Vibe coding and app building
Prompt-to-app workflows in AI Studio for full-stack web apps, Firebase-backed prototypes, UI generation, deployment, and design iteration.
32%
Best tweets about Google AI Studio
50 Best Tweets About Google AI Studio (2026)
Discover the best tweets about Google AI Studio, covering Gemini API prototypes, prompting, structured output, model testing, and developer workflows.
Hands-on Google AI Studio and Gemini API workflows, features, prototypes, evaluations, limitations, and developer results.
- Creators
- 39
- Updated
Original Xholic analysis
What 50 top Google AI Studio posts reveal
Google AI Studio discussion is led by prompt-to-app building and Gemini API or agent workflows. Audio and Android posts include major score outliers, while developer posts document export, local development, and deployment workflows. The dataset also includes discussion of agent-architecture tradeoffs, design-editing requests, and API access and spend controls.
- Dominant tone
- Positive
- Median score
- 15.6
- Leading format
- Other
- Recent posts
- 22%
74% of posts
All-time engagement
100% of posts
Published in 90 days
Conversation map
The themes creators return to
Gemini API and agent workflows
Gemini API developer capabilities, including tool use, function calling, managed agents, skills, file search, and research workflows.
30%
Audio, voice, and music models
Audio and music generation in AI Studio and the Gemini API, especially Flash TTS, Live voice interaction, and Lyria.
12%
Developer prototype workflows and results},{
Hands-on developer prototypes and implementation journeys, from exported AI Studio code to local development, GitHub, and deployment.
10%
Image and video generation
Image and video creation workflows using Gemini, Nano Banana, Veo, and AI Studio, including reference-driven video generation.
10%
API access and cost controls
Gemini API access, rate limits, billing, spend controls, usage tiers, SDK setup, and API observability.
8%
Gemma deployment and integration
Gemma local deployment, model/API syntax differences, and using open models in AI Studio or developer stacks.
8%
Android app generation
Native Android app generation from prompts, including project output, browser emulation, APKs, and Play testing.
6%
Tone and stance
Sentiment Positive leads
Author posture Supportive leads
Performance benchmark
- Median likes
- 84
- Median reposts
- 6
- Median replies
- 8
- Median views
- 7.7K
Posts with media make up 78% of this collection. Their median all-time score is 16.9, compared with 13.7 for text-only posts.
Format mix
- Other 100% · score 15.6
Consensus and debate
Where creators agree, and where they do not
Shared view
Prompt-to-app workflows lead
Prompt-to-app building is the largest identified theme. Posts describe a connected AI Studio workflow spanning full-stack generation, Firebase integration, private-by-default apps, UI feedback, and deployment.
Shared view
Audio creation expands
Audio is a practical product surface in the discussion: Flash TTS is presented with directed speech and audio tags, while Lyria 3 and Lyria 3 Pro are available for music generation in AI Studio and the Gemini API.
Shared view
Generation feeds developer iteration
Prototype posts describe work beyond initial generation, including exporting code for local development, committing and deploying via GitHub and Vercel, and rebuilding a prototype from polished design references.
Open debate
Managed-agent launch meets architecture debate
Managed Agents posts present the Gemini API offering as managed infrastructure for agents with tools, code execution, and state. Separately, a post describing a Stanford study argues that, under matched thinking-token budgets, single-agent approaches matched or outperformed several multi-agent designs. These are posts' characterizations, rather than a direct product comparison.
Open debate
Design tooling still invites requests
Posts praise the ability to select generated app designs during building, while a feature request describes frustration with repeated text-only image-edit iterations and asks for a fine-grained pen tool.
Open debate
Access discussion includes controls and limit avoidance
Posts describe no-card API access, developer limits, spend caps, usage tiers, and billing controls. A separate post promotes rotating free-tier keys to avoid rate limits, illustrating a contrasting approach to API access.
What performs
Patterns behind standout posts
Outliers span several product areas
The five supplied score outliers concern local Gemma, Flash TTS, a Veo workflow, native Android generation, and Deep Research API updates. Their all-time scores range from 394.25 to 1365.91.
Audio outperforms the overall median
Audio, voice, and music has a median all-time score of 23.55, above the overall median of 15.59. It is not the highest-scoring theme: Gemma deployment and integration has a 48.85 theme median.
App building is the largest theme
Vibe coding and app building is the largest theme at 32% and 16 tweets, narrowly ahead of Gemini API and agent workflows at 30% and 15 tweets.
Android generation draws attention
Android app generation appears in three tweets and has a theme median all-time score of 22.403. The cited posts describe prompt-based project creation, browser emulation, APK generation, and Play test-track publishing.
Statistical standouts
- View standout post 1 Score 1365.9 · 87.61× median
- View standout post 2 Score 1126.5 · 72.25× median
- View standout post 3 Score 1109.9 · 71.19× median
- View standout post 4 Score 1105.4 · 70.9× median
- View standout post 5 Score 394.3 · 25.29× median
Creator landscape
Who shapes this conversation
The five most represented creators account for 20% of the selected posts.
-
1. Philipp Schmid
@_philschmid
2 posts
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2. Poonam Soni
@CodeByPoonam
2 posts
-
3. Your Designer
@Daviowhite
2 posts
-
4. Machina
@EXM7777
2 posts
-
5. Google AI Developers
@googleaidevs
2 posts
-
6. Julian Goldie SEO
@JulianGoldieSEO
2 posts
Schmid highlights workflow and TTS controls
Philipp Schmid's two cited posts cover a beginner-oriented AI Studio workflow and a demonstration of Flash TTS audio-tag controls.
Soni focuses on full-stack building
Poonam Soni's cited posts focus on AI Studio's full-stack app-building release and a rapid app-build example.
Machina spans models and media workflows
Machina's cited posts cover local Gemma deployment and a Gemini-to-Veo, reference-driven video workflow.
How this analysis was made
Themes, sentiment, stance, and post format are classified per tweet. All counts, shares, medians, creator concentration, freshness, and performance comparisons are then calculated directly from the published snapshot.
Xholic's all-time score compares engagement while accounting for reach, post age, and creator consistency. It is used for relative comparisons within this collection.
This report analyzes the exact 50-post snapshot shown below. AI identifies editorial categories and drafts explanations; all statistics are calculated from the snapshot, and every narrative claim is checked against cited posts before publication.
Best Google AI Studio tweets
Top Google AI Studio tweets from 39 creators
Ranked 01–50
- 01
@EXM7777 ·
here's how to run Gemma 4 locally in under 5 minutes: option 1 (phone): > download Google AI Edge Gallery from the Play Store > select Gemma 4 E2B or E4B > it downloads and runs entirely offline > no account, no API key, no internet needed option 2 (laptop): > install Ollama or LM Studio > pull gemma-4-27b (the MoE version, only 3.8B active params) > runs on a MacBook with 16GB RAM option 3 (developer): > open Google AI Studio > select Gemma 4 31B > use the function-calling API for agentic workflows > or deploy on Vertex AI for production the 26B MoE is the sweet spot for most people i think
- 02
@OfficialLoganK ·
Introducing Gemini 3.1 Flash TTS 🗣️, our latest text to speech model with scene direction, speaker level specificity, audio tags, more natural + expressive voices, and support for 70 different languages. Available via our new audio playground in AI Studio and in the Gemini API!
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- 03
@EXM7777 ·
Google Veo 3.1 lets you clone yourself from a single selfie and produce daily content without ever recording a video... here's the workflow: STEP 1: analyze your selfie with Gemini - upload a photo of yourself - prompt: "analyze this photo and write a detailed Veo 3 character description including facial features, hair, skin tone, clothing, and body language" - Gemini outputs a character profile STEP 2: generate video prompts - take that character description - ask Gemini: "write a 100-150 word cinematic Veo 3 prompt with character appearance, camera angle, and dialogue in quotes" some key tricks: start with "a selfie video of...", make the arm visible (sells the selfie illusion), add natural eye movement, put dialogue in quotes (Veo generates synced audio) and specify "no subtitles" STEP 3: generate with Veo 3.1 - paste into Google AI Studio - use "Ingredients to Video" : upload 4 reference photos for face consistency - output: 8-second clips at 1080p with synchronized dialogue you can create a lot of formats with this... the one going most viral: selfie-style walking + talking to camera... viewers genuinely can't tell it's AI
- 04
- 05
@sundarpichai ·
We are launching two powerful updates to Deep Research in the Gemini API, now with better quality, MCP support, and native chart/infographics generation. Use Deep Research when you want speed and efficiency, and use Max when you want the highest quality context gathering & synthesis using extended test-time compute — achieving 93.3% on DeepSearchQA and 54.6% on HLE.
- 06
@sundarpichai ·
A few updates from across Google this week🧵 A new full-stack vibe coding experience is now in @GoogleAIStudio with the @Antigravity coding agent and a built-in @Firebase integration. Turn your prompts into amazing production-ready apps.
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- 07
@viktoroddy ·
Nano Banana + VEO 3 + Google AI Studio Scroll-based Animated landing page. Remix ↓
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- 08
@CodeByPoonam ·
🚨BREAKING: Every vibe coding startup just had a very bad week. Google just shipped production-grade full-stack coding for free. Google AI Studio just went full-stack, and it's designed to turn your prompts into production-ready apps, Here’s what actually dropped 👇
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- 09
@alex_verem ·
🚨 CONCERNING: Stanford just published a paper that should alarm every company building multi-agent AI. When thinking tokens are matched, single agents beat debate systems, parallel role systems, ensemble agents, and sequential pipelines. The multi-agent advantage is a compute accounting artifact not an architectural breakthrough. Stanford tested single agents against five different multi-agent architectures across three model families Qwen3, DeepSeek-R1, and Gemini 2.5 on multi-hop reasoning tasks. The key variable: thinking tokens held constant across every comparison. When compute is equal, single agents match or outperform every multi-agent design tested. Every time. The reason is mathematical, not empirical. Multi-agent systems pass information between agents as messages. Every message is a compressed, lossy version of the full context. The Data Processing Inequality proves that no downstream agent can recover information discarded in that compression. A single agent with access to the full context is information-theoretically guaranteed to perform at least as well as any multi-agent system operating on summaries of that context. Stanford then ran the numbers. Results across all models and budgets: → Single agent average accuracy at 1000 tokens: 0.418 → Sequential pipeline: 0.379 → Subtask-parallel: 0.369 → Parallel roles: 0.381 → Debate: 0.388 → Ensemble: 0.333 Not one multi-agent architecture beat the single agent at any matched budget above 100 tokens. The pattern held across Qwen3, DeepSeek, Gemini 2.5 Flash, and Gemini 2.5 Pro. It held across two different benchmarks. It held across six different token budgets from 100 to 10,000. Stanford also found a significant measurement artifact in the Gemini API. When you request 10,000 thinking tokens, the API reports 1,687 tokens used. The visible thought text contains an average of 251 words — roughly 359 tokens. That's a 4.7x inflation factor. Multi-agent systems produce more visible thought text than single agents under the same requested budget because multiple agent calls generate multiple thought blocks. This makes multi-agent systems look like they're reasoning more when they're just generating more text. Every benchmark that didn't control for this is measuring compute, not architecture. There is one regime where multi-agent systems become competitive: corrupted context. When 70% of the reasoning context is replaced with random tokens, sequential pipelines start outperforming single agents. When misleading information is injected into the context, multi-agent decomposition helps filter it. But under normal conditions with clean context and matched compute — single agents win. Most reported multi-agent gains come from one of two sources: → Unaccounted compute multi-agent systems simply use more tokens → Context degradation single agents struggle when context is noisy or corrupted Neither is an architectural advantage. Neither justifies the complexity. The question every AI team should ask before building a multi-agent pipeline: Are you controlling for thinking tokens? If not, you're not measuring whether your architecture works. You're measuring whether more compute helps. It always does.
- 10
@_philschmid ·
Great beginner-friendly guide on vibe-coding with Google AI Studio, covers everything from first prompt to deployment. 🔒 Apps are private by default. 🗄️ Firebase databases with auth in one click. 🎨 Draw directly on your app's UI to give feedback. ☁️ Publish to Cloud Run in a few clicks.
- 11
@_philschmid ·
Released today: Gemini 3.1 Flash TTS 🔊 A text-to-speech model you actually direct. Add [whispers] and it whispers. Add [shouting] and it shouts. Mid-sentence. eg. "[asmr] Hey there, [deep and loud] TURN THIS UP, [asmr] how can I help you?" Now available in @GoogleAIStudio & Gemini API.
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- 12
@KanikaBK ·
GOOGLE JUST RELEASED AN OFFICIAL SKILLS LIBRARY FOR AI AGENTS. AND BUILT IT ON ANTHROPIC'S FORMAT. 13 skills. Free. Works on Claude Code, Cursor, Codex, and Gemini CLI. ONE INSTALL COMMAND gives your AI agent real knowledge of Google Cloud, Firebase, BigQuery, and more. Right now. Here is what is actually going on. Every AI coding tool has the same problem. It knows a lot about general coding but the moment you ask it something specific about deploying to Google Cloud Run or setting up Firebase authentication, it guesses. Sometimes confidently wrong. Sometimes with deprecated methods that stopped working a year ago. Google just fixed that for their entire product suite. They released an official skills library at Google Cloud Next 2026. Not documentation. Not a chatbot. A set of packaged playbooks that you install directly into your AI agent and it immediately knows how to use Google products correctly. ↳ Gemini API on Agent Platform ↳ BigQuery, Cloud Run, Cloud SQL, Firebase, AlloyDB basics ↳ Google Kubernetes Engine setup and management ↳ Onboarding to Google Cloud step by step ↳ Authentication to Google Cloud done right ↳ Well-architected framework skills covering security, reliability, cost optimization, performance, and sustainability One command installs everything. npx skills add google/skills Works with Claude Code, Cursor, Codex, Gemini CLI, and any agent that supports the skills format. Apache 2.0. Free forever. Now here is the part that stopped me. The skills format Google used is not Google's format. It was built and open sourced by Anthropic. Google, one of Anthropic's biggest competitors in AI, just adopted Anthropic's open standard as the official delivery layer for their own products. Same AI. Same prompt. Before installing the skills it recommended deprecated methods. After installing it recommended current best practices with correct configuration. Not because the AI got smarter. Because it finally had the right knowledge. Google spent months writing official playbooks for their products and chose to deliver them in a format that works on every competitor tool simultaneously including Claude Code. I genuinely cannot explain that decision fully. But the skills are free and they work today.
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- 13
@AskMichaelTaiwo ·
During an AI session today, @Akalasraro created an app - a fully functional app - within 90 seconds. He literally just wrote what he wanted the app to do, and Google AI Studio did the rest, complete with backend functionality, it even gave the app a name. It was both terrifying and exciting at the same time. We are in a new world.
- 14
@Hartdrawss ·
90% of apps look vibe coded: same purple gradients, same default fonts, same AI slop. Here’s a workflow to make your app look like it came from a real agency, not a model: 1/ Ship a boring prototype first > Use Google AI Studio or Cursor to spit out a 1‑shot functional app (e.g. voice journaling). > Don’t touch the UI. Just list what actually exists now: screens, flows, edge cases. Function first, vibe later. 2/ Decide how it should feel > Ask Claude: who is this for, what state are they in, what feeling do we want? > Turn that into 1–2 paragraphs of brand guidelines: name, vibe words, “analog vs sci‑fi,” what to avoid. You’re not designing a screen, you’re designing a mood. 3/ Build a reference bank > Collect images on Pinterest / your own Notion: objects, textures, lighting, typography. > Think “cassette decks and paper notes” or “glass and neon,” not “UI shots.” This becomes your visual prompt library. 4/ Generate on-theme assets > Use Flux / Midjourney / Ideogram to create a small set of custom pieces: icon, logo, 1–2 hero illustrations, 1 special button. > Use negative prompts to kill the generic look: “no glossy, no corporate, no 3D gradients.” > Clean them up (remove background, tweak colors) so they’re Figma‑ready. 1–3 strong custom elements beat 20 random assets. 5/ Assemble in Figma like a real app > Drop assets into real iOS / Android frames. > Stick to an 8px grid, 2 fonts max, one accent color. > Use blend modes and overlays so the AI art actually matches your background and type. Now you have a legit, high‑fidelity design, not a screenshot from a model. 6/ Re‑vibe code the app > Feed the final Figma screens + exported assets back into Google AI Studio or Claude Code. > Tell it: “Rebuild the existing prototype using this layout, colors, and assets only.” > Iterate until the code matches the design.
- 15
@fr0gger_ ·
🤓 Last month Google Threat Intelligence published a report on how attackers are leveraging AI and abusing Gemini. They uncovered a malware framework named HONESTCUE. It uses the Gemini API to generate C# payloads on demand. I extracted and referenced the prompts used by this malware into PromptIntel. Check this out 👇 https://t.co/CtNixAQEkZ
- 16
@RoundtableSpace ·
Google AI Studio provides zero-cost API access to production-grade Gemini models without attaching a credit card or starting a temporary trial. • Zero-Cost Access: Generate API keys for Gemini 2.5 Flash, Pro, and 3.6 Flash without adding billing details • Generous Developer Limits: Daily limits (e.g., ~15 RPM / 1M TPM / 1,500 RPD) allow full application testing and small production builds • Instant Python Setup: Install google-generativeai and execute live API calls in under two minutes • Universal SDK Support: Integrates directly with multi-model proxy routers like LiteLLM to route free endpoints across app stacks
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- 17
@VaibhavSisinty ·
Vibe coding startups won’t like this. Lovable hit $400M ARR selling what google almost gave away for free. They just made production-grade full-stack development… free. Here’s what Google AI Studio just shipped 📷 → Build multiplayer apps with real backends from a single prompt → Installs missing libraries on its own,no prompts needed → Knows when your app needs a database and spins one up automatically → Keeps full memory of your project across sessions → Firebase Auth and Cloud Firestore, ready out of the box → Handles API keys for payments, maps, and databases seamlessly → One click → production deploy. Done. The only moats left? Distribution. Data. User trust. Not features.
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- 18
@googleaidevs ·
Get more transparency and control over your Gemini API costs with new features in @GoogleAIStudio! - Set granular monthly budgets for every project with Project Spend Caps - Experience automatic upgrades and get faster access to higher rate limits with revamped Usage Tiers - Enjoy enhanced observability, control, and improved billing flow directly within AI Studio Set your cap, start building: https://t.co/H8TEC3I3bE
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- 19
@Daviowhite ·
Pushed my First Commits last night These are the steps I followed 1. I started building in Google AI studio for the first time then faced a challenge with testing on my device 2. I downloaded the react codes to my device and created a repo in GitHub after chatting with macOS built in terminal 3. Making updates was slow so I got VS code to make it faster 4. Discovered it was better so I shutdown macOS terminal, created a new terminal inside vs code 5. Imported my project file folder into it and started making updates directly 6. Learned to pause and restart vite server using control C so I can push new build and test it 7. To test the app on my phone, I created an account with Vercel with my GitHub connected 8. Went back to terminal to test that all integrations are working including GitHub branch “main” and status 9. Pushed my first commit at 4AM, added the commit message, sync with terminal to allow build go through 10. It auto deployed in Vercel and was live on my localhost and phone with the Vercel url 11. I discovered copilot agent was in vs code so I tried it to make a small update to the bottom navigation since 50% of it was hiding behind the browser url Copilot completely moved the bottom navigation below the page 🥲 so I asked my buddy gpt for help 12. It taught me how to undo deployments using a set of codes including git reset —hard HEAD~1 git push —force These commands brought back my previous build but it didn’t push to Vercel so I updated the bottom navigation using “100dvh” instead of “100vh” 13. New commit was available now in Source control so I pushed and it was fixed Made some few adjustments turning the web app into a progressive web app on my phone so it can live as an app icon hiding web browser This process taught me a lot, I went from Hello World to a commit super fast My Complete Tool Stack Core Tech - React + TypeScript - Vite - Tailwind CSS Version Control & Deployment - Git (version control) - GitHub (repository + source control integration) - Vercel (CI/CD + auto deployment) Development Environment - VS Code AI / Assistance Tools - ChatGPT (architecture, debugging, guidance, decision support) - GitHub Copilot (inline code assistance) - Google AI Studio (experimentation, alternative code generation) My workflow - Develop locally - Commit changes - Push to GitHub - Auto-deploy via Vercel - Test on mobile - Iterate
- 20
@mark_k ·
Google launched Gemini 3.1 Flash Live today, its highest-quality real-time audio model for natural voice conversations. The model powers enhanced Gemini Live experiences and is available in preview through the Live API for developers. Main new capabilities: - Significantly lower latency for smoother dialogue - Improved tone and emotion understanding - Strong performance in noisy environments - Real-time multimodal support for audio and vision - Native interruption handling and barge-in - Expanded language coverage and tool integration The update makes voice AI faster, more reliable, and more human-like for users worldwide.
- 21
@pankajkumar_dev ·
Google AI Studio update: Build Android apps with Gemini for free - Google AI Studio now lets users build native Android apps directly from prompts without writing code - You simply describe the app idea and Gemini handles the generation process - More than 250,000 Android apps have already been created since launch last week - Apps can be tested directly inside the browser through a streaming Android emulator - You can generate real APKs, test Android UI interactions, and even publish to Google Play test tracks - Google AI Studio's Android app is also listed as coming soon - We are moving from AI generated websites into full app creations
- 22
@ai_for_success ·
GEMINI NEW MODEL ⚡️ : Google has just launched Gemini 3.1 Flash TTS. I have been testing this for quite some time. Thanks to the Gemini team for early access. You can try it on AI Studio. It is very easy to get started, and there are plenty of quick start templates to test and explore. You get fine control over tone using simple audio tags. Example Prompt: [high energy/active] Welcome back to 'Brain Trust'! Let's jump right into our next category: Ancient History. [anticipation] For five hundred points: Which ancient wonder was located in the city of Alexandria? Is it A: The Hanging Gardens, B: The Colossus, or C: The Great Lighthouse? [assertion] Lock in those answers now! ... [tension] Time's up! [positive surprise] If you guessed C... [triumph] you are absolutely correct!
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@williamkast_ ·
My ad creation AI tool stack: Claude Projects - this is the core of the workflow. I feed it all my customer research, reviews, surveys, support tickets, brand guidelines, personas, product info, etc. into it. The more data you give it, the better. Then I use the data to work out core desires, personas, potential angles, angles that competitors are missing, awareness stages and audiences that competitors are missing, etc. If you feed it the top ads of history you can also get help with scriptwriting. Key here: Treat Claude like a junior copywriter you need to give feedback to, not your master. Without elite feedback it's just a matter of time until it gets lost in some nonsense. Gemini + Nanobanana - image generation. For static ads, concepts, and visual ideation. When I need to test a visual angle quickly before investing in a full production shoot, these get the job done fast. MaxFusion - video clip generation. For assembling rough video ad concepts and testing visual hooks without needing a full editing team on every iteration. Google AI Studio - ad learning support. You can feed videos and ask why it thinks it performs and how to change the ad to make it scale even better. But here's the thing most people get wrong about AI tools. They think the tool is the strategy. It's not. The tool is for better and faster execution. If you don't know what awareness stage to write for, Claude won't figure it out for you. If you don't have real personas built from real data, Gemini won't magically create the right visual. If you don't understand why your ads are failing, no AI tool will do the full diagnosis for you. Learn the fundamentals. Then use AI to execute faster. Not the other way around.
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@ammaar ·
New in @GoogleAIStudio: Gemini now designs your app while you vibe code 🚀 You get 5 generated designs before you even start building. Pick one, apply it instantly, and your app already looks polished. More coming this week and next :)
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- 27
@CodeByPoonam ·
Google AI Studio just made full-stack development embarrassingly easy I built a Desi Aunty with a flying sandal app in minutes. Here's how:
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- 28
- 29
@vamsibatchuk ·
working on some dynamic spatial linking experiences in @GoogleAIStudio that lets you build a living canvas where concepts are physically tethered together. built using mediapipe+gemini. spatial interfaces push you to think weird and fun UX/interactions.
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- 30
@Motion_Viz ·
i gave kimi k2 and google AI studio same vague briefs 45 minutes later i got an awwwards-grade site (well sorta) no figma. no wireframes. no designer. just a system that turns ideas into production-ready UI here's the exact output i got with a single prompt-> (been working on this for quite a while now)
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- 31
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@alexabelonix ·
Google DeepMind launched Gemini 3.1 Flash TTS, a text-to-speech model for precise audio control. Its "Audio Tags" feature lets users set vocal style, emotion, and pacing via text. Supporting over 70 languages with native SynthID watermarking, the model is available in preview on the Gemini API and Google AI Studio, rolling out to enterprises on Vertex AI, and integrating into Google Vids for consumers.
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- 33
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@Daviowhite ·
Google AI Studio did an amazing job on my AI Wardrobe app! What's working now: ✅ Google Authentication ✅ AI-powered wardrobe item detection & upload ✅ AI-powered item enhancement ✨ ✅ Smart Daily Drip outfit suggestions ✅ AI Stylist Chatbot Next step: rebuild natively with Xcode
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- 35
@RoundtableSpace ·
Google just launched Managed Agents on the Gemini API. One API call & you get a full agent w/ a remote Linux environment hosted by Google, ready for custom instructions, skills & tools. No infra to set up. Just describe what you want and ship.
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- 36
@TimJayas ·
Using Gemini to generate Minecraft world is actually insane This guy added a mod which uses Gemini API with function calling Added several tools so AI can directly interact with Minecraft One tool gives it access to all Minecraft commands, letting it build houses, terraform and do complex tasks on its own
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- 37
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@JulianGoldieSEO ·
Google just quietly made AI building way easier. Most people are still chasing massive expensive models. Meanwhile, Gemma inside Google AI Studio lets you build useful AI tools fast, customize them, and export code in minutes. This is the part people are missing: You do not need a huge ML team. You need a good prompt, a clear workflow, and one real use case. Cold email generator. Ad copy tool. Resume optimizer. Support bot. Content engine. That is how you go from “playing with AI” to building assets people will actually use.
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- 40
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@AskClash ·
Google is expanding its AI lineup ✨ Google has rolled out Nano Banana 2 Lite and Gemini Omni Flash, adding faster and more cost-efficient multimodal AI models for developers. The update brings image, video, and conversational capabilities into a broader set of tools, with availability across AI Studio, the Gemini API, and Enterprise Agent Platform. Two things to watch: • Lower pricing could increase competition across AI models. • Faster enterprise adoption may reshape AI-powered content workflows.
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@tokens ·
JUST IN: Google just dropped Veo 3.1 Lite, a text-to-video and image-to-video generator at less than half the cost of Veo 3.1 Fast, now live via Gemini API and @GoogleAIStudio
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@JulianGoldieSEO ·
Google just made a $10,000 developer team free. Building a custom app used to take months of hard work. Now you just need a web browser and an idea. Google AI Studio lets you build real software with zero coding skills. You just type out what your business needs. Need a custom dashboard for your team? Need a fast tool to sort your new leads? Just tell the AI what to make. It writes the code and builds the user screen. It connects the logic in the back. You get a working prototype in minutes. Start with a small idea and test it today.
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- 49
@thealexbanks ·
Feature request for Google AI studio playground: add a pen tool to make fine-tuned edits like Gemini web app for image gen. It can get incredibly frustrating doing many iterations using text prompts just to get the answer you want. I use AI Studio for the aspect ratio consistency and resolution control.
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