This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
StateCarry helps you return to interrupted coding work without replaying the whole history. It looks at the project as it exists now, along with relevant Codex conversations, and helps you answer three questions: What was I doing? What changed? Where do I continue? Close the project. Come back tomorrow. Pick it up again.
I built StateCarry because I kept running into the same problem while working across multiple projects and AI coding sessions: coming back was expensive.
The code was still there. The commits were still there. The conversations were still there.
But I had lost the meaning of the current state.
What was I doing? What changed? What still mattered? Where could I continue?
I kept spending the first part of every resumed session reconstructing work I had already done.
So I started StateCarry with a simple question:
What if returning to interrupted work felt more like continuing than reconstructing?
StateCarry looks at the project as it exists now, along with relevant Codex conversations, and helps you understand what the work was about and where you can continue.
This is an early public beta. I’m releasing it now because I want to find out whether this problem is specific to my workflow, or something other developers working across repositories and AI coding sessions run into too.
If you try it, I’d especially love to hear:
When you come back to a project after a few days, what do you usually have to figure out first?
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About StateCarry on Product Hunt
“Resume coding where you left off.”
StateCarry was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #37 on the daily leaderboard. StateCarry helps you return to interrupted coding work without replaying the whole history. It looks at the project as it exists now, along with relevant Codex conversations, and helps you answer three questions: What was I doing? What changed? Where do I continue? Close the project. Come back tomorrow. Pick it up again.
StateCarry was featured in Productivity (661.2k followers), Open Source (68.9k followers), Developer Tools (519.8k followers), GitHub (41.4k followers) and OpenAI Day (39 followers) on Product Hunt. Together, these topics include over 293.2k products, making this a competitive space to launch in.
Who hunted StateCarry?
StateCarry was hunted by ThreeLight. 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.
Want to see how StateCarry stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
ThreeLight
I built StateCarry because I kept running into the same problem while working across multiple projects and AI coding sessions: coming back was expensive.
The code was still there. The commits were still there. The conversations were still there.
But I had lost the meaning of the current state.
What was I doing? What changed? What still mattered? Where could I continue?
I kept spending the first part of every resumed session reconstructing work I had already done.
So I started StateCarry with a simple question:
What if returning to interrupted work felt more like continuing than reconstructing?
StateCarry looks at the project as it exists now, along with relevant Codex conversations, and helps you understand what the work was about and where you can continue.
This is an early public beta. I’m releasing it now because I want to find out whether this problem is specific to my workflow, or something other developers working across repositories and AI coding sessions run into too.
If you try it, I’d especially love to hear:
When you come back to a project after a few days, what do you usually have to figure out first?