We've completely rebuilt Kilo Code for VS Code, built on OpenCode server. New portable core, parallel tool calls, subagent delegation, inline code review, multi-model comparisons. Get started: kilo.ai/install
A lot of people hit a breaking point when agents start generating more diffs than they can confidently review—how did you design the inline diff reviewer + line-comment-to-chat loop to reduce review fatigue, and what review metrics (time-to-approval, revert rate, “second pass” prompts) are you tracking to prove it works?
And yes, while you can bring your own keys or use local models, most users pay for inference via the Kilo Gateway, which lets you switch freely between models using one balance.
You just pay for token at provider costs - whatever Anthropic charges for Opus, and whatever OpenAI charges for GPT, that's what you pay!
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Can you diff review across model comparisons? Like if three models each refactor something differently, can I review those diffs against each other instead of just against the original?
@whetlan Yes exactly! You can do that with the new Agent Manager. Spin up 3 parallel agents to refactor something, choose a different model in each, and then review the individual, parallel diffs against the main branch!
absolutely - this new @VS Code extension introduces an Agent Manager to let you run multiple, independent agents in separate tabs, give each one a role, an AI model, and use git worktrees so they never step on each other's code.
Been using VS Code for most of my systems projects and the idea of running parallel agents on different parts of a codebase at once is something I've been waiting for. Curious how the diff reviewer handles C and low-level code — going to try it on my kernel prefetcher project this week.
Rebuilt for VS Code sounds handy. Parallel tool calls + that subagent thing has me curious - less sitting around for runs? I bounce between GPT/Claude, so multi-model compare in-editor could save tabs. Gonna try it on a throwaway repo tonight.
Parallel agents and subagent delegation is a solid foundation — but how does Kilo Code decide which model to route a subtask to in multi-model mode? Is that user-defined or does the agent pick autonomously?
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@ishika_bisht the agent picks the model based on the agent mode. You can choose to route between frontier, balanced, or free models.
@job_rietbergen@fmerianClaude and GPT-5 for reasoning-heavy tasks, Cursor for faster implementation. Would love to see Kilo Code route between them automatically based on task type.
also your comment highlights something key. some tools want to lock you into one interface, one way of doing things, adding friction to your workflow. @Kilo Code is different. the mission is to build an all-in-one, agentic AI platform that supports you wherever you are.
you choose how you work: your interface (a GUI editor, a CLI, or both), your model (500+ models available), your workflow. go give it a spin at kilo.ai/install
@Kilo Code is the leading open-source AI coding extension for @VS Code, with 1,000,000+ downloads.
@madalina_barbu@jobrietbergen also curious how you like working with AI coding agents? do you prefer to (a) have a look at the context usage (human-in-the-loop) or (b) review the outputs only (agent-first)?
The line level review comments on agent diffs is a really smart UX call. Feels like the missing link between AI wrote this and I actually trust this going to prod.
I'm hearing more and more about Kilo Code, and I have to say it genuinely makes me happy. At @Edgee we try to use as many coding agents as possible, and Kilo Code is really great. To be honest, I haven't tested it in VS Code yet (I mostly use the CLI), but I'll be doing that soon. One important question: how do you manage to limit token consumption? Do you have any specific optimization strategies (compression, compaction, output control...)?
We currently have auto-compaction, input cache (for those models that support it), and we’re experimenting with codebase indexing! There's also other things in the pipeline that will ship soon, so stay tuned.
We currently have auto-compaction, input cache (for those models that support it), and we’re experimenting with codebase indexing! There's also other things in the pipeline that will ship soon, so stay tuned.
@arya_marwaha Git worktrees are used to avoid conflicts among parallel agents, and latency largely depends on the speed of the model you're using.
So - if you need faster responses, you can freely switch to a faster model - and for more reasoning, switch to a more reasoning-intensive, frontier model!
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KiloClaw
@curiouskitty Good question!
We offer both local reviews in the extension and automated reviews on Github and GitLab PRs.
You can specify the strictness in both cases, so that you can filter down to the review points you actually care about.
How does the multi agent system comparison handle tokens ? does it run them all in the background simultaneously ? btw Congrats on the launch :)
KiloClaw
@farhan_nazir55 Thank you!
And yes, while you can bring your own keys or use local models, most users pay for inference via the Kilo Gateway, which lets you switch freely between models using one balance.
You just pay for token at provider costs - whatever Anthropic charges for Opus, and whatever OpenAI charges for GPT, that's what you pay!
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exactly - pay only for what you use. learn more about @Kilo Code pricing here: https://kilo.ai/pricing
Kilo Code
@farhan_nazir55 it runs them on separated git worktrees
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thanks for the support! help us spread the word on LinkedIn, repost this
Can you diff review across model comparisons? Like if three models each refactor something differently, can I review those diffs against each other instead of just against the original?
KiloClaw
@whetlan Yes exactly! You can do that with the new Agent Manager. Spin up 3 parallel agents to refactor something, choose a different model in each, and then review the individual, parallel diffs against the main branch!
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@brian_turcotte any AI models you'd recommend for such tasks?
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absolutely - this new @VS Code extension introduces an Agent Manager to let you run multiple, independent agents in separate tabs, give each one a role, an AI model, and use git worktrees so they never step on each other's code.
to learn more about the Agent Manager, you can read the docs here: https://kilo.ai/docs/automate/agent-manager
hope it helps!
Been using VS Code for most of my systems projects and the idea of running parallel agents on different parts of a codebase at once is something I've been waiting for. Curious how the diff reviewer handles C and low-level code — going to try it on my kernel prefetcher project this week.
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awesome! really looking forward to seeing what you're building with @Kilo Code
keep us posted, feel free to join the Discord server for additional support: kilo.ai/discord
happy shipping!
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also fun fact: parallel agents was one of the bets in v7 that took the longest to get right.
help us spread the word on X! repost this
Kilo Code
@rahul_mehta20 you can try out a few different models with agent manager on the same C task, and compare them against each other.
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@jobrietbergen any AI models you'd recommend for programming in C?
Product Hunt Wrapped 2025
Rebuilt for VS Code sounds handy. Parallel tool calls + that subagent thing has me curious - less sitting around for runs? I bounce between GPT/Claude, so multi-model compare in-editor could save tabs. Gonna try it on a throwaway repo tonight.
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@alexcloudstar lfg! you're in a safe place, @Kilo Code is the leading open-source AI coding extension for @VS Code with 1,000,000+ downloads ✌️
Kilo Code
@alexcloudstar sound great. did you manage to give it a spin? curious to your thoughts.
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yes, really looking forward to your thoughts! feel free to join the Discord server at kilo.ai/discord or/and open issues on GitHub: https://github.com/kilo-org/kilocode
Parallel agents and subagent delegation is a solid foundation — but how does Kilo Code decide which model to route a subtask to in multi-model mode? Is that user-defined or does the agent pick autonomously?
@ishika_bisht the agent picks the model based on the agent mode. You can choose to route between frontier, balanced, or free models.
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@ishika_bisht @job_rietbergen curious what are your preferred AI coding models
@job_rietbergen @fmerianClaude and GPT-5 for reasoning-heavy tasks, Cursor for faster implementation. Would love to see Kilo Code route between them automatically based on task type.
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@job_rietbergen @ishika_bisht great feedback!
also your comment highlights something key. some tools want to lock you into one interface, one way of doing things, adding friction to your workflow. @Kilo Code is different. the mission is to build an all-in-one, agentic AI platform that supports you wherever you are.
you choose how you work: your interface (a GUI editor, a CLI, or both), your model (500+ models available), your workflow. go give it a spin at kilo.ai/install
@Kilo Code is the leading open-source AI coding extension for @VS Code, with 1,000,000+ downloads.
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framing this!
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oh and fun fact: parallel agents was one of the bets in this release that took the longest to get right.
let's spread the word on X - repost this
Congratulations!
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thanks for the continuous support! please help us spread on LinkedIn, repost this
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Follow-up question: What should @Kilo Code launch next? See discussion here in /p/kilocode
Kilo Code
@madalina_barbu Thank you Madalina! Are you using any agentic coding tools already?
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@madalina_barbu @jobrietbergen also curious how you like working with AI coding agents? do you prefer to (a) have a look at the context usage (human-in-the-loop) or (b) review the outputs only (agent-first)?
see discussion in /p/kilocode
The line level review comments on agent diffs is a really smart UX call. Feels like the missing link between AI wrote this and I actually trust this going to prod.
KiloClaw
@carter_garcia I agree! And it helps to get a local review as a sanity check before shipping to a public repo
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IMHO That's a key point in this release. Review before approve, diff before commit. The right balance between capability and visibility.
Follow-up question: How do you like to work with AI coding agents? Join the discussion in /p/kilocode
Kilo Code
@carter_garcia yeah it's very helpful for my daily workflows
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strong +1! FYI you can read the docs for the full setup and options: kilo.ai/docs/automate/code-reviews
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Thank you! Best one-line review of this v7 launch so far.
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we just reposted it on X - lfg!
Edgee
I'm hearing more and more about Kilo Code, and I have to say it genuinely makes me happy. At @Edgee we try to use as many coding agents as possible, and Kilo Code is really great. To be honest, I haven't tested it in VS Code yet (I mostly use the CLI), but I'll be doing that soon.
One important question: how do you manage to limit token consumption? Do you have any specific optimization strategies (compression, compaction, output control...)?
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@sachamorard thank you! absolute fan of what you're building at @Edgee, your words mean the world.
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oh and please keep us posted how your experience goes with @Kilo Code! also curious what we should build/improve/fix cc @jobrietbergen @dax1
Kilo Code
@sachamorard really happy to hear you like the CLI and are keen to give our VS Code extension a try.
About your question. Check out this link: https://kilo.ai/docs/customize/context/context-condensing#cli
We currently have auto-compaction, input cache (for those models that support it), and we’re experimenting with codebase indexing! There's also other things in the pipeline that will ship soon, so stay tuned.
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@jobrietbergen looking forward to it 👀
Contrario
Congrats on the launch! How do you handle contention and latency?
KiloClaw
@arya_marwaha Git worktrees are used to avoid conflicts among parallel agents, and latency largely depends on the speed of the model you're using.
So - if you need faster responses, you can freely switch to a faster model - and for more reasoning, switch to a more reasoning-intensive, frontier model!
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@brian_turcotte any AI models you'd recommend in both cases?
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thanks for the support, Arya!
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also please help us spread the word on LinkedIn - repost this