Kilo Code Reviewer - Automatic AI-powered code reviews the moment you open a PR
Automated code review agents that analyze pull requests, suggest improvements, catch bugs, and ensure code quality standards. Pick from 500+ models (Claude, GPT, Gemini, and several free options) to get instant feedback before merging.
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Hey Product Hunt! 👋
Brian, DevRel from Kilo here. We built @Kilo Code Code Reviewer to kill PR bottlenecks.
It runs automatically when you open a PR, catching security issues, performance problems, and style inconsistencies before your teammates even look at it, and offers comments and inline suggestions.
It's completely free with models like MiniMax M2.1 and GLM 4.7 - or use the latest from @Claude by Anthropic, @Gemini, or whatever you prefer from over 500 supported models.
What's your biggest code review pain point?
Humans in the Loop
LFG! keep up the great work ?makers 🐐
Flexprice
PR bottlenecks are real. Anything that catches issues before human review usually makes teams way faster. Curious how this fits into existing review workflows.
@shreya_chaurasia19 Definitely - my opinion is that for sensitive reviews (things that will go into production, breaking changes, etc), still require human eyes.
The point of AI Code Reviewer there, is to reduce the friction between an issue and a human reviewer seeing it.
For other projects (passion projects, docs, landing pages, etc.), where you don't necessarily need an extensive human review, Code Reviewer can automate the entire review workflow for you.
@shreya_chaurasia19 @brian_turcotte Is it checking for logic and syntax errors?
@brian_turcotte, congratulations on the launch!
@srbhr Thank you! Good to see you here :)
Humans in the Loop
@srbhr thanks for the continuous support, Saurabh! please help us spread the word on X
The Startup Catalyst Podcast - 01: Tarik Sultan, Founder of Sultan Ventures, Managing Partner XLR8UH
@brian_turcotte Fantastic work, crushing things at Kilo speed. Nobody wakes up wishing they had more code reviews to do today, Kilo helping make it a little (a lot) less painful
@luketucker No doubt! Thanks for the kind words!
Humans in the Loop
@brian_turcotte @luketucker framing this!
@brian_turcotte Very nice. Congrats on the launch!
Curious to know how it would compare against CodeRabbit
Humans in the Loop
@brian_turcotte @bekjon_ibragimov Great question.
TL,DR @Kilo Code is best for:
Model flexibility (500+ options)
Token-based pricing
No platform-switching friction
More details in this page -- hope it helps: kilo.ai/landing/coderabbit
Kilo Code
@Kilo Code Code Reviewer has become such a big part of my workflow. Can't imagine coding without it.
Humans in the Loop
@scobreit curious: what's your favorite model for code reviews?
@scobreit congrats on the launch. You can fully build out of Slack?
@austin_heaton Thank you! That's right - we now have Kilo for Slack, which lets you make full codebase changes by just tagging Kilo in a DM or shared channel. It'll make the change with Cloud Agents and produce a PR right there in Slack:
https://kilo.ai/features/slack
Humans in the Loop
@austin_heaton @brian_turcotte the all-in-one agentic engineering platform 💛🖤
As a data engineer, I’ve been using Kilo Code reviewer and it’s surprisingly data aware, not just code aware. It helps me catch pipeline changes that would only break dashboards later
Humans in the Loop
love it, Pedro! I just reshared it on X
what model are you using for code reviews?
@fmerian The biggest lever for me isn’t the model, it’s the inputs I provide. keep the memory-bank current with data related context, then add a clear PR description (I use a repeatable Kilo workflow and it takes about 10 seconds to get a detailed PR description ready). With those two in place, most reviewer setups outperform any data specific reviewer tools I’ve tried.
Humans in the Loop
great insights, thanks!
@pedro_heyerdahl Plus you can use any model, so you can pick those that excel at data tasks when you need to!
Humans in the Loop
@brian_turcotte any suggested model in particular for data tasks?
@fmerian Large context windows help there, so models like @Claude Code Sonnet 4.5 (1M Token Context Window) for high-reasoning and @MiniMax M2.1 (1M) for quicker implementations are my suggestion!
@brian_turcotte TIL!
That’s huge! Most AI coders stop at syntax.
I've been using KC for code reviews at Resume Matcher, and the experience has been amazing so far.
You can see it in action here: https://github.com/srbhr/Resume-Matcher/pull/638
Humans in the Loop
@srbhr real-life comparison! love it. thanks for the feedback, Saurabh 🙏
Humans in the Loop
@srbhr oh and qq: what should they launch next from your perspective? take the poll here in /p/kilocode: https://www.producthunt.com/p/kilocode/what-should-kilo-code-launch-next
@srbhr I love this project!
Humans in the Loop
had a blast working with the team on this new launch, introducing Kilo Code Reviewers -- AI-powered code reviews that understand your codebase and catch bugs before merging.
First launched on @Product Hunt about a year ago, @Kilo Code is now the most popular open-source coding agent, trusted by 1M+ developers.
S/O to @sytses @scobreit and team 👏👏
@fmerian It was great working with you on this as well! Excited for everyone to try Code Reviewer 💪🚀
Humans in the Loop
let's go!
This could be huge for junior devs on my team. They'd get feedback instantly instead of waiting for me to free up. Congrats, exciting to see this!
@irina_t_ Thanks for the kind words! That's exactly what we're seeing - it's not only a friction remover, it's also an education multiplier for new engineers.
Lancepilot
How does the AI understand our team’s specific coding standards and architectural decisions over time? (And can it learn from accepted vs. rejected suggestions?)
@istiakahmad You can give custom instructions and focus areas to highlight your team's standards and architectural decisions!
Humans in the Loop
@istiakahmad @brian_turcotte yes, and to learn more about focus areas, see the docs here. hope it helps!
Lancepilot
@iftekharahmad There are several ways to do this with Code Reviewer:
1. You can choose the review strictness between Strict, Balanced, and Lenient to adjust the severity of issue that Code Reviewer will flag
2. You can add custom instructions, to adjust the behavior/writing style of reviews
3. You can choose your Focus Area, selecting only the topics that matter to you or your team
Humans in the Loop
@iftekharahmad to learn more about the review styles and focus areas, see the docs here. hope it helps!
pr bottlenecks are real , especially on small teams where everyone's busy building.
quick question: does it learn from previous reviews? like if i keep ignoring certain suggestions, does it adapt over time?
also how it handles false positives. nothing worse than an ai reviewer flagging stuff that's actually fine.
@topfuelauto It'll keep the context of previous reviews on the sam ePR, and update dynamically within that PR.
If you want to teach it to forgo certain suggestions or understand your preferences, you can add custom instructions from the Kilo Dashboard!
Kilo Code
The amount of time this product helped me out is wild. I spin up PRs daily and let code reviewer take care of it before asking a human dev to do a final check.
Humans in the Loop
@jobrietbergen awesome! what's the best AI model from your perspective? in this thread, some people suggest @OpenAI's GPT-5.2 and @Gemini 3 for debugging tasks. genuinely curious