Idea to production: AI apps with Tomek Porozynski

Year: 2026 · ▶ Watch on YouTube

Aja Hammerly (Director DevX AI) · Tomek Porozynski (Google Developer Expert, Cloud & AI; Staff ML Engineer)

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Segments (8)

  • 00:00:00 · Introduction — Aja Hammerly
    • Aja Hammerly introduces the topic of AI dev tools and guest speaker Tomek Porozynski.
  • 00:16:08 · Speaker Introduction — Tomek Porozynski
    • Tomek introduces himself as a Staff ML Engineer and Google Developer Expert from Poland.
  • 00:28:18 · Project Showcase: Multi-Voice Audiobook — Tomek Porozynski
    • Tomek describes an exciting project he built that uses Gemini Text-to-Speech to convert text into a multi-voice audiobook.
  • 01:47:29 · Tools and Technology — Tomek Porozynski
    • He explains using Gemini CLI with skills for Vertex AI and the Gemini API, and how he moved the project to a Google Colab notebook.
  • 02:33:29 · Architecture Deep Dive — Tomek Porozynski
    • Tomek details the application’s architecture, which involves a combination of serial and parallel processing to generate the audio.
  • 04:26:24 · Challenges and Learnings — Tomek Porozynski
    • He discusses the challenge of rapidly evolving AI tech and how using ‘skills’ helps models access up-to-date information and APIs.
  • 05:48:29 · Getting Started with AI Dev Tools — Tomek Porozynski
    • Tomek advises starting small and recommends Antigravity IDE for coders and Google AI Studio for those without coding skills.
  • 10:14:04 · Conclusion — Aja Hammerly
    • Aja thanks Tomek for sharing his insights and details about his open-source project.

Demos (1)

  • 00:38:09 ✓ · Multi-Voice Audiobook Generator — Tomek Porozynski
    • Tomek verbally described a workflow he created that uses Gemini Text-to-Speech to analyze a story, identify characters, assign different voices, and generate a multi-voice audiobook. He also mentioned it’s an open-source project available as a Google Colab notebook.

Notable Quotes (6)

  • 00:38:09 — Tomek Porozynski:

    I’m really excited about Google, or Gemini Text-to-Speech APIs.

  • 02:46:11 — Tomek Porozynski:

    I open-sourced the solution and I used that on the DevFest talks to actually show people how that can be done.

  • 05:33:28 — Aja Hammerly:

    I don’t know what your experience has been like, doesn’t always go exactly the way I planned. I always run into something.

  • 06:38:00 — Tomek Porozynski:

    My advice would be not to give up when the first version is not perfect.

  • 07:00:23 — Tomek Porozynski:

    One thing that I think is sometimes overlooked is the plan phase or the brainstorming phase.

  • 09:07:05 — Tomek Porozynski:

    I think the great idea is to check Google AI Studio.

Visual Signals

On-screen (4)

  • 00:00:00 · Google Cloud Next 26 logo
    • Brands the event and the year.
  • 00:33:21 · Aja Hammerly, Director DevX AI, Google Cloud
    • Identifies the speaker and her role.
  • 00:21:20 · Tomek Porozynski, Google Developer Expert, Cloud & AI
    • Identifies the speaker and his role.
  • 10:29:26 · Google Cloud Next 26 logo
    • End card for the video segment.

Stage (1)

  • 00:00:00 · The video begins with two speakers, Aja Hammerly and Tomek Porozynski, seated at a desk in a studio/booth setting at the Google Cloud Next conference.

Key Topics

AI Dev Tools · Gemini API · Text-to-Speech · Google AI Studio · Gemini CLI · AI Agents · Agent Skills · Generative AI Development · Proof of Concept (POC) · Google Colab · Open Source AI · Developer Experience (DevX) · Prompt Engineering · Application Architecture · Rapid Prototyping

Takeaways

  • Gemini Text-to-Speech API is powerful enough to create sophisticated applications like multi-voice audiobooks by identifying characters and assigning unique voices.
  • For rapid prototyping, Gemini CLI combined with ‘skills’ is an effective tool for testing ideas and building proof-of-concepts.
  • The development process for AI applications should include a ‘planning phase’ where developers converse with an AI agent to brainstorm, refine ideas, and select the tech stack before writing code.
  • Google offers accessible entry points for all skill levels: Antigravity IDE for developers who prefer coding, and Google AI Studio for a no-code/low-code approach to building and deploying AI apps.
  • The fast pace of AI innovation is a major challenge; using ‘skills’ with AI agents is a key strategy to ensure models can access the most up-to-date information and APIs.
  • Open-sourcing projects and using shareable formats like Google Colab notebooks are excellent ways to contribute to the community and help others learn.
  • It’s possible to go from an idea in Google AI Studio to a fully deployed application on Cloud Run with a custom domain in a very short amount of time.
  • Iterative development is key when working with generative AI; the first result is rarely perfect, and developers should be prepared to refine and troubleshoot.