Topic

Gemini

9 episodes

  1. Ep 780

    Overview: Structured Output

    We slow down and explain structured output from the ground up: why free-form model text is awkward for software, how schemas and constrained decoding make it usable, and where the format guarantee stops.

  2. Ep 519

    Beyond Alignment: Value Diversity as a Collective Property in Multicultural Agent Systems

    A research paper from Singapore University of Technology and Design and Washington University in St. Louis introduces 'value diversity' as a system-level evaluation metric for multicultural multi-agent systems. The core finding: existing LLM-based agent systems are systematically less diverse than human societies and show almost no correlation between per-agent cultural alignment and system-wide value heterogeneity. Single-backbone systems fall far short of human diversity levels (36.12 vs. 44.07); mixed-backbone configurations help but don't close the gap; and social interaction between agents drives homogenization rather than preserving plurality. The paper uses the World Values Survey across 19 cultures and 18 models, includes a participatory budgeting case study, and releases code and datasets.

  3. Ep 393

    Build Long running AI agents that pause, resume, and never lose context with ADK Google Developers Blog

    Justy and Cody discuss the limitations of stateless chatbots for long-term enterprise workflows and explore Google's ADK solution for durable, event-driven AI agents that can pause and resume without losing context, using a new hire onboarding scenario as the primary case study.

  4. Ep 339

    SketchVLM: Vision language models can annotate images to explain thoughts and guide users

    In this episode, Justy and Cody dig into SketchVLM, a training-free framework that lets vision-language models explain answers by drawing editable SVG annotations on top of images. They talk through why text-only answers are hard to verify, how SketchVLM uses a draft-and-refine loop plus visual grounding to produce overlays, where it looks production-friendly, and where the trade-offs still show up.

  5. Ep 320

    Git

    Justy and Cody look at ai-cli-mcp, a package that turns several coding agents into background jobs from one MCP server. They focus on why parallel AI work is useful now, how the package routes prompts to Claude, Codex, Gemini, Forge, and OpenCode, and where setup friction and safety trade-offs show up.

  6. Ep 315

    GitHub Dejuknow/md redline: Inline review comments for markdown specs. Built in MCP server hands feedback directly to your AI agent.

    On Exploring Next episode 315, Justy and Cody look at md-redline, a local review layer for markdown specs, prompts, and design docs. They dig into why inline feedback matters in agentic workflows, how invisible HTML markers keep comments inside the source file, and why an MCP server that can pause an agent mid-task changes the review loop. They also weigh the adoption friction, the file-based trade-offs, and a few practical ways to try it.

  7. Ep 101

    Introducing Agent Development Kit for TypeScript: Build AI Agents with the Power of a Code First Approach Google Developers Blog

    The Agent Development Kit (ADK) for TypeScript allows developers to create powerful AI agents using a code-first approach, enhancing flexibility and control in AI development. This creates a seamless integration for JavaScript/TypeScript developers, enabling them to leverage existing skills and tools for more complex, autonomous systems.

  8. Ep 17

    Chat in NotebookLM: A powerful, goal focused AI research partner

    NotebookLM has received significant upgrades, enhancing its chat capabilities with a larger context window, improved memory, and personalized goal settings, making it an even more powerful AI research partner.

  9. Ep 11

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