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The DevFest Community Workshop Experience: Building Real Agents Together
Google introduced 'Workbench,' a new workshop experience launched at DevFest in New York City to teach engineers how to build self-evolving multi-agent systems. The program prioritizes architectural mental models over syntax and code snippets.
Why it matters
Engineers can create more reliable AI agents and reduce idle compute costs by learning to separate state from active compute. This approach replaces unpredictable prompt engineering with durable architectural boundaries.
The big picture
This initiative complements Google's broader deployment of agentic technology and AI training seen in its Public Sector and educator programs.
The details
Ricky Robinett explained that prompt engineering is a probabilistic suggestion rather than a strict execution boundary. The workshop included speed quizzes and training on self-patching harnesses to detect spend anomalies. Participants explored the Gemini Enterprise Agent Platform's Memory Bank.
What's next
The Workbench experience will tour five additional cities, including Sunnyvale, Washington DC, Atlanta, Seattle, and Boston, through November 10.
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In this article
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Technologies
Topics
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Key connections
Google owns RAG Engine
Christina Lin works at Google
Americas DevRel Team members
Ricky Robinett works at Google
Senior Director of Developer Marketing
Rachel Francois leads Google Developer Groups (GDG)
Google Developer Groups (GDG) North America Program Lead
Logan Hennessy works at Google
Americas Developer Relations Engineer (DRE)
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Workbench is related to graph engineering
Workbench is related to self-evolving architectures
Workbench is related to automated self-patching harnesses
Memory Bank is related to Gemini Enterprise Agent Platform
Memory Bank on Gemini Enterprise Agent Platform
RAG Engine is related to Gemini Enterprise Agent Platform
RAG Engine on Gemini Enterprise Agent Platform
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