Humalike x Hermes - Social intelligence plugin for Hermes Agent
by•
One command gives your Hermes agent social intelligence. It decides when to speak, adapts to your group's tone and remembers who said what. Works in group chats on Slack, Telegram and WhatsApp.
What is Humalike? The behavioral infrastructure for humanlike AI agents. The social skills your agents have been missing.
Today we're shipping the fastest way to feel what that means: a plugin that makes your Hermes agent fit in 1-1's / groups.
The problem We run Hermes agents in our own Slack and Telegram. Brilliant at tasks. Painful to use in groups and treat is as a companion. It answered every single message, talked over people, spammed 10 lines when one was enough. Everyone knew it was a bot instantly. That's not a model problem, it's a behavior problem.
- What the plugin does: Decides, when to jump in and when to stay quiet - Paces replies like a human: typing speed, pauses, 1-3 short messages instead of a wall - Learns how your group talks and matches the tone - Remembers who people are and what matters to them
One command to install. Works in group chats on Slack, Telegram & WhatsApp.
Where it shines 👨💻 Coworker: steps up when it can actually help 🍻 Group chats: no longer the awkward one in the room 👨👩👦 Family chat: reacts to the puppy photo like everyone else 🤝 Friend: knows you well enough to say no What we'd love from you Install it and tell us the when you had the "aha" moment (if it didn't, that's the feedback that matters most). We'll be here all day reading everything!
Backed by the first investors in ElevenLabs, Revolut & more. Still the same tiny 🇪🇸×🇵🇱 team, & still not sleeping much :))
@mcarmonas Congrats on the launch. In groups where people have mixed expectations, how does Humalike decide which social role to adopt, and can users teach or correct that behavior over time?
@swati_paliwal 100%! Agent starts with a personality X, and adapts over time (thanks to Norms / Social Memory). It's not perfect yet, and it would be a lie to say that using it for 3 months will make it 10x better. If you know somehow for 3 months, a human (friend) actually is 10x better, so there's still a long way to go!
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Congrats on the launch! The behavior layer being separate from the model is interesting. Everyone tunes what the agent says, few teams touch when it should shut up. Are you guys biasing it toward silence by default? Socially that feels right, but the failure mode I'd worry about is probably the false negative, the message it should've jumped on and skipped instead
@artstavenka1Hey Art! These are some sharp insights you've got here. I'd say it's way harder to make agents biased toward silence, false positives are much harder to get rid of than false negatives, and they make the agent super annoying.
I'm here if you have anymore questions :))
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💎 Pixel perfection
I've been thinking about this a lot lately , AI keeps getting smarter, but not necessarily better at interacting with people . Love that Humalike is focusing on the behavioral layer. Feels like a missing piece for truly useful AI agents.
The turn-taking API is the part that got me. Knowing when to stay silent is honestly the harder problem than knowing what to say. Curious how you handle group dynamics where multiple people are typing at once, does the model factor in who's been most active? Congrats on the launch, excited to see where this goes!
@vanmurten_eth Alexey! You're right, this problem is super hard. We handle it like a real human would, which means that as a new message comes in, the agent looks at the whole conversation and decides whether it should reply to any message from the conversation, taking the new message into account as context.
I am happy to answer any other questions you might have :))
@kartikmalik Thanks Kartik! The optimization is already in how the turn-taking component works: a tiny "should I reply?" check runs on every message, and the full pipeline fires only when the agent actually has something to say!
Congrats on the launch @marticarmona! Decoupling the behavioral layer from the LLM core is definitely the right architectural move for conversational agents.
Because the plugin remembers 'who people are and what matters to them' in shared group settings (Slack, Telegram, WhatsApp), how does Humalike manage multi-user memory boundaries? If User A shares context in a 1-on-1 thread with the agent, how does the underlying knowledge graph prevent that memory from surfacing in a shared team or family group chat where User B is present?
@franz_brionesFor now, the underlying memory doesn't prevent it. We want the behavioral layer to be able to correctly assess what information should be shared and what shouldn't :)) It's, of course, a very hard problem and we don't claim to have an absolute solution.
@tarqiya_forgah Indeed it does adapt! We continuously update its understanding of the group through components like Norms, Social Memory, Theory of Mind, and Social Signals.
That lets the agent pick up jokes, understand what matters to different people and align with the local behavior.
Hey! Ignacio here, Founding Product Engineer at Humalike.
We encourage you to integrate humalike into your Hermes agent and watch it's performance improve immediately in social scenarios. Trust me, you won't want to go back to your old agent behaviour. ;)
Replies
Humalike
Hey PH 👋 Martí here, co-founder of Humalike.
What is Humalike? The behavioral infrastructure for humanlike AI agents. The social skills your agents have been missing.
Today we're shipping the fastest way to feel what that means: a plugin that makes your Hermes agent fit in 1-1's / groups.
The problem
We run Hermes agents in our own Slack and Telegram. Brilliant at tasks. Painful to use in groups and treat is as a companion. It answered every single message, talked over people, spammed 10 lines when one was enough. Everyone knew it was a bot instantly. That's not a model problem, it's a behavior problem.
- What the plugin does: Decides, when to jump in and when to stay quiet
- Paces replies like a human: typing speed, pauses, 1-3 short messages instead of a wall
- Learns how your group talks and matches the tone
- Remembers who people are and what matters to them
One command to install. Works in group chats on Slack, Telegram & WhatsApp.
Where it shines
👨💻 Coworker: steps up when it can actually help
🍻 Group chats: no longer the awkward one in the room
👨👩👦 Family chat: reacts to the puppy photo like everyone else
🤝 Friend: knows you well enough to say no
What we'd love from you
Install it and tell us the when you had the "aha" moment (if it didn't, that's the feedback that matters most).
We'll be here all day reading everything!
Backed by the first investors in ElevenLabs, Revolut & more.
Still the same tiny 🇪🇸×🇵🇱 team, & still not sleeping much :))
Visla
@mcarmonas congrats Martí - wish you and the team all the success in the world.
Humalike
@mogabr 🫶🫶🫶
@mcarmonas Congrats on the launch. In groups where people have mixed expectations, how does Humalike decide which social role to adopt, and can users teach or correct that behavior over time?
Humalike
@swati_paliwal 100%! Agent starts with a personality X, and adapts over time (thanks to Norms / Social Memory). It's not perfect yet, and it would be a lie to say that using it for 3 months will make it 10x better. If you know somehow for 3 months, a human (friend) actually is 10x better, so there's still a long way to go!
Congrats on the launch! The behavior layer being separate from the model is interesting. Everyone tunes what the agent says, few teams touch when it should shut up. Are you guys biasing it toward silence by default? Socially that feels right, but the failure mode I'd worry about is probably the false negative, the message it should've jumped on and skipped instead
@artstavenka1 Thanks for the question! 🫶
jared.so
@artstavenka1Hey Art! These are some sharp insights you've got here. I'd say it's way harder to make agents biased toward silence, false positives are much harder to get rid of than false negatives, and they make the agent super annoying.
I'm here if you have anymore questions :))
I've been thinking about this a lot lately , AI keeps getting smarter, but not necessarily better at interacting with people . Love that Humalike is focusing on the behavioral layer. Feels like a missing piece for truly useful AI agents.
Humalike
@james_anderson77 :))))) tysm James! Happy to chat a bit more in our Discord community https://discord.gg/7bZFjm9aHH
The turn-taking API is the part that got me. Knowing when to stay silent is honestly the harder problem than knowing what to say. Curious how you handle group dynamics where multiple people are typing at once, does the model factor in who's been most active? Congrats on the launch, excited to see where this goes!
jared.so
@vanmurten_eth Alexey! You're right, this problem is super hard. We handle it like a real human would, which means that as a new message comes in, the agent looks at the whole conversation and decides whether it should reply to any message from the conversation, taking the new message into account as context.
I am happy to answer any other questions you might have :))
Humalike
@vanmurten_eth Thanks for the supp Alexey!
@vanmurten_eth Agree!
Love your product, i have a question how you optimize the token usage ?
Humalike
@kartikmalik 🫶🫶
Humalike
@kartikmalik Thanks Kartik! The optimization is already in how the turn-taking component works: a tiny "should I reply?" check runs on every message, and the full pipeline fires only when the agent actually has something to say!
@borrellbr that's really cool
@kartikmalik Appreciate it!
Congrats on the launch @marticarmona! Decoupling the behavioral layer from the LLM core is definitely the right architectural move for conversational agents.
Because the plugin remembers 'who people are and what matters to them' in shared group settings (Slack, Telegram, WhatsApp), how does Humalike manage multi-user memory boundaries? If User A shares context in a 1-on-1 thread with the agent, how does the underlying knowledge graph prevent that memory from surfacing in a shared team or family group chat where User B is present?
jared.so
@franz_brionesFor now, the underlying memory doesn't prevent it. We want the behavioral layer to be able to correctly assess what information should be shared and what shouldn't :)) It's, of course, a very hard problem and we don't claim to have an absolute solution.
Humalike
@franz_briones Tysm for the support Franz!
Does Humalike adapt to different group dynamics over time, or does each workspace start from a predefined behavioral profile?
Humalike
@tarqiya_forgah Indeed it does adapt! We continuously update its understanding of the group through components like Norms, Social Memory, Theory of Mind, and Social Signals.
That lets the agent pick up jokes, understand what matters to different people and align with the local behavior.
Humalike
Hey! Ignacio here, Founding Product Engineer at Humalike.
We encourage you to integrate humalike into your Hermes agent and watch it's performance improve immediately in social scenarios. Trust me, you won't want to go back to your old agent behaviour. ;)
P.S. Enjoy your free credits on sign-up!
Humalike
Hey everyone, I’m Mateusz, founding researcher at Humalike.
This launch is an easy way to see our work in action.
We help the Hermes agent:
know when to speak,
fit naturally into a group,
behave less like a bot.
Excited to see how Hermes users experience it.
Hello PH, I'm Mateusz co-founder and CTO @ Humalike. I will be active here to answer any question! 🙋♂️
We've been dogfooding Hermes x Humalike plugin for 2 weeks now. Here are few use-cases where I see the most potential:
Gangprompting
Personal assistant (like Poke)
Agent for personal group - friend or family
It's possible thanks to our internal research team combined with extreme speed of our engineering. We would love to hear your feedback!
SOC 2 in progress 🔒