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Hey HN! We're Charles and Dean, and we're building Stage: a code review tool that guides you through reading a PR step by step, instead of piecing together a giant diff.Here's a demo video: https://www.tella.tv/video/stage-demo-1pph.
You can play around with some example PRs here: https://stagereview.app/explore.Teams are moving faster than ever with AI these days, but more and more engineers are merging changes that they don't really understand. The bottleneck isn't writing code anymore, it's reviewing it.We're two engineers who got frustrated with GitHub's UI for code review. As coding agents took off, we saw our PR backlog pile up faster than we could handle. Not only that, the PRs themselves were getting larger and harder to understand, and we found ourselves spending most of our time trying to build a mental model of what a PR was actually doing.We built Stage to make reviewing a PR feel more like reading chapters of a book, not an unorganized set of paragraphs. We use it every day now, not just to review each other's code but also our own, and at this point we can't really imagine going back to the old GitHub UI.What Stage does: when a PR is opened, Stage groups the changes into small, logical "chapters". These chapters get ordered in the way that makes most sense to read. For each chapter, Stage tells you what changed and specific things to double check. Once you review all the chapters, you're done reviewing the PR.You can sign in to Stage with your GitHub account and everything is synced seamlessly (commenting, approving etc.) so it fits into the workflows you're already used to.What we're not building: a code review bot like CodeRabbit or Greptile. These tools are great for catching bugs (and we use them ourselves!) but at the end of the day humans are responsible for what gets shipped. It's clear that reviewing code hasn't scaled the same way that writing did, and they (we!) need better tooling to keep up with the onslaught of AI generated code, which is only going to grow.We've had a lot of fun building this and are excited to take it further. If you're like us and are also tired of using GitHub for reviewing PRs, we'd love for you to try it out and tell us what you think!
Show HN: Stage – Putting humans back in control of code review
Puts 'humans back in control of code review' by guiding reviewers through changes in logical 'chapters,' addressing the bottleneck of reviewing large, AI-generated PRs and improving comprehension.
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AI Executive Synthesis
Puts 'humans back in control of code review' by guiding reviewers through changes in logical 'chapters,' addressing the bottleneck of reviewing large, AI-generated PRs and improving comprehension.
Stage directly confronts the escalating challenge of code review, exacerbated by the proliferation of AI-generated code. By structuring PRs into logical 'chapters' and guiding reviewers, it aims to restore human comprehension and control over the review process, which GitHub's traditional UI struggles with. This addresses a critical bottleneck in modern development workflows where code generation outpaces human review capacity. Positioned as a human-centric alternative to AI-powered review bots, Stage targets engineering teams struggling with large, complex PRs, offering a solution to maintain code quality and understanding in an AI-accelerated development landscape. This enhances developer productivity and code integrity.
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What is Stage – Putting humans back in control of code review?
Stage – Putting humans back in control of code review is analyzed by our AI as: Puts 'humans back in control of code review' by guiding reviewers through changes in logical 'chapters,' addressing the bottleneck of reviewing large, AI-generated PRs and improving comprehension.. It focuses on Stage directly confronts the escalating challenge of code review, exacerbated by the proliferation of AI-generated code. By structuring PRs into lo...
Where did Stage – Putting humans back in control of code review originate?
Data for Stage – Putting humans back in control of code review was aggregated directly from the Hacker News community ecosystem, representing raw developer and early-adopter sentiment.
When was Stage – Putting humans back in control of code review publicly launched?
The initial public indexing or launch date for Stage – Putting humans back in control of code review within our tracked developer communities was recorded on April 17, 2026.
How popular is Stage – Putting humans back in control of code review?
Stage – Putting humans back in control of code review has achieved measurable traction, logging over 105 traction score and facilitating 93 recorded discussions or engagements.
Which technical categories define Stage – Putting humans back in control of code review?
Based on metadata extraction, Stage – Putting humans back in control of code review is categorized under topics such as: code review tool, PR, giant diff, coding agents.
What are some commercial alternatives to Stage – Putting humans back in control of code review?
Our semantic intelligence engine identifies potential commercial alternatives in the SaaS space, such as Databerry, which offers overlapping value propositions.
How does the creator describe Stage – Putting humans back in control of code review?
The original author or development team describes the product as follows: "Hey HN! We're Charles and Dean, and we're building Stage: a code review tool that guides you through reading a PR step by step, instead of piecing together a giant diff.Here's a demo video: https:/..."
Community Voice & Feedback
(i find)the right way to read a PR can differ a lot from project to project. it's not just about context, or syntax, or workflow...sometimes the best entry point is the PR description or an external ticket. sometimes you need to read the code first to understand the reasoning behind the changes. sometimes the diff itself is fine, but you have to go back several PRs to see how the codebase got into its current state.i guess like everyone said here, there no right way to do it.but i enjoy the video and the project, kudos ;)
So, when I code review, I have a super simple Cursor command that "orients" me in the PR:* where does the change sit from a user perspective?* what are the bookends of the scope?* how big is the PR?* etc.Once I'm "in" and understand what it does, I pepper the AI with questions:* Why did the author do this?* I dont understand this?* This looks funky, can you have a look?* etc.The more questions I ask, the more the AI will (essentially) go "oh, I didn't think of that, in fact, looks like the issue was way more serious than I first thought, let me investigate". The more I ask, the more issues AI finds, the more issues AI finds, the more issues I find. There's no shortcuts to quality control -- the human drives the process, AI is merely (and I hate to use this term but I will) a...force multiplier.
Haven't tried it yet, but it looks neat!My pain points with PRs where people vibe coded something is a bit different though:
- I'd like to get an idea how they prompted and developed the PR.
- I want to see if for example they just took everything the AI gave them or if they interacted with it critically
- I want to see some convincing proof that they tested it, e.g. manually. I.e. along the lines of what Simon describes here: https://simonwillison.net/2025/Dec/18/code-proven-to-work/
- I want to see an AI doing a review as well
- I'd like to get an idea how they prompted and developed the PR.
- I want to see if for example they just took everything the AI gave them or if they interacted with it critically
- I want to see some convincing proof that they tested it, e.g. manually. I.e. along the lines of what Simon describes here: https://simonwillison.net/2025/Dec/18/code-proven-to-work/
- I want to see an AI doing a review as well
If I'm reviewing AI code, I don't want AI summaries. I want to be able to read the code and understand what it does. If I can't do that, the code the AI output isn't very good. In theory, your AI changes should be smaller chunks just like a real developer would do.
Maybe I'm missing something obvious, but if I was going to have my team use this, I'd want someone to answer the following questionIf AI is good enough to explain what the change is and call out what to focus on in the review, then why isn't AI good enough to just do the review itself?I understand that the goal of this is to ensure there's still a human in the review cycle, but the problem I see is that suggestions will quickly turn into todo lists. Devs will read the summary, look at the what to review section, and stop reviewing code outside of things called out in the what to focus on section. If that's true, it means customers need to be able to trust that the AI has enough context to generate accurate summaries and suggestions. If the AI is able to generate accurate summaries and suggestions, then why can't we trust it to just do the review itself?I'm not saying that to shit on the product, because I do get the logic behind it, but I think that's a question you should have a prepared answer for since I feel like I can't be the only one thinking that.
> more and more engineers are merging changes that they don't really understandYou cannot solve this problem by adding more AI on top. If lack of understanding is the problem, moving people even further away will only worsen the situation.
Looks kind of neat like devon.ai review / reviewstack crossover. But as i tell every of the dozens projects trying to make a commercial review tool: i would rather spend a week vibe copying this than onboarding a tool i have to pay for and am at the mercy of whoever made it. Its just over for selling saas tools like this. For agents i also need this local not on someones cloud. Its just a matter of time until someone does it.
It's an interesting idea, but I feel like it's missing almost the most important thing; the context of the change itself. When I review a change, it's almost never just about the actual code changes, but reviewing it in the context of what was initially asked, and how it relates to that.Your solution here seems to exclusively surface "what" changes, but it's impossible for me to know if it's right or not, unless I also see the "how" first and/or together with the change itself. So the same problem remains, except instead of reviewing in git/GitHub/gerrit + figure out the documents/resources that lays out the task itself, I still have to switch and confirm things between the two.
> Stage automatically analyzes the diff, clusters related changes, and generates chapters.Isn't that what commits are for? I see no reason for adding this as an after-thought. If the committers (whether human or LLM) are well-behaved, this info is already available in the PR.
Totally different part of the reviewing experience, but I would love to see PR comments (or any revisions really) be automatically synced back to the context coding agents have about a codebase or engineer. There’s no reason nowadays for an engineer or a team of engineers to make the same code quality mistake twice. We manually maintain our agents.md with codebase conventions, etc, but it’d be great not to have to do that.
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