downhill. And in some ways I agree, so I through I’d spend a little bit more time looking at the alternatives, and how they behave.

This post tries to compare 9 different setups, and will primarily look at the differences in presentation within the VS Code IDE that each of these different coding assistants have. How the default user interactions work, and how the tasks are broken down and presented to the user, and generally what the user experience is like between these different assistants.

I’ll try to flag up some other useful information along the way, such as time comparisons, amount of human interaction needed, and overall satisfaction with what the thing is doing, and if this all presents itself nicely in this post, I might find myself writing more in the future…

However, I will not be looking at cost, setup, resource usage or what’s happening with my data along the way…

Assistant, LLM combinations

AssistantModelMain tasks @Tests @Second app @
Github CopilotGPT 4o~ 5:00~ 24:45~ 32
Github CopilotGPT 4.1~ 15:00~ 17:40~ 35
Github CopilotClaude Sonnet 4~ 17:00 (inc tests)~ 17:00~ 28
Gemini Code AssistantGemini Something ?~ 11:20~ 14:30~ 25
AmazonQClaude Sonnet 4~ 7:20~ 15:50~ 28
RoocodeGPT 4.1 (via Github Copilot)~ 5:30~ 10:00~ 18
RoocodeClaude Sonnet 4 (via Anthropic)~ 15:30~ 20:00~ 37
Claude CodeClaude Sonnet 4~ 9:30~ 17:40~ 24
Claude CodeClaude Opus 4~ 10:00N/AN/A

I have setup this post, and the code problem in such a way that I should be able to easily add more combinations and comparisons in the future, and directly compare the performance back to this post. Ideally, at some stage I’d try some other models via Ollama, and also some other pay per requests LLM APIs…

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