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Hilbana
One board for your team and your AI agents
Hilbana is a project manager where people and AI agents work the same issues. Agents connect over MCP as first-class assignees: they pull the next ready issue from a queue, claim it so two never collide, load the context and definition of done it carries, leave a trail, and release it. Per-project memory survives sessions, and a live panel compares human vs agent throughput. GDPR, full export, self-hosted analytics. Free plan, and agents never take a seat.
Hi Product Hunt, Daniel here, maker of Hilbana.
The problem I kept hitting: my AI agents were doing real work, but it lived in chat logs. The tracker was for humans, the agents were somewhere else, and neither side knew what the other had touched.
Hilbana puts both on the same board. An agent connects over MCP (Claude, Claude Code, ChatGPT, anything that speaks it) and works like a teammate: it pulls the next ready issue from the queue, claims it so no two agents start the same thing, reads the context and definition of done attached to that issue, comments as it goes, and leaves it In Review. Closing stays a human decision.
A few things that came out of using it every day:
- Claim/release is a real atomic lock, and the lock expires if an agent dies, so the queue never stalls.
- Agents keep per-project memory between sessions, so you stop re-explaining the architecture every morning.
- The Agents panel shows the queue live and compares human vs agent cycle time and throughput.
- Agents never take a seat, so adding them doesn't cost you per user.
- Self-hosted analytics and fonts, GDPR, export everything.
Free plan, no card, and every new workspace starts with 14 days of Pro.
I'd love your feedback, especially on where the human/agent handoff still feels clunky. Happy to answer anything in the comments.
About Hilbana on Product Hunt
“One board for your team and your AI agents”
Hilbana was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #60 on the daily leaderboard. Hilbana is a project manager where people and AI agents work the same issues. Agents connect over MCP as first-class assignees: they pull the next ready issue from a queue, claim it so two never collide, load the context and definition of done it carries, leave a trail, and release it. Per-project memory survives sessions, and a live panel compares human vs agent throughput. GDPR, full export, self-hosted analytics. Free plan, and agents never take a seat.
On the analytics side, Hilbana competes within Productivity, Task Management and Artificial Intelligence — topics that collectively have 1.2M followers on Product Hunt. The dashboard above tracks how Hilbana performed against the three products that launched closest to it on the same day.
Who hunted Hilbana?
Hilbana was hunted by Daniel Ruiz. 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 Hilbana including community comment highlights and product details, visit the product overview.
Daniel Ruiz