Launched this week
Agently
Your whole stack, running itself!
553 followers
Your whole stack, running itself!
553 followers
Every other tool answers, retrieves, or runs brittle rules. Agently holds your whole company in context and does the work. 100+ connectors flow into one brain that never forgets. It links a Stripe event to a Slack thread to a Linear ticket on its own. When something needs doing, Jarvis routes it to an agent that runs it end to end: triggered, running, shipped. The work lands without you, nothing falls through the cracks. Connecting takes minutes. The layer between today's AI and tomorrow's AGI.
This is clever. What does Jarvis do when it can't confidently route a task to any agent?
@dhiraj_patel5 The architecture does not allow for it. The subagents are spun up based of the task that needs to be done. Jarvis injects the context into them and details the role and desired objective.
@dhiraj_patel5 Routing always resolves, because Jarvis dynamically spins up a subagent for the task instead of matching against a static set, so "no agent fits" isn't a failure state. Confidence gating lives at the subagent's actions, not the routing, high-confidence reversible work runs, anything ambiguous or consequential routes back to you.
Congrats on shipping @omarships! How do you handle messy and keep growing context?
@nicklaunches Thanks 🙏
On messy: when signals are weak or conflicting, it degrades to asking, not guessing, so bad input never becomes a confident action.
On growing: connecting sources is table stakes, but every correction and decision you make gets encoded, so it keeps getting sharper long after your stack is wired up.
@nicklaunches Messy: we link on hard signals (shared IDs/domains), and when a match is weak we flag instead of forcing it.
Growing: as more episodes land, the graph's relationship density climbs and every human correction becomes a durable signal, so the curve bends up past "everything connected." It's not just more data, it's more resolved connections.
Hey Product Hunt 👋,
I'm Omar, founder of Agently.dev.
Here's the bet I'd stake the company on: one person should be able to run a whole company without being its memory, and a small team should ship like a big one. That only happens if the agent stops being the product. The agent is the commodity. The brain is the product.
Most agents are stateless: grab data, do a task, forget. Fancy macros. Ours runs on a persistent, entity-resolved model of your whole company, what each thing is, why it matters, when it's relevant, how it connects, across every tool, never forgetting. A living graph, not a chat history, so work lands instead of waiting on you.
Jarvis reads that brain, decides what needs doing, and dispatches event-triggered agents that act back through 100+ two-way connectors, so the work closes instead of piling on you: triggered, running, shipped. Real artifacts, not summaries. The hard part everyone stops at is keeping that model live, correct, and safe to write back through.
It compounds. Months in, your brain knows your company in a way even your co-founder cant, and you come off the critical path. That's the moat.
The teams already running on it go from solo founders to enterprises. This is where work is going. Become part of the future. 🧠
Learnetto
@omarships Looks super cool. Will give it a try!
@hrishio Looking forward to your feedback. In our vibe building era
@omarships Super excited for this launch. First company of its kind
Hey Product Hunt 👋, I'm Ahmad,
Co-founder and CTO of Agently.dev
Here's what nobody warns you about when you build agents: entity resolution. The same customer shows up in Stripe, Slack, and Linear under three different names, and if your model of the company gets that wrong, everything downstream is wrong too. Agent demos are easy now. The hard part is what the agent knows.
We spent most of 8 months there: one living automated temporal knowledge graph of the whole company, kept correct enough that agents can safely write back through it. Our 100+ connectors are two-way, so agents don't just read your tools, they act back in them. Jarvis reads that graph, decides what needs doing, and dispatches agents on what it sees, not prompt by prompt.
"Do I trust the write-back" was the first question every beta cohort asked. Fair question, and parts of this are still early.
Happy to go deep on architecture, entity resolution, how Jarvis dispatches, or write-back safety. Ask away. 🛠
@ahmadhajj Building a the future for founders!
Congrats on the launch, @omarships ! The bi-temporal / contradiction-at-write-time answers in this thread are more rigorous than most of what's out there. "The source's clock is a claim, not the truth" is a good line.
One thing I keep running into from the knowledge side: the brain can only reconcile what actually flows through a connector. But a lot of the highest-value context never touches a system. It's the answer someone gave in a DM, or the reason a decision got made that nobody wrote down. Does the brain have a path for capturing that, or is the bet that enough of it leaks into Slack/Linear to be inferable?
Either way, rooting for you guys 🚀
@doganakbulut Agently runs on Claude (Anthropic's Opus 4.8), and we match the right model to each job under the hood — so you don't have to pick or wire anything up.
Curious though: is model choice something you'd want to control, or more a "just make it work" thing for you? 🙌
@doganakbulut @ahmadhajj Yup what Ahmad said is correct, we do run multiple models throughout the process but the model you interact with Jarvis is Opus. If you would like to BYOK or run it with your own model, do let us know
@ahmadhajj Upvoted Agently, bold promise with "runs itself." Curious how the onboarding sequence proves that in the first few days after signup.
@alex_iliescu only one way to find out 👀