Humalike - Give your AI agents the social intelligence they're missing
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Today's models are capable enough. Smart enough. Fast enough. But we still feel they don’t fit in the room. Humalike is building the behavioral infrastructure for humanlike AI agents. The social skills & proactiveness your agents have been missing. APIs, models, benchmarks.
Replies
How are you measuring "humanlike" in your benchmarks, and do the APIs let you tune how proactive an agent gets so it doesn't end up nudging users nonstop?
@serdardvi1 Hi, the bar for making AI more social is low enough that you can see the difference with naked eye. On top of that we have benchmarks related to specific capabilities, like adapting to local social norms: https://arxiv.org/pdf/2606.14600
Social Learning component helps agent understand and adapt to specific group. If it's not enough you can always tune it on your end, turn-taking component accepts prompt on how it should behave.
Humalike
@serdardvi1 Norms / Turn-taking / Theory of Mind are the pillars that enable Humalike to not have the "nudging users nonstop" problem.
For Humalike, when you say AI agents are missing “social intelligence,” is the core use case more about agents communicating with end users, collaborating with other agents, or handling public/community channels? The topic mix includes Developer Tools, Marketing & Sales, Design & Creative, and Social & Community, so I’m wondering who you see as the first user with the sharpest pain.
@mia_qiao Agent interacting with multiple humans is use case that we care about the most. We can argue that if you master this scenario, then 1:1 also gets better, and maybe agent-to-agent collaboration also improves, but we are not focusing on agent to agent at all.
Humalike
@mia_qiao Hey Mia! Agents communicating with end users. Agent-to-agent collaboration is not our core use case right now (more niche / less useful use cases). Core 2 ICP are (today.): 1. Any company that has agents communicating in any way with Humans (user experience is bad generally). 2. Devs with/want companions/personal agents
"APIs, models, benchmarks" implies you have a way to measure social intelligence in agents, which is actually the hardest part of this whole space to get right. What does a benchmark for humanlike behavior look like here, who's evaluating it, and how do you avoid the benchmark just measuring surface-level mimicry like filler words and pacing rather than actual social appropriateness?
@ansari_adin Agree, evaluating social intelligence is the hardest part. And we don't have the full holy grail benchmark for social intelligence yet. We are tackling this problem and released a paper about inferring local social norms in LLMs, it's not testing social intelligence, but model with social intelligence will do well on this benchmark, and it's not trivial to game it.
paper link: https://arxiv.org/pdf/2606.14600
P.S. there are some benchmarks that claim to measure social intelligence (e.g. Sotopia) and we are not fan of those. They make big claims without being rigorous
Congrats @mcarmonas and team! The origin story of the community manager that everyone instantly clocked as a bot is way too real, no amount of prompt engineering ever fixes that vibe.
Humalike
@vaishnavi_goel :)))) totally. Tysm for the support Vaishnavi!