Ayven drives your agenda. It means observing, cutting the work into pieces your team can take one at a time, putting an owner and a date on each, and filing them in Jira or YouTrack. Then it runs, tracks and talks about the work for weeks: asking whoever knows, waiting, chasing silence, moving work when someone is away. Your team answers in Slack and the board moves. Planning stops being the barrier and you ship your agenda like crazy.
We didn't start with a product. We started with an ANNOYANCE. Agents were impressive while you were talking to them, and then, as soon as you stopped typing, they effectively disappeared.
You'd put one in Slack and end up with another bot sitting in a channel waiting for someone to tell it what to do.
You don't prompt your teammates.
So the real problem was never, "How do we make the model smarter?" It was: how do you give a language model a spine? Something that lets it chain call after call, across days and months, reaching out to different people, all without a human babysitting it.
Sounds impossible if you know from experience just how complex chaining LLM calls can be. Three things turned out to matter, and we learned each one the painful way.
1. What a piece of work actually is.
Small enough that it can be validated, iterated, executed and closed 99.9% of the time.
Too big and the agent starts hallucinating. Too small and it loses all semantic meaning.
2. Resolving time should be first-class.
A lot of work in a team is essentially waiting.
Waiting isn't failure. It's the norm. And that happens to be one of the things LLM agents are worst at. Ayven reasons about when it should wake up next, EVERY SINGLE TIME, across thousands of runs a week.
It is about recognising a deadline, annual leave, or when a teammate has gone quiet. The async gap is hard to nail down. Ayven does that.
3. What is the base unit of a fact.
In a team, things change constantly. Someone changes their mind, a deadline moves, a customer replies, a meeting gets cancelled. An agent would treat information that was true two days ago as gospel. Change is the critical signal, and that was difficult to implement when teamwork is so unpredictable. Ayven makes sure the right things change with it.
The magic moment that wowed us, and made us decide to launch Ayven: we gave Ayven the agenda for September. Nothing else. The next thing we knew, the board was full, and accurate to our plans. It put together the pieces of what execution would look like.
Later, I asked: "What's stopping us from launching on Product Hunt?" Ayven then told me about every dependencies that I did not previously know. Nobody wrote that answer. It was just the work being captured in its truest, current state.
There is a lot more to Ayven that we haven't covered here.
Talk to us if you want this deployed in your own environment. Tell us what you want it connected to.
Really interesting Launch, the workflow on agenda mapping and tracking is a perfect target.. good wishes for its success Howard and team..
"resolving time should be first-class" is the sharpest line in that post. waiting being the norm rather than a failure state is exactly the thing most task tools get wrong, they treat an open ticket as something going wrong instead of something just not due yet. the rerouting-when-someone's-away answer below is the part I'd want more detail on though - does the reassigned person get a say before the work lands on them, or does Ayven just move it and tell them after? autonomous reassignment without a check-in is the kind of thing that works great until it hands someone a deadline they didn't know was coming.
The Slack connection sounds practical. It's easier to keep work moving when people can reply where they already chat.
Can Ayven adjust deadlines automatically when someone on the team is away?
Chasing people for updates takes up so much time. Having something handle those reminders would be a real help.
About Ayven on Product Hunt
“Carries and drives your team's agenda”
Ayven launched on Product Hunt on October 11th, 2026 and earned 95 upvotes and 14 comments, placing #8 on the daily leaderboard. Ayven drives your agenda. It means observing, cutting the work into pieces your team can take one at a time, putting an owner and a date on each, and filing them in Jira or YouTrack. Then it runs, tracks and talks about the work for weeks: asking whoever knows, waiting, chasing silence, moving work when someone is away. Your team answers in Slack and the board moves. Planning stops being the barrier and you ship your agenda like crazy.
Ayven was featured in Productivity (662.8k followers), Messaging (52k followers) and Artificial Intelligence (480.7k followers) on Product Hunt. Together, these topics include over 309.4k products, making this a competitive space to launch in.
Who hunted Ayven?
Ayven was hunted by Howard Chen. 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 Ayven stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Howard Chen
Howard here, founder of Alknoma.
We didn't start with a product. We started with an ANNOYANCE. Agents were impressive while you were talking to them, and then, as soon as you stopped typing, they effectively disappeared.
You'd put one in Slack and end up with another bot sitting in a channel waiting for someone to tell it what to do.
You don't prompt your teammates.
So the real problem was never, "How do we make the model smarter?" It was: how do you give a language model a spine? Something that lets it chain call after call, across days and months, reaching out to different people, all without a human babysitting it.
Sounds impossible if you know from experience just how complex chaining LLM calls can be. Three things turned out to matter, and we learned each one the painful way.
1. What a piece of work actually is.
Small enough that it can be validated, iterated, executed and closed 99.9% of the time.
Too big and the agent starts hallucinating. Too small and it loses all semantic meaning.
2. Resolving time should be first-class.
A lot of work in a team is essentially waiting.
Waiting isn't failure. It's the norm. And that happens to be one of the things LLM agents are worst at. Ayven reasons about when it should wake up next, EVERY SINGLE TIME, across thousands of runs a week.
It is about recognising a deadline, annual leave, or when a teammate has gone quiet. The async gap is hard to nail down. Ayven does that.
3. What is the base unit of a fact.
In a team, things change constantly. Someone changes their mind, a deadline moves, a customer replies, a meeting gets cancelled. An agent would treat information that was true two days ago as gospel. Change is the critical signal, and that was difficult to implement when teamwork is so unpredictable. Ayven makes sure the right things change with it.
The magic moment that wowed us, and made us decide to launch Ayven: we gave Ayven the agenda for September. Nothing else. The next thing we knew, the board was full, and accurate to our plans. It put together the pieces of what execution would look like.
Later, I asked: "What's stopping us from launching on Product Hunt?" Ayven then told me about every dependencies that I did not previously know. Nobody wrote that answer. It was just the work being captured in its truest, current state.
There is a lot more to Ayven that we haven't covered here.
Talk to us if you want this deployed in your own environment. Tell us what you want it connected to.
Ask me anything :)