Welcome back to How I AI. I'm Claraveville, product leader and AI obsessive here on a mission to help you build better with these new tools. Today was the first day of Google IO, Google's flagship event where they launched so many products, so many features, so many names of products, some of which are live and some of which we're going to try live on today's show. In this mini app, we'll start from most technical to most fun, talk a little bit about the releases that caught my eye today at Google IO, and see if the promise of some new consumer grade creative features really live up to the hype of the event. Let's get to it. This episode is brought to you by Magic Patterns. Today's engineers use cursor and claude code to ship features in hours that used to take weeks. If you're a designer or PM, you've probably felt a shift, too. the pressure to move faster, validate sooner, and keep up with the team that's operating at a completely different speed. You've already tried AI prototyping tools to close that gap. But if your prototypes don't look like your actual product, it doesn't matter how fast you can build, you still end up redrawing it by hand. Magic Patterns takes your product team from idea to production and works from your real design system. When you build a prototype, what you get back actually looks like your product. You'll validate faster, get alignment sooner, and when it's time to build, engineers can connect your prototype to cursor or cloud code with the Magic Patterns MCP to pick up where you left off. Your team has their AI advantage. Make magic patterns yours. Try it today at magicpatterns.com/howi aai. There was so much interesting product launch today, but I want to start with the foundation stuff, the models. Today, Google announced Gemini 3.5 family of models, including Gemini 3.5 Flash, their fastest, smartest coding model. What's unique about Gemini 35 fast? It is both rivals the intelligence of some of our favorite coding models 5.5 opus 47 even 46 but it is four times as fast as those models and so if you look at 3.5 flash you're getting according to Google's benchmarks a super smart model sort of a codeex 47 model if you like 47 at the speed of something much more like their 3.1 flash model so it's super super fast and super smart. If you look at the benchmarks, they're really focused on the agentic capabilities of this model. And if you trace this all the way through the announcements today, you'll see that Google is really going fullbore into agents. It feels a little bit like catchup. Some of the features that they released, as you'll see, are things that you're used to seeing in some of the products from Anthropic and OpenAI, but applied, I think, in two different aspects. one is with the speed of the flash models that we know and love and two with much more of a creative consumer bent to it. And so while we're going to start this episode talking a little bit about the 3.5 models in the coding products, we're going to end this episode testing this model and a couple other models on more creative use cases. But again, Gemini 35 available across the product portfolio with Google and really focused on coding and in particular agentic capabilities at speed as well as the thing that we all know Gemini is really good at which is multimodal. I have always told people if you are working with files, videos, any sort of transformative work where you have to go from one modality um maybe document to another modality. Gemini models are really really good at handling files. I love it for handling videos. And you can see here the benchmarks compared to its peers both the previous Gemini 3 family of models as well as its peers from the Claude and GPT models themselves. really exceed the benchmarks in multimodal and according to them some of their agentic capabilities and then it's fast. We love something fast.

Now, how are you going to use this model? Well, if you're a developer, you're going to use it in an IDE or in an agentic coding harness. And so, you know, you don't hear people talk a lot about anti-gravity, but when I do hear people talk about anti-gravity, they say it's quite good. Anti-gravity is Google's IDE, Agentic IDE, and they announced several features. So, when you read about these features, you're really going to feel like Google's playing catch-up to in particular codecs. You can see a lot of the concepts that were built into anti-gravity are concepts that we've seen in particular in codecs. But let's go through them one by one. First, I want to pop up anti-gravity so you all can see it. Here, a couple changes. This is called anti-gravity 2.0. 0 a couple changes they made in the desktop app. One is they've brought the idea of projects into anti-gravity. So these are sort of like folder constrained environments or workspaces that you're working on. I pulled in the chat prd um website app here. And then they've also added in scheduled tasks. So this UI looks very similar to what we've seen in the codeex app. projects along the side, scheduled tasks along the side, and schedule tasks are exactly what you would think they would be, a name, a project that you're working on, a schedule, and a prompt that runs on a regular cron. So, nothing mind-blowing here, but again, you're going to see that Gemini 35 flash um high reasoning and low reasoning, both very fast for a limited time, are available here in the anti-gravity IDE. The other thing that was announced was the anti-gravity CLI. So again, a clawed code or codeex CLI style interface for coding. This is one where you can open up your terminal and work with it outside the IDE. Very similar form factor to what we've been working with. So again, you're going to kind of feel like this is a little bit of catch-up to what the other providers have been doing in terms of agentic coding, but it looks nice and we're defaulted again to Gemini 35 flash high and so it should be a fast experience. Let's just test this really quickly. This is on my website and I have a feature for the blog that I wanted to work on and that is our blog generator for our podcast. So, as I said at the beginning, the Gemini models are very good at video. And so, one of the things that we do is we put the videos from these podcasts into an admin tool on the marketing site and it generates blog post for us. But I want to be able to do that agentically. So, let's see how fast Gemini 35 responds to that request. And I'm just going to use um I'm going to type in and I'm going to say we have a blog generator UI at admin tools. I want to turn this into an API that an AI agent can use instead of a web UI for our team. Please build. So that should go ahead just very similar to these other tools that we're used to. look at directories, ask me for permissions. I'm going to say yes and always allow. And it's going to run through and hopefully write some quick code. Now, I'm not noticing it is particularly faster, but let's see how long it takes to get to an outcome. You know, it doesn't feel that much faster to me, but we'll see how long it takes to generate. I want to show you a couple other features of anti-gravity that was released today. So again going on this theme of playing a little bit of catch-up with claude code and codeex. The core agent features that were released today in anti-gravity are sub aents. Again the ability for the main agent to spawn off a sub agent to do a specific task. One use case that people love of anti-gravity, especially coming from Google, is the browser sub agent, which has always been available, but now different sub aents could be spawned by the main agent to work on coding tasks. This is something that you've seen in cloud code and codecs again, but now available in anti-gravity. There's also hooks. So, you can use hooks at different parts of the life cycle of your agent. If you don't know what hooks are, there are little events emitted every time your agentic harness kicks off a tool or every time it completes a turn or every time a new session is started and you can hook into those events and do something on demand. And so now anti-gravity has the ability to configure those hooks. We have the idea of projects which I told you about and showed you in the desktop app. There are native git work trees and local local development environments. Again, these are all things that we have seen in codecs. So, nothing super surprising here. The ones that I really like that I want you to spend a couple minutes on while we're letting anti-gravity in the IDE cook are these slash commands. Now, I love some slash commands, especially in codecs. My favorite one has been slash goal. the ability to define a goal and basically have your agent, you know, bash his head against that problem over and over until it solves solves a problem or meets the goal. So, anti-gravity has shipped a slashgoal slash command which will allow an agent to do a longunning task against a goal. But, there are actually a couple other really fun slashcomands that I want to call out that I think I'm going to be testing over the next couple weeks and probably give you all my feedback on. So this first one is this grill me slashcomand. I love this because you know Claude code has this question and answer tool where it'll like clarify for you. It's very polite. It's very anthropic coded. You know if you make a PRD or a spec in claude code and then it needs clarification, it's going to go ahead and ask you a couple questions and clarify. This seems like a much more aggressive version of that. It's called grill me. So what this does is this command the agent will ask clarification questions back and really get to the heart of what your requirements are and how it's going to work. Now the question is is this actually as hardcore as the slash command communicates or is this just a cute way to differentiate against the question and answer tool? We'll see. Maybe we can spin it up in the anti-gravity IDE and test it. The other slash commands are SLC schedule. So be able to schedule those tasks as we showed in the UI as well as use the browser. And so again, anti-gravity in particular is pretty good at using an autonomous agent to test in the browser. There's an ability to kick that off using the slash browser tool. So a lot of updates here. Again, the TLDDR coding's faster, the model's faster, it's caught up to codeex, and it has a couple interesting slash commands. Let's go back to anti-gravity in the IDE and see if it really built something as fast as it claims. Okay, it edited several features and it went ahead and created a programmatic API endpoint. It has API key authentication that it can use. It can be trigger. It can trigger the generation of visual workflows which is what we want. And um the agent can now provide a featured image URL. So it has created all these documents pretty fast. I am curious what this slash artifact command will show us. So um if I click open, it will show me the documentation on how it works. Very nice, fast, kind of what I would expect from a coding agent. Nothing too special here. Again, I think we're really just playing catch-up. But with the speed of the Gemini 35 flash model, I'll be curious to see if more of us reach for anti-gravity, especially for wall scope tasks to get them done, get them out the door without waiting.

For the less technical, I do want to call out a couple changes that were made to Google AI Studio, Google's sort of low code, no code coding product. So, a couple things that they released in Google AI Studio, again powered by Gemini 35 Flash, is the ability to build apps connected to your Google Workspace apps. So, again, Google is the source of truth for so much personal information and for companies that usual use Google Workspace for company information. And I've seen a lot of this in cloud code and cloud co-work. People are using the MCP connectors to build artifacts and apps on that data source. And Google is going straight for owning that experience themselves. So now you can build apps that read sheets, draft Gmails, organize Drive, see your calendar, all with built-in workspace integration out of the box. Now, we're going to try this and see if it actually works. But if it does, it's really going to carve off a lot of those internal enterprise use cases for productivity or those throwaway personal assistant use cases. You can now create Android apps inside Google AI Studio. So again, this is a lower code experience. And so if you want to start creating mobile apps for the Android ecosystem, that's something that you can do here in Google AI Studio. All right. So one of the things that I found a little bit frustrating with the Google announcements today is that they've announced a bunch of stuff and then at the very very bottom they're like it's available to some subset of people or it's available but later this summer. And so we're going to see if it has access to my Google calendar and mail. If not, we'll move on with our life and we will try it as soon as I have access. I am a paying customer, so hopefully I have early access, but we'll see. So, I'll say, "Make me an app to manage the next month of weekend events with my kids in particular, our sporting events. They are all on my personal calendar in Google." So, let's see what this does. It's going to think and hopefully it has integrated access with my workspace and can go ahead and build that product. And guess what? It didn't do anything magical. And I'm looking in the settings. I'm looking in the connectors. I could not find it. So, it's possible that not all of us have access to this right away. But I do think when we get Google Workspace access, you can imagine the kinds of features that you could build with this. So, this is one we're gonna have to circle back to and do another day. But again, the vision here is for Google AI Studio to have access to your work workspace apps and be able to build products with that workspace already integrated. I just can't figure out how to access it and I am pretty smart. Okay, we're going to go more and more fun stuff. Let's switch over to Gemini. Now, I'm going to reflect on something about all these announcements, which is I cannot keep the product and brand name straight. Just to clarify, so far we've talked about Google Gemini 35 Flash, the model. We have talked about anti-gravity, the IDE and anti-gravity, the CLI. We've talked about Google AI Studio, the low code, no code product. Now we're talking about Gemini, Google AI, the consumerish AI product, competitor to like Claude and Chat GBT. We've got too many brands going across this API portfolio. I'm not even done. I have like seven more tabs to get you all through. So again, if I could ask the Google team to do anything, it's a comprehensive brand analysis and singular brand that I can work with.

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Now, one of the things that you'll notice when you go into the new Gemini is there is a redesign. They made a big deal about this redesign. They called it something ridiculous that I can't remember now, but we will put it in the show notes. It's like supposed to make you feel good. Look at this glow. Everything's redesigned. You have a bunch of prompts and examples. So they really are trying to uplevel and upscale the consumer experience of using Gemini. But even more than that, they have added some pretty cool features to Gemini. So if you're not familiar with it, Nano Banana is one of the best image gen models. You can now create images with Nanobanana using a bunch of templates. So they're really trying to make it easy to inspire you with what to do with these models. I use Nanabanana quite a bit actually for our podcast thumbnails. So, let's try it really quickly. I'm actually going to grab a screenshot of myself so it'll look cute. Okay, I drag this in and I say upscale and beautify because I want to be pretty the image of this podcast host. change the background to a professional podcasting studio. Okay, so I'm going to press enter. Sorry to the people in the comments that keep saying, "Stop typing on your laptop. Type on your keyboard. It's making the video shake." I know. I'm just used to doing it. Okay. It took a little bit, but here it is. This is not my face. This is horrifying in every way possible. But some of the things that I notice about the image gen that has changed is again all these image gen models want to get a lot better at generating text. You see that it looks a little bit photorealistic even though it doesn't look face realistic. And it generated pretty fast but more fun than the image gen models are the video generation models. And so Google announced a new videogen model called Omni. Omni has a bunch of capabilities that we're going to show in a minute in the Flow app, but it's able to create longer, more consistent, more photorealistic videos using AI, and it's able to use reference materials to create those videos as well. Okay, I have this image that my kid drew me of this little guy. I'm actually going to take a screenshot of it while I hold it up to this camera. So, just bear with me while I do that. I'm going to drag this over into Gemini video creation and we're going to use this new model to animate this superhero. Animate this superhero breaking a kid out of class to go have fun. Now, Google has made all of these experiences more agentic. So, you saw it generate a plan and then it's going to create a video. It's going to take a couple minutes. So, while we're letting that generate, let's just talk a little bit more about how Google is describing Gemini Omni. They're comparing it to Nano Banana for video is now Omni for video and it's going to combine a reasoning model with a video creation model. And what they say is you can create video from anything. So, which is why I picked the example of taking this very cute drawing that I keep from my kid over here on my desk and seeing if we could create something from this. Again going back to what I talked about the Google models the multimodal capabilities of these models is very high. So when you want to do conversion of video to text image to video all those sorts of things you can ground what they say is you can ground Gemini in real world knowledge and create video components based on that. There's a couple really cool features. So, one of the things that they let you do is conversationally edit videos. So, let's say you have a video of a structure. You can change that video of that structure to change the structure into bubbles. And so, you can take real life video components and change them, edit them sort of Photoshop style with Omni by just prompting it. I think that's very cool. You can take a video and have Omni describe it. So again, this like multimodal part of it and so you can have it describe it and then you can edit the description to generate a new version of that. I think that's pretty cool. You can refine the same video. So again, one of the challenges with these video generation models is that when you create them, they take very long and then you can't really edit them and then you get inconsistent characters. And so the ability to change the environment, angle, etc., But keep characters consistent is going to be really powerful when doing sort of production level video. Gen, let's see. My video's ready. >> Let's get out of here and go have some real fun. Hold on tight. Here we go. >> So, my kid is really going to like this. Again, this was 10 seconds long and so it really is much longer than I think the six or seven seconds that Sora was. So again, we're like extending this bit by bit. And then the ability for me to like conversationally edit this video or change the school to like a an academy and have it be snowy outside. All those sorts of things are here with the Omni model. But you can see that it's going to be a really powerful video editing model.

Now, if you want to go deeper into video editing, you can use Google Flow, which is a much more prescriptive step-by-step video editing tool. Um, they embedded Omni into this new tool, Flow. And one of the things that you'll see here is they're really double doubling down on cinematic quality production quality editing. And so, they're looking at cinematic realism. Is this hyper realistic? You can blend multimodal references. So if you have a person, which I'm going to get to, a situation, an environment, you can use that to seed the video. And then you can kind of edit videos using conversational information. One of the things that you'll see in Flow that they've encoded is the ability for you to define characters. So let's say I want to take this guy and call him Captain Escapo School. I can use this design a character in Google Flow and then at@mentntion that character in any future video moving forward and create videos with that. And then you can actually create yourself as an avatar. So in addition to being able to create kind of like uh unique new characters, you can actually take a video of yourself and create an avatar. Maybe we'll try that. Um, there's a lot of custom tools built in, brainstorming, how to scale, how to organize. So, you see this really coming for production grade AI video genen. But let's jump into flow really quickly and see if we can make an avatar of myself and how it works. How you do this, you go to flow.google. It will redirect you to Google labs. You click your name, you create an avatar. We're going to get started. Okay. I scan this QR code. I pull it up on my phone. It's selfie.app.google. I agree to it taking my face. I'm going to allow camera access. I'm going to move this mic out of the way. Give me a sec. BRB. It's telling me to read numbers out loud. 25 47 56 87 18 52 Okay, it's turn and then I've turned it. Okay. And then it's telling me to turn my face to the left. Okay. That was it. Please don't steal my identity. All right. So, it's uploading and it is creating an AI avatar of at me and then I should be able to use that for any video moving forward. No. No sir, I couldn't. So again, here's where we're really on the struggle bus with Google, which is they've announced a lot of stuff and it hasn't really worked. So I did it. I gave them my identity. I trained their model. I subjected my human face to their deep mind engineers. And it didn't even create the avatar. So, the promise is really good for some of these things, but the reality is if you're not able to use them or they're broken on the day and then people are going to lose patience for some of this. And so, you know, a couple of my challenges that I've had with the Google announcements is one, I haven't been able to really find where they are because the products are named hard. And two, even when they announce a feature, even if it's live, even if I can get to it, it hasn't quite worked yet. So, that's a real bummer. You know, the last ones I'll show you, I was hoping to do videos, but we'll close it off with something a little bit more accessible, which is there are two tools that I think are really interesting for designers and marketings. There is Pomelli, which is their brand product, and then there is Stitch, which is their design product. Again, we've we got the anti-gravities, we got the AI studios, we got Google AI/gemini, we've got Flow, we've got Omni, we've got Stitch, we've got Pamel. So like Pimelli Pomelli, we've got a lot of products. We'll put them in the show note. I want to show you two of these products what they released. So Pamelli is their brand and marketing content generator. They announced a lot of stuff. I'm going to scroll through this on Twitter. There is an agent that allows you to create a core brand identity from a website. This is very similar to Claude design where you can put in a website and it will create sort of a brand identity and then you can create websites and brand books in addition to what Pamelli is good at which is creating campaign assets and photooots. Really easy. You just put in for me I would put in chatp prd.ai. I could continue and this agent will go ahead again and create a brand book for me. Yes, that is my website. It's going to analyze it. Now, in case you missed it, Google has been really focused on how to articulate design systems for AI. They released a standard called design.md that allows you to encode your product design in a markdown file for agents to use. I'm pretty sure that's what's behind this Pamelli brand um book as well as what you're going to see in Stitch. And then what this is going to do is it's going to gather my colors, my content, all that kind of stuff and build it out. I want to show a very similar flow in Stitch, which is their design tool. Stitch released a couple features that I think are really nice. Streaming into a design canvas like Figma. I'll show you how that looks in just a minute. Being able to start with existing designs, doing inline AI edits, so being able to select a component and edit it with text, and then import export options both between your production code and no code tools like lovable. I did a stitch earlier today just to show what this streaming looks like. So I said, "Design me an app that covers the recent changes to Stitch in the style of the Google IO site. I want to paste the Google IO site in." So let's get the website. I'm going to paste that in. I'm going to click go. And you will see here, if you haven't seen Stitch, it's again kind of like a in in browser Figma. It's using this agentic experience, building the design system, researching, pulling in the content, and then what you'll see is this design start to stream in the right side. So again, a bunch of these surfaces are about creation. They're about creating apps. They're about creating websites. They're creating videos. They're about creating images. And all of this is getting streamed into different apps. And it'll be interesting to see how they all come together or if they come together or if some of these things just stay in labs format. So again, you can see here Stitch is designing in my screens. It's going to create a mobile app because I accidentally selected mobile instead of web. This is a nice experience. Again, this is where I think I feel the speed of the Flash models is actually in design and this sort of experience versus the coding experience which is like browsing files. It should be fast. And so again, here are the features that Stitch released um designed by Stitch in streaming. We've got code sync, real time streaming canvas, um start with your own design in place edits, and this is a really interesting tool that I think, you know, more designers might want to play with. Now, one of the things that we should call out is every AI tool ships their own version of slop. Google's slop looks like Google. Claude slop looked like Claude. I'm not really sure what GPT's slop look like. It doesn't necessarily look good, but this is Google Stitch. And then we'll go back to Pamel and wrap this up. It has created a brand for me. These are definitely my brand colors. This is my tagline. And now I can create, this is the new feature, create a website. So it'll be really meta to take my brand identity and create a new website in Pamelly. And so while this is generating, we'll wrap it up by showing whether or not this did a good job. So I just want to recap for you the developer and designer focused features that were released today at Google IO. New model family Gemini 3.5 in particular 35 fast which is fast anti-gravity their agentic coding tool released a bunch of new features in their IDE including scheduled tasks new slash commands um the concept of projects as well as an IDE similar to clawed code. Google AI Studio integrated Google Workspace apps and data into the noode apps that you can generate. Google Gemini, the sort of like consumer chat interface released and upgrade to image generation, a new design um end to end as well as a video model omni that can be used in the Google AI Gemini experience as well as in a creative tool called flow. Flow released a bunch of character consistency, scene consistency, and videotovideo editing tools that are going to be really interesting for production grade editing. They also released an avatar feature which does not to date work. And then two more interesting marketing and design tools. Stitch, the sort of Figma style in browser design tool released streaming inline edits and brand consistency. And then Pimelli released the ability to do websites, brand books, etc. And it's still generating today. Okay. And not to wrap on a total dud, but maybe it's the summary of the evening. I had time to do a diaper change. Come down and check out my PML generated website and it's fine. So, I think a lot of interesting releases today from Google. A bunch of stuff to go play with. I think the video piece is the part that I'm most excited about. probably second is just the speed of coding that comes from these flash models, but there are some sharp edges, some things that definitely need to be improved and some things that actually need to be released. I cannot wait to see what you build. I can't wait to hear your feedback and what you're most excited about from Google IO this year. Thanks for joining How AI. Thanks so much for watching. 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