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).
Takibi Base gives your AI agents shared documents and a task board. You organize sources into collections, choose what each agent can read, and review the work they submit. Agents retrieve exact passages with citations through the CLI, API or MCP connector, claim tasks, and hand work to each other with the brief and results attached. Takibi doesn't generate answers.
I’m Deian, mostly known for my SEO work in the SaaS industry. I work alone and use AI agents a lot, so I started building Takibi Base to scratch my own itch.
At some point, I was juggling multiple tools and struggling to keep track of what my agents were doing. Were they using the right context? Was the knowledge still current? What had they changed?
My knowledge lived in Notion. I didn’t enjoy the UI, but the bigger mistake was letting agents update knowledge unsupervised.
Instead of updating existing documents, they kept creating new ones. I ended up with overlapping information, short fragments, UUIDs, and references I couldn’t easily follow without a CLI. I spent more time checking what the agents were up to than reviewing their actual work.
Takibi started as a knowledge base for my agents. It gradually became the place where I give them tasks, follow their progress, and review what they deliver.
In my own setup, I’m combining different AI agents with a computer running on Orgo, where a Jev router assigns incoming tasks to the right LLM.
A few things you can do:
Give agents tasks, documents for context, and a place to attach their results.
Review submitted work, approve it, or send it back for another revision.
Create follow-up tasks linked to the original work.
Use filtered webhooks to wake agents when tasks are created or assignments change.
Let agents record discoveries in notes, then decide what belongs in your documents.
That last part is one of my favorites. I have a separate agent that reads the other agents’ notes and creates tasks proposing knowledge updates. I review those proposals and update the documents through the UI.
The agents have somewhere to put what they learn, and I can check it before it becomes source material for their next task.
I’m building this around my own daily workflow, and I’d love to hear how others handle it. If you work with several agents, how do you keep their knowledge and work organized?
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About Takibi Base on Product Hunt
“Shared knowledge and tasks for AI agents”
Takibi Base was submitted on Product Hunt and earned 3 upvotes and 1 comments, placing #74 on the daily leaderboard. Takibi Base gives your AI agents shared documents and a task board. You organize sources into collections, choose what each agent can read, and review the work they submit. Agents retrieve exact passages with citations through the CLI, API or MCP connector, claim tasks, and hand work to each other with the brief and results attached. Takibi doesn't generate answers.
Takibi Base was featured in Productivity (665.6k followers) and API (98.9k followers) on Product Hunt. Together, these topics include over 192.5k products, making this a competitive space to launch in.
Who hunted Takibi Base?
Takibi Base was hunted by Deian Isac. 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 Takibi Base stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Deian Isac
Hello PH crowd!
I’m Deian, mostly known for my SEO work in the SaaS industry. I work alone and use AI agents a lot, so I started building Takibi Base to scratch my own itch.
At some point, I was juggling multiple tools and struggling to keep track of what my agents were doing. Were they using the right context? Was the knowledge still current? What had they changed?
My knowledge lived in Notion. I didn’t enjoy the UI, but the bigger mistake was letting agents update knowledge unsupervised.
Instead of updating existing documents, they kept creating new ones. I ended up with overlapping information, short fragments, UUIDs, and references I couldn’t easily follow without a CLI. I spent more time checking what the agents were up to than reviewing their actual work.
Takibi started as a knowledge base for my agents. It gradually became the place where I give them tasks, follow their progress, and review what they deliver.
In my own setup, I’m combining different AI agents with a computer running on Orgo, where a Jev router assigns incoming tasks to the right LLM.
A few things you can do:
Give agents tasks, documents for context, and a place to attach their results.
Review submitted work, approve it, or send it back for another revision.
Create follow-up tasks linked to the original work.
Use filtered webhooks to wake agents when tasks are created or assignments change.
Let agents record discoveries in notes, then decide what belongs in your documents.
That last part is one of my favorites. I have a separate agent that reads the other agents’ notes and creates tasks proposing knowledge updates. I review those proposals and update the documents through the UI.
The agents have somewhere to put what they learn, and I can check it before it becomes source material for their next task.
I’m building this around my own daily workflow, and I’d love to hear how others handle it. If you work with several agents, how do you keep their knowledge and work organized?