Finyuus is a code-first platform for building, running, and governing AI workflows. It introduces a small indentation-based DSL for composing agents, tools, guards, human approvals, and nested workflows — then runs them on Temporal with retries, cancellation, and replayability. Unlike visual builders, workflows are stored as text for Git-based review and diffs. Unlike prompt chains, every run is durable, versioned, observable via Langfuse, and governable through guards and human approvals.
Hey Product Hunt! 👋
I kept running into the same problem while building AI apps: the AI logic — prompts, tool calls, retries, guards, approval waits — kept getting tangled into my application code. At one point I was maintaining 300-line system prompts in the same codebase as my iPhone app's buttons and screens. Every small behavior change meant rebuilding and redeploying the whole app.
There's a useful parallel with how apps treat databases. Applications talk to databases through SQL, so data logic lives independently from app code. I wanted that same separation for AI: define, version, operate, and modify agents, prompts, tools, guards, and workflows independently from the apps that use them.
Finyuus is what I've built. It's a small indentation-based DSL for composing AI workflows, backed by Temporal for durable execution (retries, cancellation, long-running waits, child workflows), Langfuse for tracing and cost reporting, and a dashboard for authoring, running, and reviewing everything. Workflows are stored as text, so they get Git history, PRs, and readable diffs — something visual builders lose at scale.
It's open source and runs fully locally with Docker (Temporal, ClickHouse, MinIO (or s3), Langfuse, Redis all included). I'd love feedback on the DSL ergonomics, the governance model (guards + human approvals), and what you'd want next.
Happy to dig into any part of the architecture. 🙏
Keeping workflows as plain text instead of locking everything into a visual builder is probably my favorite part. Git diffs and PR reviews are hard to give up once a project grows.
the durability and git-diffable execution graph is the genuinely useful part, that's a real gap in a lot of prompt-chain tools. the new DSL is the part I'd push back on though - Temporal already has SDKs in Python and TypeScript that get you retries, replay and versioning without asking anyone to learn new indentation rules. what does the language buy you over a thin Python wrapper around the same guards and approvals, besides a smaller surface to write the interpreter for? "governable" and "diffable" don't obviously require a new syntax, they require the underlying execution model you already built.
Temporal, ClickHouse, MinIO, Langfuse and Redis to run a prompt is the part I'd push on. Nobody spins that up on a Tuesday afternoon, and a Tuesday afternoon is how these things actually get adopted. The SQL analogy cuts the other way too, SQL won because it was one language across every engine, and a DSL that runs on exactly one runtime is a lock in people can feel. I'd ship a single binary mode that fakes durability in SQLite so someone can write a workflow in ten minutes and only meet Temporal when they need it.
About Finyuus on Product Hunt
“A code-first language for durable, governed AI workflows”
Finyuus launched on Product Hunt on August 4th, 2026 and earned 89 upvotes and 12 comments, placing #15 on the daily leaderboard. Finyuus is a code-first platform for building, running, and governing AI workflows. It introduces a small indentation-based DSL for composing agents, tools, guards, human approvals, and nested workflows — then runs them on Temporal with retries, cancellation, and replayability. Unlike visual builders, workflows are stored as text for Git-based review and diffs. Unlike prompt chains, every run is durable, versioned, observable via Langfuse, and governable through guards and human approvals.
Finyuus was featured in Open Source (68.7k followers), Developer Tools (517.2k followers), Artificial Intelligence (475.5k followers) and GitHub (41.4k followers) on Product Hunt. Together, these topics include over 231.8k products, making this a competitive space to launch in.
Who hunted Finyuus?
Finyuus was hunted by marius ndini. 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.
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