AI Deep Dive with Google (Ep 2) - Orchestrating Agents with ADK 2.0
Event PAST

AI Deep Dive with Google (Ep 2) - Orchestrating Agents with ADK 2.0

05 August Online

About this event

The AI Deep Dive Series is a hands-on virtual initiative designed to empower developers to architect the next generation of Agentic AI. Moving beyond basic prompting, this series guides you through the complete engineering lifecycle using Google’s advanced stack.
You will master the transition from local Gemini CLI environments to building intelligent agents with the Agent Development Kit (ADK) and Model Context Protocol (MCP), culminating in the deployment of secure, collaborative Agent-to-Agent (A2A) ecosystems on Google Cloud Run. Join us to build AI systems that can truly reason, act, and scale.
Each session includes ▶️ a deep-dive talk, live demo, 🧑‍💻 hands-on code labs, and 🤝 networking with speakers and a global tech community (developers, engineers, builders and tech leaders).
Tech Talk: Wrangling unstructured data with LLM-driven vector embedding
Speaker: Annie Wang (Google)
Abstract: ADK 2.0, Google's Agent Development Kit, fixes this with three orchestration patterns: graph workflows, collaborative agents, and dynamic workflows. In this hands-on webinar, you'll watch all three run live inside a single app, then build them yourself, step by step, in a Colab lab. We'll cover when each pattern fits, how ADK 2.0 turns hidden control flow into visible, testable structure, and the one question that tells you which pattern to reach for. You'll leave with working code and a decision tree you can apply to your own agents the next day.
Venue:
virtual, join from anywhere.
Global AI Tech Community on Discord
Join us on discord for local and global AI tech community:
- Events chat: chat and connect with speakers and global and local attendees;
- Learning AI: events\, learning materials\, study groups;
- Startups: innovation\, projects collaborations\, founders/co-founders;
- Jobs and Careers: job openings\, post resumes\, hiring managers

Want to find AI jobs?

Join thousands of AI professionals finding their next opportunity

We respect your inbox. Unsubscribe at any time.

© 2026 DevFound.ai. All rights reserved.

Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.