Loading video...

Video Failed to Load

There was a problem loading this video. This could be due to a temporary network issue or the video might be unavailable.

As we build tools that scale alongside rapid AI advancements, platform design must evolve to let the models do their best work. Kevin Hou on the evolution of @Antigravity at AI Engineer.

Google AI Developers

115,470 subscribers

27,228 views • 5 days ago •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

0 Comments

No comments available

Comments from the original post will appear here

Related Videos

Why did we build Antigravity? Our Head of Product Engineering Kevin Hou breaks this down in his keynote from AI Engineer

Why did we build Antigravity? Our Head of Product Engineering Kevin Hou breaks this down in his keynote from AI Engineer

Google Antigravity

68,764 views • 7 months ago

Put Google Flow Tools in the hands of creatives, and what do you get? “Personalization at a global scale,” according to MetaPuppet. Alongside MetaPuppet, we partnered with five incredible creatives to build custom Tools for you to explore, including Kat ⊷ the Poet Engineer and @Maestasdesign. Tools for creators, by creators. Hear their stories below:

Put Google Flow Tools in the hands of creatives, and what do you get? “Personalization at a global scale,” according to MetaPuppet. Alongside MetaPuppet, we partnered with five incredible creatives to build custom Tools for you to explore, including Kat ⊷ the Poet Engineer and @Maestasdesign. Tools for creators, by creators. Hear their stories below:

Google Flow

56,007 views • 1 month ago

Last week at #CES2026, our CEO Jensen Huang unveiled #NVIDIARubin, our new extreme-codesigned, six chip AI platform, alongside major advancements in open models and physical AI. On the show floor, we showcased some of the AI infrastructure and #acceleratedcomputing technologies that's powering the next era of AI. Thank you to everyone who stopped by the NVIDIA Showcase and we’ll see you next time. 👋

Last week at #CES2026, our CEO Jensen Huang unveiled #NVIDIARubin, our new extreme-codesigned, six chip AI platform, alongside major advancements in open models and physical AI. On the show floor, we showcased some of the AI infrastructure and #acceleratedcomputing technologies that's powering the next era of AI. Thank you to everyone who stopped by the NVIDIA Showcase and we’ll see you next time. 👋

NVIDIA AI Infrastructure

30,098 views • 5 months ago

Hi, we're Decagon :) The conversational AI platform to build, optimize, and scale AI agents that deliver concierge CX.

Hi, we're Decagon :) The conversational AI platform to build, optimize, and scale AI agents that deliver concierge CX.

Decagon

12,607 views • 8 months ago

We studied 27 of the fastest-growing AI & crypto tools… And built a platform where you can: - Use all the best AI models (including the best open source from Hugging Face 🤗), - Earn tokens from using AI, - Co-own and trade AI models and agents, - Stake on new AI creations and get rewards every day, Want early access? 👇 Comment “AI” and we’ll send you the demo. (First 250 only – must be following)

We studied 27 of the fastest-growing AI & crypto tools… And built a platform where you can: - Use all the best AI models (including the best open source from Hugging Face 🤗), - Earn tokens from using AI, - Co-own and trade AI models and agents, - Stake on new AI creations and get rewards every day, Want early access? 👇 Comment “AI” and we’ll send you the demo. (First 250 only – must be following)

Perspective AI

55,036 views • 1 year ago

You can now export your MagicPath designs straight into Google Antigravity for deeper code work. The best AI design tool + the best AI IDE. A ridiculously powerful loop.

You can now export your MagicPath designs straight into Google Antigravity for deeper code work. The best AI design tool + the best AI IDE. A ridiculously powerful loop.

Pietro Schirano

23,572 views • 7 months ago

💡Why Vana? “Ultimately, AI models are only as good as their training data. So if you want to build the best AI, you need the best data.” shares the vision behind Vana’s mission, centered on DataDAOs that aggregate specific datasets, reward data owners for their contributions and level up AI models with high-quality data🏆

💡Why Vana? “Ultimately, AI models are only as good as their training data. So if you want to build the best AI, you need the best data.” shares the vision behind Vana’s mission, centered on DataDAOs that aggregate specific datasets, reward data owners for their contributions and level up AI models with high-quality data🏆

vana

108,354 views • 1 year ago

Design tools evolve, but the craft remains. Forge (AI) - now live in UXPin.

Design tools evolve, but the craft remains. Forge (AI) - now live in UXPin.

UXPin

433,901 views • 2 months ago

Aion 1.0 Plan represents an evolution of what the Windows on-device AI platform is capable of at scale! Thrilled to partner with Unsloth AI on optimization across our silicon ecosystem. More #MSBuild news here:

Aion 1.0 Plan represents an evolution of what the Windows on-device AI platform is capable of at scale! Thrilled to partner with Unsloth AI on optimization across our silicon ecosystem. More #MSBuild news here:

Windows Developer

85,479 views • 1 month ago

The possibilities for AI-powered protein design are endless! In this case study we show how we used BindCraft to engineer a programmable maltose biosensor from scratch, including wet lab validation at Adaptyv of course. We envision a future where every biologist can make their own bespoke protein tools to investigate environmental samples, cell behaviour or create therapeutics. AI-based protein design can enable that future if powered by rapid wet lab validation. Once the cycle from design → test → application shrinks to weeks, the frontier explodes.

The possibilities for AI-powered protein design are endless! In this case study we show how we used BindCraft to engineer a programmable maltose biosensor from scratch, including wet lab validation at Adaptyv of course. We envision a future where every biologist can make their own bespoke protein tools to investigate environmental samples, cell behaviour or create therapeutics. AI-based protein design can enable that future if powered by rapid wet lab validation. Once the cycle from design → test → application shrinks to weeks, the frontier explodes.

Adaptyv Bio

52,094 views • 10 months ago

As agents take on longer-running work, engineering shifts to setting direction, reviewing work, and designing better systems around the models. Peter Steinberger 🦞 at AI Engineer

As agents take on longer-running work, engineering shifts to setting direction, reviewing work, and designing better systems around the models. Peter Steinberger 🦞 at AI Engineer

OpenAI Developers

128,659 views • 11 days ago

Which is the best AI Code Editor? 🐁 Cursor 📥 Trae 🧑‍🚀 Antigravity These tools go head to head on the only benchmark that actually matters...

Which is the best AI Code Editor? 🐁 Cursor 📥 Trae 🧑‍🚀 Antigravity These tools go head to head on the only benchmark that actually matters...

Jon Meyers

10,925 views • 6 months ago

Every company is racing to adopt AI, but many don't know where to start – let alone how to do it at scale. Hessian forward deploys into your business to map the work, then builds, operates and scales AI agents on their platform to get the job done. Congrats on the launch, Bao Nguyen, Tom, and James Smith!

Every company is racing to adopt AI, but many don't know where to start – let alone how to do it at scale. Hessian forward deploys into your business to map the work, then builds, operates and scales AI agents on their platform to get the job done. Congrats on the launch, Bao Nguyen, Tom, and James Smith!

Y Combinator

15,737 views • 1 month ago

Introducing Lab: A full-stack platform for training your own agentic models Build, evaluate and train on your own environments at scale without managing the underlying infrastructure. Giving everyone their own frontier AI lab.

Introducing Lab: A full-stack platform for training your own agentic models Build, evaluate and train on your own environments at scale without managing the underlying infrastructure. Giving everyone their own frontier AI lab.

Prime Intellect

3,112,755 views • 5 months ago

Scott Wu says Karpathy's idea of jagged intelligence explains why humans and AI work best together. AI is superhuman at some tasks, shockingly weak at others. “As long as that tail exists of what humans can do, that's what we'll own.” We still decide what to build. In the end, software engineering is just telling the computer what to do.

Scott Wu says Karpathy's idea of jagged intelligence explains why humans and AI work best together. AI is superhuman at some tasks, shockingly weak at others. “As long as that tail exists of what humans can do, that's what we'll own.” We still decide what to build. In the end, software engineering is just telling the computer what to do.

vitrupo

38,496 views • 1 year ago

Sometimes your best ideas start on paper. Watch Antigravity take a sketch, implement the design, and then build into the app.

Sometimes your best ideas start on paper. Watch Antigravity take a sketch, implement the design, and then build into the app.

Google Antigravity

196,574 views • 4 months ago

💡Can robots autonomously design their own tools and figure out how to use them? We present VLMgineer 🛠️, a framework that leverages Vision Language Models with Evolutionary Search to automatically generate and refine physical tool designs alongside corresponding robot action plans. ✨ VLMgineer can fully automate tool and action design with AI-driven physical creativity. No human intervention. No pre-defined templates or few-shot examples. ✨ VLMgineer outperforms human-specified designs and existing everyday tools. ✨ We let the VLM fully decide how to evolve designs. Deep dive with me: 🧵

💡Can robots autonomously design their own tools and figure out how to use them? We present VLMgineer 🛠️, a framework that leverages Vision Language Models with Evolutionary Search to automatically generate and refine physical tool designs alongside corresponding robot action plans. ✨ VLMgineer can fully automate tool and action design with AI-driven physical creativity. No human intervention. No pre-defined templates or few-shot examples. ✨ VLMgineer outperforms human-specified designs and existing everyday tools. ✨ We let the VLM fully decide how to evolve designs. Deep dive with me: 🧵

Junyao Shi

29,764 views • 1 year ago

Our co-founder Pratyush Kumar highlighted Sarvam's "contrarian bet" of being a full-stack AI platform. That means we build every layer: the models, how they run (inference), how agents work with each other (orchestration), and the AI applications people use. This lets us build AI that actually works for India's unique context and diverse language needs.

Our co-founder Pratyush Kumar highlighted Sarvam's "contrarian bet" of being a full-stack AI platform. That means we build every layer: the models, how they run (inference), how agents work with each other (orchestration), and the AI applications people use. This lets us build AI that actually works for India's unique context and diverse language needs.

Sarvam AI

16,310 views • 7 months ago

some advice for designing tools in the age of ai: 1. embrace ambiguity — ai tools work best when you're comfortable with not having full control. leave room for emergence and surprise. 2. focus on the human-ai collaboration model — design the interaction patterns, not just the outputs. what's the back-and-forth like? how do humans guide the ai? 3. design for iteration, not perfection — ai outputs are rarely perfect the first time. design systems that make refinement natural and easy. 4. think in systems, not features — ai changes fast, so build adaptable foundations rather than specific implementations that will break. 5. protect against the uncanny valley — either make it obviously ai-generated or indistinguishable from human work. the middle ground feels weird. 6. consider the invisible costs — ai has computational, environmental, and social costs that aren't immediately visible but matter. 7. design for augmentation, not replacement — the best ai tools make humans more capable rather than trying to replace them. 8. build in feedback loops — systems that learn from user interactions get better over time. the thing is, we're all figuring this out together. the design patterns for ai are still being invented. it's like the early web days — exciting, messy, and full of possibilities.

some advice for designing tools in the age of ai: 1. embrace ambiguity — ai tools work best when you're comfortable with not having full control. leave room for emergence and surprise. 2. focus on the human-ai collaboration model — design the interaction patterns, not just the outputs. what's the back-and-forth like? how do humans guide the ai? 3. design for iteration, not perfection — ai outputs are rarely perfect the first time. design systems that make refinement natural and easy. 4. think in systems, not features — ai changes fast, so build adaptable foundations rather than specific implementations that will break. 5. protect against the uncanny valley — either make it obviously ai-generated or indistinguishable from human work. the middle ground feels weird. 6. consider the invisible costs — ai has computational, environmental, and social costs that aren't immediately visible but matter. 7. design for augmentation, not replacement — the best ai tools make humans more capable rather than trying to replace them. 8. build in feedback loops — systems that learn from user interactions get better over time. the thing is, we're all figuring this out together. the design patterns for ai are still being invented. it's like the early web days — exciting, messy, and full of possibilities.

Ryo Lu

30,781 views • 1 year ago

“In Africa, we are no longer satisfied to be passive consumers of technology, we want to build, deploy that technology at scale as well.” President Kagame at the AI for Good Global Summit 2026. #RBANews

“In Africa, we are no longer satisfied to be passive consumers of technology, we want to build, deploy that technology at scale as well.” President Kagame at the AI for Good Global Summit 2026. #RBANews

Rwanda Broadcasting Agency (RBA)

18,165 views • 3 days ago