Review AI edits like stacked PRs at generation time.
Every edit the agent proposes arrives with a built-in explanation and its own chat. Ask why, what it touches, or tell it to redo it. None of it derails the main agent.
Hey, I’m Vignesh, solo dev.
I built Handler, a Mac app for reviewing AI-generated code before it becomes one giant diff.
It works with Codex and OpenCode. While the agent is generating code, Handler breaks the work into smaller reviewable edits. Each edit comes with a short explanation: what changed, why it changed, and what it touches.
If something feels unclear, you can open a side chat on that specific edit and ask follow-ups like “why this approach?”, “what else does this affect?”, or “redo this part,” without derailing the main agent run.
The idea is similar to why stacked PRs are easier to review: smaller, understandable units. Handler applies that at AI generation time, before the change turns into one giant diff.
I built it because I noticed myself losing the mental model when agents gave me 300–500 line changes. Tests would pass, the diff would look reasonable, and I’d start skimming instead of really understanding what changed.
The bottleneck was no longer writing code. It was understanding the code fast enough to stay in control.
What Handler does:
- Explains each agent edit as it happens
- Lets you side-chat on a single edit without de-railing the main agent (fork chat)
- Lets you accept/reject changes edit by edit
- Runs on existing Codex and OpenCode setups
- Uses worktrees so parallel runs don’t collide
- Includes a built-in terminal with a Chrome DevTools-style feel, plus a native JSON viewer/builder for inspecting structured output
It’s not trying to replace review tools like CodeRabbit or Greptile. Those review after the fact. Handler sits earlier in the workflow, while the code is being generated, so you can keep the mental model instead of reconstructing it later.
I’ve been using it daily and can’t go back to merging agent changes blind.
Would love feedback from anyone using coding agents seriously.
About Handler on Product Hunt
“Review AI edits like stacked PRs at generation time.”
Handler launched on Product Hunt on June 3rd, 2026 and earned 86 upvotes and 1 comments, placing #18 on the daily leaderboard. Every edit the agent proposes arrives with a built-in explanation and its own chat. Ask why, what it touches, or tell it to redo it. None of it derails the main agent.
On the analytics side, Handler competes within Software Engineering and Development — topics that collectively have 48.4k followers on Product Hunt. The dashboard above tracks how Handler performed against the three products that launched closest to it on the same day.
Who hunted Handler?
Handler was hunted by Vignesh Warar. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Handler including community comment highlights and product details, visit the product overview.
Vignesh Warar