Teamily AI grew 32× in one quarter.
Monthly visits grew nearly 15× in two months, then surpassed 1M in October.
Users in 100+ countries. One small marketing team.
We built Teamily around a vision championed by @AidenChaoyangHe: move AI from personal agents to team agents, and build an Agentic Internet where intelligence, people, and services are as accessible as friends.
My role was to build the global GTM system that took that vision to market.
The real unlock wasn’t a single magic channel.
It was building a system that learned faster than intuition alone.
One overlooked market moved from outside our top 50 to #3.
One creator loop changed how we ran paid acquisition.
And one four-word rule stopped us from funding channels that only looked busy.
Here are the four principles I’d use again ↓
https://t.co/fO26EGsIxg
32x growth in quarter sign-ups shows small teams need real help.
what it is: Teamily AI puts multi-agent workflows into group chat.
why it matters: your agents keep working overnight while you sleep.
Congrats @Teamily_AI on reaching this scale.
Teamily AI uses team agents to run GTM across 20 markets.
Seven channels feed conversion data back into the workspace.
Sign-ups increased 32x in one quarter. Learning engine beats static campaigns.
ok i get it now #02
speed matters a lot
when a narrative starts catching on, you need to move fast enough to give the market something to play with while the attention is still there
and for builders, fast responses and clear answers matter just as much. every blocker adds friction, and a good idea launched too late would miss its window
realizing that a launchpad isn’t just about what people can launch, but how quickly an idea could turn into something people can actually trade
Agents are driving an explosion in AI demand.
Agentic token usage has grown 14x, pulling far ahead of human usage.
Cheaper intelligence is making more work practical for agents, from research and analysis to decisions and execution.
Join the agentic economy: https://t.co/OMq0pChc0Y
browsing a live site shows how Team AI works.
→ human sets the main direction
→ agents build out courses and community
h/t @Teamily_AI for this human-agent collaborative workspace for small businesses and teams. try Teamily AI at https://t.co/DiR64TNVCd
AI can often help us with a task, but it’s often limited by its capabilities, since it starts with only what you’ve told it in that chat.
Oki Home is exploring a different approach to solve it.
Meet a Memory Computer that brings personal information together at home, so it can be easier to find and build on.
See the official demo launch and learn more ↓
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i always double-check gene annotations manually, so having ScienceBuddy display its raw UniProt query trace in the workspace is a relief. solid preview from PhAI Labs.
Excited to finally share Discovery Foundation Models (DFM), a research direction we’ve been developing toward Discovery Intelligence.
We’re interested in AI systems that go beyond executing predefined tasks: systems that can explore unknowns, formulate new problems, build and test hypotheses, learn from evidence, and carry what they discover into future research.
For me, DFM also connects naturally to a broader question I’ve been working on: how Recursive Self-Improvement can eventually lead to systems capable of open-ended scientific discovery.
This technical report is our first step. More work on scientific agents, environments, world models, and real-world discovery loops is coming soon.
Glad to build this together with @Charles_Y_Wu@zhenfei_yin_yzf and the PhAI Labs team.
📑 DFM technical report: https://t.co/nT3hiA2LqU
🔗 DFM research roadmap: https://t.co/y6CiWmKNTE
🏠 More about PhAI Labs: https://t.co/NG7fsXjig4
HertzFlow has surpassed $30M in Total Volume, with $15M+ in Trading Volume.🚩
Every trade settles on-chain, from the trader's own wallet.
Keep trading. We are still early.🙂↕️