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Gemini 3.5 Flash 🤝 Google Antigravity Watch how the model deploys multiple subagents to design and build an entire city.

80,940 次观看 • 4 个月前 •via X (Twitter)

34 条评论

Google DeepMind 的头像
Google DeepMind4 个月前

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Hüseyin Örskaya 的头像
Hüseyin Örskaya4 个月前

@antigravity Everyone's eyeing the city layout, but the real win's the subagent orchestration. If it can't handle conflicting constraints between agents, it's just a fancy simulation.

Vance Lever 的头像
Vance Lever4 个月前

Used subagents to design our entire go-to-market structure last quarter. Main agent assigned territories, built the comp plan, hired 6 SDRs, and allocated budget. Our CFO found out when payroll ran. She said 'none of these people are real.' They are not real. The quota attainment is still impressive.

Julie Loves Tech 的头像
Julie Loves Tech4 个月前

@antigravity watching subagents coordinate to design and build an entire city in real time is the kind of demo that makes you put your phone down and just stare. this is the Google that people kept saying was sleeping. turns out they were just loading 🤭

Jahanzaib Ahmed 的头像
Jahanzaib Ahmed4 个月前

@antigravity The coordination layer is kinda the whole bet. I'm curious how it handles rollback when one subagent's output breaks another agent's constraints.

Logika Agency 的头像
Logika Agency4 个月前

@antigravity To actually achieve this how much token usage is needed really ? I mean I assume you would hit limits fast with all these sub agents ?

Avi Yadav  的头像
Avi Yadav 4 个月前

@antigravity New UI is 🤮

Hodler 的头像
Hodler4 个月前

@antigravity wow, this is cool af.

Abhinav Shrivastava 的头像
Abhinav Shrivastava4 个月前

@antigravity The interesting part isn’t even the benchmark jump anymore. It’s that models are starting to behave less like “chatbots” and more like operating systems coordinating specialized agents in parallel. We’re slowly moving from prompting intelligence → directing intelligence.

AIOfficeTR 的头像
AIOfficeTR4 个月前

@antigravity

teze 的头像
teze4 个月前

@antigravity hey , like this

Finbar Quinn 的头像
Finbar Quinn4 个月前

@antigravity im sorry but this example is so bad, no? like its generating almost nonsense. im sure the tool is usefull for something ... but this?

CallMeMASTA_IamYourSenpai 的头像
CallMeMASTA_IamYourSenpai4 个月前

@antigravity Gemini 3.5 flash+ code execution tools = god tier , in ai studio it auto test and do auto benchmark its amazing and efficient

matata 的头像
matata4 个月前

@antigravity Love google

Andrew Kirby 的头像
Andrew Kirby4 个月前

@antigravity Was hopeful for antigravity but lack of extensions (like giving me access to Claude code) make it useless for my needs. Downloaded update, struggled as the help gave outdated advice, then deleted.

Luciano Henriques | 🟩🟨🟦⬜️ RJ - 🇧🇷 的头像
Luciano Henriques | 🟩🟨🟦⬜️ RJ - 🇧🇷4 个月前

@antigravity Incrível de verdade! Muitos ainda não se deram conta da grandiosidade e poder do Gemini 3.5 Flash.

Gerard Sans | Axiom 🇬🇧 的头像
Gerard Sans | Axiom 🇬🇧4 个月前

@antigravity

LongLimbsLenore 的头像
LongLimbsLenore4 个月前

@antigravity "What if we shoved AI into every aspect of your fucking lives!"

Second Foundation 的头像
Second Foundation4 个月前

@antigravity Please resolve the limits issue. The project can't be completed in three hours. Tokens are disappearing faster than people expect. Compare this to the Codex. @GoogleDeepMind

Spencer 24/7 的头像
Spencer 24/74 个月前

@antigravity AI is moving WAY faster than most people expected.

AI Mastery Guide 的头像
AI Mastery Guide4 个月前

@antigravity We went from autocomplete to building cities. The jump in capability this year alone is hard to process

cedric 的头像
cedric4 个月前

@antigravity Sick multi subagents demo

Hershal Rao 的头像
Hershal Rao4 个月前

@antigravity can’t wait for the subagents to start unionizing

Dawid Maka 的头像
Dawid Maka4 个月前

@antigravity hmmm? nie ogarnia

Kris Kashtanova 的头像
Kris Kashtanova4 个月前

@antigravity Antigravity is cool

Felix 的头像
Felix24 天前

@antigravity The subagent orchestration is the real story here — specialised agents with scoped contexts beat one monolithic prompt for spatial planning. Curious how they handle inter-agent state sync and failure recovery at scale. Agentic architecture > raw parameter count.

Faheem | FrontierMind AI 的头像
Faheem | FrontierMind AI4 个月前

@antigravity The multi-agent city build is a strong demo because it shows planning, delegation and execution together. That is where these models start feeling useful for real projects.

Eclipse 🌖 的头像
Eclipse 🌖4 个月前

@antigravity multi-agent orchestration at this fidelity is the real unlock — single-model bottlenecks are the bigger constraint than raw parameter count.

Jason Fleagle 的头像
Jason Fleagle4 个月前

@antigravity Subagents are where the demo starts to resemble real work. The operator question becomes coordination: who owns the plan, how conflicts get resolved, what evidence each subagent returns, and how the final result is judged before anything hits production.

lodl 的头像
lodl4 个月前

@antigravity Sorry, but splitting the old application into two separate ones wasn't a great move. Installing both Antigravity 2.0 and Antigravity IDE now just gives me exactly what we had before in a single application.

Rubbish Talk 的头像
Rubbish Talk4 个月前

@antigravity Looks like Google fixed housing problem.

Ganesh Rajendran 的头像
Ganesh Rajendran4 个月前

@antigravity Please retain Gemini CLI

Whois Me 的头像
Whois Me4 个月前

@antigravity 3.5 flash it's impressive but, hey! I was never reaching the limit for the previous model. Now I did it in record time. (Plus user)

Kekko D’Amato 的头像
Kekko D’Amato4 个月前

@antigravity Subagent orchestration for complex spatial tasks is where things get genuinely interesting. Not "AI writes code" interesting, but "AI models understand dependencies and parallel workstreams" interesting. That's a different level of reasoning.

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