Google AI Studio Deep-Dive + Google ADK Multi-Agents (Live Build) | AI Bros Pod EP 33

Description

In AI Bros Podcast EP 33, Nisaar and Rohan explore Google AI Studio end-to-end (Playground, Image Gen, Veo 3.1 video, TTS/Live) and then scale prototypes into multi-agent systems with Google ADK. We refactor single agents from EP 32 into parallel and sequential pipelines, wire sessions, artifacts, and FastAPI, and demo practical use-cases (web+SQL agents, research, reporting). Plus: real talk on billing hiccups, roadmap, and what’s next. Timestamps 00:00 Overview: Google AI Studio + Multi-Agent goals for today 01:15 Housekeeping: billing hiccup (Vivo/Veo costs), travel plans & schedule update 03:05 Turning EP 32 single agents into a multi-agent setup (repo plan, API consumption) 03:51 Consistency chat: 33–34 lives in a year, what’s working/not 06:17 Monetization brainstorms: product ideas, plugins, Maps/Search data angles 10:22 Freelance/content ops: connecting businesses ↔ creators with AI tooling 11:15 Fun demo: AI-generated T-shirt designs + simple 3D mockups with prompts 15:57 Speed wins: QR/payments, code assistant, cutting months → minutes 20:30 AI Studio for creators: streaming, summarizing, title/desc/thumbnail ideation 21:14 Auto thumbnails & intro scripts with AI; model/output settings overview 22:33 Veo 3.1: text-to-video + image-to-video references (practical flow) 30:49 Gaps & wishes in AI Studio; intro to Multi-Agent SDK direction 36:33 RAG + Web agents recap (Tesla example) in a unified UI 37:57 Building base agent + RAG agent (Pinecone) refresh for better answers 38:44 ADK Web agent registration (“root agent”) & exposing APIs beyond defaults 40:39 Roll your own agents as clean FastAPI endpoints (quick import pattern) 42:49 Sessions 101: events, state, in-memory vs DB vs Vertex store 47:47 When to use in-memory session storage (dev/unit test trade-offs) 49:43 DB-backed sessions via connection URLs (SQLite/Postgres examples) 51:02 Session service: chat state/history options & new session flows 51:48 Managing conversation state: key-value patterns & end-conversation cleanup 55:59 FastAPI + async: running agents and handling requests efficiently 57:56 Artifacts service: store big JSON/output blobs & pass lightweight refs 59:21 (Hindi) Session management approaches & pre-call parameter visibility 1:00:05 Execution control: before/after tool/model calls; constraining actions 1:04:34 Sequential agents: planner-driven step-wise pipelines 1:07:55 Determinism & refactors: making runs reproducible 1:10:43 Parallel agents: concurrent tasks → merge for final response 1:12:07 Tips: register base/root agent, consistent outputs, artifact refs to save tokens 1:25:02 Parallel research example: energy/EVs/carbon capture in one pass 1:26:34 Merging parallel outputs into a cohesive answer 1:31:48 Final agent plan: Cybertruck price & sales via parallel + sequential combo 1:32:40 Naming/description conventions for agent clarity; orchestration best practices 1:34:07 Structured reporting: synthesize, filter noise, tag sources 1:35:23 Markdown reporting + per-agent attributions & citations 1:36:56 Audience Qs: how many units sold/costs → pipeline design live 1:37:50 Parallel SQL + cost analysis; getting to a comprehensive final output 1:39:23 Wrap-up: congrats, time off, what’s next 1:40:10 Roadmap: 5 topics for next month (session memory, callbacks, storage, more) YouTube Tags (copy all): Google AI Studio, AI Studio Playground, Gemini, Veo 3.1, video generation, image generation, multimodal AI, text to video, image to video, TTS, Live API, Build workflow, structured outputs, function calling, prompt engineering, usage limits, developer console, ADK, Google ADK, Agent Development Kit, multi-agent systems, planner agent, critic agent, researcher agent, sequential agents, parallel agents, sessions, artifacts, FastAPI, async Python, web agent, SQL agent, Pinecone, RAG, retrieval augmented generation, Tesla earnings, Cybertruck analysis, tracing, observability, orchestration, guardrails, retries, AIBROS podcast, Nisaar, Rohan, AI coding live, Generative AI, Large Language Models, machine learning, Python AI, Vertex AI Hashtags: #AIBROS #GoogleAIStudio #GoogleADK #MultiAgent #Veo31 #ImageGen #RAG #SQL #FastAPI #Python #LLM #GenAI #AIEngineering