A product discussed on AI Engineer.

Build & deploy AI-powered apps — Paige Bailey, Google DeepMind
Apr 29, 2026 · 1:03:20
Paige Bailey, engineering lead for developer relations at Google DeepMind, demonstrates how the company's latest multimodal models and AI Studio platform enable rapid prototyping of AI-powered apps at minimal cost. She showcases Gemini 3.1 Flash Lite analyzing YouTube dinosaur videos for under a penny, the new Build feature constructing a fully functional bookshelf cataloger with Firebase database and Google login, and Gemini Live providing real-time multilingual screen interaction. Other demos include Genie 3 generating playable world models from text prompts, NanoBanana 2 performing cost-effective image editing, Veo 3.1 Lite producing stock footage (e.g., a "vegan basketball food truck" featuring Chef Curry), Lyria 3 creating custom music tracks, and Gemma 4 offering open-source multimodal models that run on mobile devices. Bailey emphasizes that the entire stack—grounded by Google Search and code execution—allows developers to ship ideas that would have been startups years ago, with all code exportable for production use.

Building in the Gemini Era – Kat Kampf & Ammaar Reshi, Google DeepMind
Dec 15, 2025 · 17:57
Kat Kampf and Ammaar Reshi from Google DeepMind present Gemini 3 and Nano Banana Pro, arguing that these models enable anyone to build complex, aesthetic applications through natural language alone. Gemini 3 achieves state-of-the-art results in one-shot UI design and agentic tool calling, with SweBench outperformance. Nano Banana Pro integrates Google Search for world knowledge and renders text accurately, handling up to 14 consistent people per image. They demonstrate vibe coding in AI Studio, building a personalized comic book with precise text, laptop stickers grounded in search, and a 3D racing game that scaled to 23 players live. Upcoming full-stack runtime adds backend support and automatic database integration, further democratizing software creation.

Useful General Intelligence — Danielle Perszyk, Amazon AGI
Aug 2, 2025 · 19:58
Danielle Perszyk, a cognitive scientist at Amazon's AGI SF Lab, argues that general-purpose AI agents like Nova Act must be built to augment human intelligence rather than replace it, drawing parallels to how human cognition relies on controlled hallucinations and social co-evolution. She explains that current agents struggle with basic computer tasks like clicking, typing, and scrolling, so Nova Act combines a specialized version of Amazon Nova trained via RL for UI reliability with an SDK that allows developers to string together atomic actions (act calls) into complex workflows. The lab's vision centers on grounding agents in a shared environment and eventually giving them models of human minds, which requires a common language for humans and agents to reciprocally level up intelligence. Demos with teammates Carolyn (searching apartments) and Fjord (extracting data with Python and parallel browsers) show how Nova Act enables three-line code starts and granular control, positioning the product as a primitive for a cognitive technology that aligns representations and stabilizes human thinking.

Building Agents with Amazon Nova Act and MCP - Du'An Lightfoot, Amazon (Full Workshop)
Jun 21, 2025 · 1:26:20
Du'An Lightfoot and Benjiro Byami present a workshop on building AI agents with Amazon Nova Act, Model Context Protocol (MCP), and Strands Agents, demonstrating autonomous web navigation and multi-step task execution. Lightfoot explains agentic AI as plan, action, and reasoning, with components like LLM, knowledge base, guardrails, and tools. Nova Act, a research preview, enables browser automation: one demo searches Amazon for a coffee maker and retrieves the product title using natural language commands instead of explicit HTML tags. Byami builds an MCP server for Nova Act, allowing clients like Claude Desktop to control the browser via spoken instructions, then integrates it with Strands Agents, an open-source framework that combines a prompt, LLM, and tools in minimal code. The workshop shows parallel execution (e.g., comparing three monitors) and multi-agent collaboration for tasks like generating a PowerPoint presentation for cloud migration. Limitations include inability to bypass CAPTCHAs and occasional loops in complex websites.

Climbing the Ladder of Abstraction: Amelia Wattenberger
Nov 3, 2023 · 16:47
Amelia Wattenberger, a designer at Adept, argues that AI can augment knowledge work by enabling users to 'zoom out' on information across different levels of abstraction, much like Google Maps hides detail at higher zoom levels. She reframes augmentation as composed of smaller automations, using the example of spreadsheets automating calculations so accountants can focus on analyzing numbers. Wattenberger demonstrates a prototype that uses LLMs to summarize paragraphs of Peter Pan into single sentences at higher zoom levels, and sketches how Adept's AI could extract key factors like Wi-Fi speed and walking distance from Airbnb and hotel listings, presenting them in customizable views and even a scatter plot for comparing 50 listings at once. The talk emphasizes that structured interfaces around AI models—not just chatbots—will transform how we work, and that Adept is building AI to automate tedious tasks while keeping users in control.
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