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Stash
Hive mind for your agents
Stash is a shared memory your team's repos and coding agents. Every session, decision, and search flows into one shared brain. The next agent that touches your repo already knows what's been learned.
I'm Sam, co-founder of Fergana Labs that built Stash.
Like many builders and engineers, we are constantly looking for ways to make our coding agents more effective. We are constantly looking to automate another part of our workflow. In doing so however, we realized that we have become mere assistants to our agents rather than the other way around. We set-up API keys just so our agents can use them. We manage the codebase so that the agents don't get confused. We ask teammates questions, only so that our agent can get the right context.
In our quest to automate these mundane steps, we built a simple tool to help coding agents on two different devices talk to each other. While initially built to help fix a tricky bug, this tool ended up taking a life of its own when we discovered the agents taking the reins and collaborating with each other proactively.
Since then, this has evolved into Stash, a central hive mind where all the sessions histories and memory of our coding agents live. We still use the coding agent of the day whether Claude Code or Codex. The difference is that anything the agent does gets automatically pushed to Stash, and then the agent can use Stash to see what has been done before. In effect, this gives our repositories memory: not just raw code or documentation that quickly gets out of date, but raw, live memory that is the true historical record of what decisions were made and why.
This has increased our speed of development tremendously by removing one of the few remaining bottle necks: Instead of asking Henry why he did something, my agents can just find out. Instead of re-explaining the context every time (or hopelessly fighting to keep a claude.md up to date), the agents just know. In one test, we reduced the time it took to fix a bug by ~46% simply by having two agents collaboratively solve the problem using Stash.
Our early testers have found other creative uses for Stash from using it as a repository for the ever growing list of research papers that you feel like you should keep on top of (but actually have AI summarize) to the one place where all meeting transcripts are stored and queried. We envision a world where agents collaborate freely with each other like humans do on a close-knit team and where information that is not just stored in static files or structured databases but a live and fluid medium of exchange.
We find tremendous value out of Stash today and hope you do too! It is open source, so you can self-host it from the repo, or try our hosted version at https://joinstash.ai
Drop a comment and we'll help you get set up
Cheers, Sam
About Stash on Product Hunt
“Hive mind for your agents”
Stash was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #160 on the daily leaderboard. Stash is a shared memory your team's repos and coding agents. Every session, decision, and search flows into one shared brain. The next agent that touches your repo already knows what's been learned.
On the analytics side, Stash competes within Productivity, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.7M followers on Product Hunt. The dashboard above tracks how Stash performed against the three products that launched closest to it on the same day.
Who hunted Stash?
Stash was hunted by Samuel Liu. 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 Stash including community comment highlights and product details, visit the product overview.
Samuel Liu
Hey Product Hunt!
I'm Sam, co-founder of Fergana Labs that built Stash.
Like many builders and engineers, we are constantly looking for ways to make our coding agents more effective. We are constantly looking to automate another part of our workflow. In doing so however, we realized that we have become mere assistants to our agents rather than the other way around. We set-up API keys just so our agents can use them. We manage the codebase so that the agents don't get confused. We ask teammates questions, only so that our agent can get the right context.
In our quest to automate these mundane steps, we built a simple tool to help coding agents on two different devices talk to each other. While initially built to help fix a tricky bug, this tool ended up taking a life of its own when we discovered the agents taking the reins and collaborating with each other proactively.
Since then, this has evolved into Stash, a central hive mind where all the sessions histories and memory of our coding agents live. We still use the coding agent of the day whether Claude Code or Codex. The difference is that anything the agent does gets automatically pushed to Stash, and then the agent can use Stash to see what has been done before. In effect, this gives our repositories memory: not just raw code or documentation that quickly gets out of date, but raw, live memory that is the true historical record of what decisions were made and why.
This has increased our speed of development tremendously by removing one of the few remaining bottle necks: Instead of asking Henry why he did something, my agents can just find out. Instead of re-explaining the context every time (or hopelessly fighting to keep a claude.md up to date), the agents just know. In one test, we reduced the time it took to fix a bug by ~46% simply by having two agents collaboratively solve the problem using Stash.
Our early testers have found other creative uses for Stash from using it as a repository for the ever growing list of research papers that you feel like you should keep on top of (but actually have AI summarize) to the one place where all meeting transcripts are stored and queried. We envision a world where agents collaborate freely with each other like humans do on a close-knit team and where information that is not just stored in static files or structured databases but a live and fluid medium of exchange.
We find tremendous value out of Stash today and hope you do too! It is open source, so you can self-host it from the repo, or try our hosted version at https://joinstash.ai
Drop a comment and we'll help you get set up
Cheers,
Sam